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| author | Prashant Sharma <prashant.s@imaginea.com> | 2013-09-06 17:53:01 +0530 |
|---|---|---|
| committer | Prashant Sharma <prashant.s@imaginea.com> | 2013-09-06 17:53:01 +0530 |
| commit | 4106ae9fbf8a582697deba2198b3b966dec00bfe (patch) | |
| tree | 7c3046faee5f62f9ec4c4176125988d7cb5d70e2 /core | |
| parent | e0dd24dc858777904335218f3001a24bffe73b27 (diff) | |
| parent | 5c7494d7c1b7301138fb3dc155a1b0c961126ec6 (diff) | |
| download | spark-4106ae9fbf8a582697deba2198b3b966dec00bfe.tar.gz spark-4106ae9fbf8a582697deba2198b3b966dec00bfe.tar.bz2 spark-4106ae9fbf8a582697deba2198b3b966dec00bfe.zip | |
Merged with master
Diffstat (limited to 'core')
456 files changed, 15777 insertions, 8683 deletions
diff --git a/core/pom.xml b/core/pom.xml index a55f58a9db..076236e20a 100644 --- a/core/pom.xml +++ b/core/pom.xml @@ -1,21 +1,50 @@ <?xml version="1.0" encoding="UTF-8"?> +<!-- + ~ Licensed to the Apache Software Foundation (ASF) under one or more + ~ contributor license agreements. See the NOTICE file distributed with + ~ this work for additional information regarding copyright ownership. + ~ The ASF licenses this file to You under the Apache License, Version 2.0 + ~ (the "License"); you may not use this file except in compliance with + ~ the License. You may obtain a copy of the License at + ~ + ~ http://www.apache.org/licenses/LICENSE-2.0 + ~ + ~ Unless required by applicable law or agreed to in writing, software + ~ distributed under the License is distributed on an "AS IS" BASIS, + ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + ~ See the License for the specific language governing permissions and + ~ limitations under the License. + --> + <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> - <groupId>org.spark-project</groupId> + <groupId>org.apache.spark</groupId> <artifactId>spark-parent</artifactId> <version>0.8.0-SNAPSHOT</version> <relativePath>../pom.xml</relativePath> </parent> - <groupId>org.spark-project</groupId> + <groupId>org.apache.spark</groupId> <artifactId>spark-core</artifactId> <packaging>jar</packaging> <name>Spark Project Core</name> - <url>http://spark-project.org/</url> + <url>http://spark.incubator.apache.org/</url> <dependencies> <dependency> + <groupId>org.apache.hadoop</groupId> + <artifactId>hadoop-client</artifactId> + </dependency> + <dependency> + <groupId>org.apache.avro</groupId> + <artifactId>avro</artifactId> + </dependency> + <dependency> + <groupId>org.apache.avro</groupId> + <artifactId>avro-ipc</artifactId> + </dependency> + <dependency> <groupId>org.eclipse.jetty</groupId> <artifactId>jetty-server</artifactId> </dependency> @@ -24,6 +53,10 @@ <artifactId>guava</artifactId> </dependency> <dependency> + <groupId>com.google.code.findbugs</groupId> + <artifactId>jsr305</artifactId> + </dependency> + <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-api</artifactId> </dependency> @@ -32,6 +65,10 @@ <artifactId>compress-lzf</artifactId> </dependency> <dependency> + <groupId>org.xerial.snappy</groupId> + <artifactId>snappy-java</artifactId> + </dependency> + <dependency> <groupId>org.ow2.asm</groupId> <artifactId>asm</artifactId> </dependency> @@ -40,8 +77,14 @@ <artifactId>protobuf-java</artifactId> </dependency> <dependency> - <groupId>de.javakaffee</groupId> - <artifactId>kryo-serializers</artifactId> + <groupId>com.twitter</groupId> + <artifactId>chill_2.9.3</artifactId> + <version>0.3.1</version> + </dependency> + <dependency> + <groupId>com.twitter</groupId> + <artifactId>chill-java</artifactId> + <version>0.3.1</version> </dependency> <dependency> <groupId>org.scala-lang</groupId> @@ -91,7 +134,18 @@ <groupId>log4j</groupId> <artifactId>log4j</artifactId> </dependency> - + <dependency> + <groupId>com.codahale.metrics</groupId> + <artifactId>metrics-core</artifactId> + </dependency> + <dependency> + <groupId>com.codahale.metrics</groupId> + <artifactId>metrics-jvm</artifactId> + </dependency> + <dependency> + <groupId>com.codahale.metrics</groupId> + <artifactId>metrics-json</artifactId> + </dependency> <dependency> <groupId>org.apache.derby</groupId> <artifactId>derby</artifactId> @@ -169,183 +223,4 @@ </plugin> </plugins> </build> - - <profiles> - <profile> - <id>hadoop1</id> - <dependencies> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-core</artifactId> - <scope>provided</scope> - </dependency> - </dependencies> - <build> - <plugins> - <plugin> - <groupId>org.codehaus.mojo</groupId> - <artifactId>build-helper-maven-plugin</artifactId> - <executions> - <execution> - <id>add-source</id> - <phase>generate-sources</phase> - <goals> - <goal>add-source</goal> - </goals> - <configuration> - <sources> - <source>src/main/scala</source> - <source>src/hadoop1/scala</source> - </sources> - </configuration> - </execution> - <execution> - <id>add-scala-test-sources</id> - <phase>generate-test-sources</phase> - <goals> - <goal>add-test-source</goal> - </goals> - <configuration> - <sources> - <source>src/test/scala</source> - </sources> - </configuration> - </execution> - </executions> - </plugin> - <plugin> - <groupId>org.apache.maven.plugins</groupId> - <artifactId>maven-jar-plugin</artifactId> - <configuration> - <classifier>hadoop1</classifier> - </configuration> - </plugin> - </plugins> - </build> - </profile> - <profile> - <id>hadoop2</id> - <dependencies> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-core</artifactId> - <scope>provided</scope> - </dependency> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-client</artifactId> - <scope>provided</scope> - </dependency> - </dependencies> - <build> - <plugins> - <plugin> - <groupId>org.codehaus.mojo</groupId> - <artifactId>build-helper-maven-plugin</artifactId> - <executions> - <execution> - <id>add-source</id> - <phase>generate-sources</phase> - <goals> - <goal>add-source</goal> - </goals> - <configuration> - <sources> - <source>src/main/scala</source> - <source>src/hadoop2/scala</source> - </sources> - </configuration> - </execution> - <execution> - <id>add-scala-test-sources</id> - <phase>generate-test-sources</phase> - <goals> - <goal>add-test-source</goal> - </goals> - <configuration> - <sources> - <source>src/test/scala</source> - </sources> - </configuration> - </execution> - </executions> - </plugin> - <plugin> - <groupId>org.apache.maven.plugins</groupId> - <artifactId>maven-jar-plugin</artifactId> - <configuration> - <classifier>hadoop2</classifier> - </configuration> - </plugin> - </plugins> - </build> - </profile> - <profile> - <id>hadoop2-yarn</id> - <dependencies> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-client</artifactId> - <scope>provided</scope> - </dependency> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-yarn-api</artifactId> - <scope>provided</scope> - </dependency> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-yarn-common</artifactId> - <scope>provided</scope> - </dependency> - <dependency> - <groupId>org.apache.hadoop</groupId> - <artifactId>hadoop-yarn-client</artifactId> - <scope>provided</scope> - </dependency> - </dependencies> - <build> - <plugins> - <plugin> - <groupId>org.codehaus.mojo</groupId> - <artifactId>build-helper-maven-plugin</artifactId> - <executions> - <execution> - <id>add-source</id> - <phase>generate-sources</phase> - <goals> - <goal>add-source</goal> - </goals> - <configuration> - <sources> - <source>src/main/scala</source> - <source>src/hadoop2-yarn/scala</source> - </sources> - </configuration> - </execution> - <execution> - <id>add-scala-test-sources</id> - <phase>generate-test-sources</phase> - <goals> - <goal>add-test-source</goal> - </goals> - <configuration> - <sources> - <source>src/test/scala</source> - </sources> - </configuration> - </execution> - </executions> - </plugin> - <plugin> - <groupId>org.apache.maven.plugins</groupId> - <artifactId>maven-jar-plugin</artifactId> - <configuration> - <classifier>hadoop2-yarn</classifier> - </configuration> - </plugin> - </plugins> - </build> - </profile> - </profiles> </project> diff --git a/core/src/hadoop1/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala b/core/src/hadoop1/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala deleted file mode 100644 index f286f2cf9c..0000000000 --- a/core/src/hadoop1/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.apache.hadoop.mapred - -trait HadoopMapRedUtil { - def newJobContext(conf: JobConf, jobId: JobID): JobContext = new JobContext(conf, jobId) - - def newTaskAttemptContext(conf: JobConf, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContext(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = new TaskAttemptID(jtIdentifier, - jobId, isMap, taskId, attemptId) -} diff --git a/core/src/hadoop1/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala b/core/src/hadoop1/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala deleted file mode 100644 index 264d421d14..0000000000 --- a/core/src/hadoop1/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala +++ /dev/null @@ -1,12 +0,0 @@ -package org.apache.hadoop.mapreduce - -import org.apache.hadoop.conf.Configuration - -trait HadoopMapReduceUtil { - def newJobContext(conf: Configuration, jobId: JobID): JobContext = new JobContext(conf, jobId) - - def newTaskAttemptContext(conf: Configuration, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContext(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = new TaskAttemptID(jtIdentifier, - jobId, isMap, taskId, attemptId) -} diff --git a/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala deleted file mode 100644 index f1c86de4cc..0000000000 --- a/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala +++ /dev/null @@ -1,27 +0,0 @@ -package spark.deploy -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.mapred.JobConf - - -/** - * Contains util methods to interact with Hadoop from spark. - */ -object SparkHadoopUtil { - - def getUserNameFromEnvironment(): String = { - // defaulting to -D ... - System.getProperty("user.name") - } - - def runAsUser(func: (Product) => Unit, args: Product) { - - // Add support, if exists - for now, simply run func ! - func(args) - } - - // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems - def newConfiguration(): Configuration = new Configuration() - - // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster - def addCredentials(conf: JobConf) {} -} diff --git a/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala b/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala deleted file mode 100644 index 875c0a220b..0000000000 --- a/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala +++ /dev/null @@ -1,13 +0,0 @@ - -package org.apache.hadoop.mapred - -import org.apache.hadoop.mapreduce.TaskType - -trait HadoopMapRedUtil { - def newJobContext(conf: JobConf, jobId: JobID): JobContext = new JobContextImpl(conf, jobId) - - def newTaskAttemptContext(conf: JobConf, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContextImpl(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = - new TaskAttemptID(jtIdentifier, jobId, if (isMap) TaskType.MAP else TaskType.REDUCE, taskId, attemptId) -} diff --git a/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala b/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala deleted file mode 100644 index 8bc6fb6dea..0000000000 --- a/core/src/hadoop2-yarn/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala +++ /dev/null @@ -1,13 +0,0 @@ -package org.apache.hadoop.mapreduce - -import org.apache.hadoop.conf.Configuration -import task.{TaskAttemptContextImpl, JobContextImpl} - -trait HadoopMapReduceUtil { - def newJobContext(conf: Configuration, jobId: JobID): JobContext = new JobContextImpl(conf, jobId) - - def newTaskAttemptContext(conf: Configuration, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContextImpl(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = - new TaskAttemptID(jtIdentifier, jobId, if (isMap) TaskType.MAP else TaskType.REDUCE, taskId, attemptId) -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala deleted file mode 100644 index 301a57fffa..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala +++ /dev/null @@ -1,59 +0,0 @@ -package spark.deploy - -import collection.mutable.HashMap -import org.apache.hadoop.mapred.JobConf -import org.apache.hadoop.security.UserGroupInformation -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment -import java.security.PrivilegedExceptionAction - -/** - * Contains util methods to interact with Hadoop from spark. - */ -object SparkHadoopUtil { - - val yarnConf = newConfiguration() - - def getUserNameFromEnvironment(): String = { - // defaulting to env if -D is not present ... - val retval = System.getProperty(Environment.USER.name, System.getenv(Environment.USER.name)) - - // If nothing found, default to user we are running as - if (retval == null) System.getProperty("user.name") else retval - } - - def runAsUser(func: (Product) => Unit, args: Product) { - runAsUser(func, args, getUserNameFromEnvironment()) - } - - def runAsUser(func: (Product) => Unit, args: Product, user: String) { - func(args) - } - - // Note that all params which start with SPARK are propagated all the way through, so if in yarn mode, this MUST be set to true. - def isYarnMode(): Boolean = { - val yarnMode = System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE")) - java.lang.Boolean.valueOf(yarnMode) - } - - // Set an env variable indicating we are running in YARN mode. - // Note that anything with SPARK prefix gets propagated to all (remote) processes - def setYarnMode() { - System.setProperty("SPARK_YARN_MODE", "true") - } - - def setYarnMode(env: HashMap[String, String]) { - env("SPARK_YARN_MODE") = "true" - } - - // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems - // Always create a new config, dont reuse yarnConf. - def newConfiguration(): Configuration = new YarnConfiguration(new Configuration()) - - // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster - def addCredentials(conf: JobConf) { - val jobCreds = conf.getCredentials(); - jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials()) - } -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMaster.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMaster.scala deleted file mode 100644 index 6a0617cc06..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMaster.scala +++ /dev/null @@ -1,334 +0,0 @@ -package spark.deploy.yarn - -import java.net.Socket -import java.util.concurrent.CopyOnWriteArrayList -import java.util.concurrent.atomic.{AtomicInteger, AtomicReference} -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.net.NetUtils -import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.api.protocolrecords._ -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.yarn.ipc.YarnRPC -import org.apache.hadoop.yarn.util.{ConverterUtils, Records} -import scala.collection.JavaConversions._ -import spark.{SparkContext, Logging, Utils} -import org.apache.hadoop.security.UserGroupInformation -import java.security.PrivilegedExceptionAction - -class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) extends Logging { - - def this(args: ApplicationMasterArguments) = this(args, new Configuration()) - - private var rpc: YarnRPC = YarnRPC.create(conf) - private var resourceManager: AMRMProtocol = null - private var appAttemptId: ApplicationAttemptId = null - private var userThread: Thread = null - private val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - - private var yarnAllocator: YarnAllocationHandler = null - private var isFinished:Boolean = false - - def run() { - - appAttemptId = getApplicationAttemptId() - resourceManager = registerWithResourceManager() - val appMasterResponse: RegisterApplicationMasterResponse = registerApplicationMaster() - - // Compute number of threads for akka - val minimumMemory = appMasterResponse.getMinimumResourceCapability().getMemory() - - if (minimumMemory > 0) { - val mem = args.workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD - val numCore = (mem / minimumMemory) + (if (0 != (mem % minimumMemory)) 1 else 0) - - if (numCore > 0) { - // do not override - hits https://issues.apache.org/jira/browse/HADOOP-8406 - // TODO: Uncomment when hadoop is on a version which has this fixed. - // args.workerCores = numCore - } - } - - // Workaround until hadoop moves to something which has - // https://issues.apache.org/jira/browse/HADOOP-8406 - // ignore result - // This does not, unfortunately, always work reliably ... but alleviates the bug a lot of times - // Hence args.workerCores = numCore disabled above. Any better option ? - // org.apache.hadoop.io.compress.CompressionCodecFactory.getCodecClasses(conf) - - ApplicationMaster.register(this) - // Start the user's JAR - userThread = startUserClass() - - // This a bit hacky, but we need to wait until the spark.driver.port property has - // been set by the Thread executing the user class. - waitForSparkMaster() - - // Allocate all containers - allocateWorkers() - - // Wait for the user class to Finish - userThread.join() - - System.exit(0) - } - - private def getApplicationAttemptId(): ApplicationAttemptId = { - val envs = System.getenv() - val containerIdString = envs.get(ApplicationConstants.AM_CONTAINER_ID_ENV) - val containerId = ConverterUtils.toContainerId(containerIdString) - val appAttemptId = containerId.getApplicationAttemptId() - logInfo("ApplicationAttemptId: " + appAttemptId) - return appAttemptId - } - - private def registerWithResourceManager(): AMRMProtocol = { - val rmAddress = NetUtils.createSocketAddr(yarnConf.get( - YarnConfiguration.RM_SCHEDULER_ADDRESS, - YarnConfiguration.DEFAULT_RM_SCHEDULER_ADDRESS)) - logInfo("Connecting to ResourceManager at " + rmAddress) - return rpc.getProxy(classOf[AMRMProtocol], rmAddress, conf).asInstanceOf[AMRMProtocol] - } - - private def registerApplicationMaster(): RegisterApplicationMasterResponse = { - logInfo("Registering the ApplicationMaster") - val appMasterRequest = Records.newRecord(classOf[RegisterApplicationMasterRequest]) - .asInstanceOf[RegisterApplicationMasterRequest] - appMasterRequest.setApplicationAttemptId(appAttemptId) - // Setting this to master host,port - so that the ApplicationReport at client has some sensible info. - // Users can then monitor stderr/stdout on that node if required. - appMasterRequest.setHost(Utils.localHostName()) - appMasterRequest.setRpcPort(0) - // What do we provide here ? Might make sense to expose something sensible later ? - appMasterRequest.setTrackingUrl("") - return resourceManager.registerApplicationMaster(appMasterRequest) - } - - private def waitForSparkMaster() { - logInfo("Waiting for spark driver to be reachable.") - var driverUp = false - while(!driverUp) { - val driverHost = System.getProperty("spark.driver.host") - val driverPort = System.getProperty("spark.driver.port") - try { - val socket = new Socket(driverHost, driverPort.toInt) - socket.close() - logInfo("Master now available: " + driverHost + ":" + driverPort) - driverUp = true - } catch { - case e: Exception => - logError("Failed to connect to driver at " + driverHost + ":" + driverPort) - Thread.sleep(100) - } - } - } - - private def startUserClass(): Thread = { - logInfo("Starting the user JAR in a separate Thread") - val mainMethod = Class.forName(args.userClass, false, Thread.currentThread.getContextClassLoader) - .getMethod("main", classOf[Array[String]]) - val t = new Thread { - override def run() { - var successed = false - try { - // Copy - var mainArgs: Array[String] = new Array[String](args.userArgs.size()) - args.userArgs.copyToArray(mainArgs, 0, args.userArgs.size()) - mainMethod.invoke(null, mainArgs) - // some job script has "System.exit(0)" at the end, for example SparkPi, SparkLR - // userThread will stop here unless it has uncaught exception thrown out - // It need shutdown hook to set SUCCEEDED - successed = true - } finally { - if (successed) { - ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED) - } else { - ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.FAILED) - } - } - } - } - t.start() - return t - } - - private def allocateWorkers() { - logInfo("Waiting for spark context initialization") - - try { - var sparkContext: SparkContext = null - ApplicationMaster.sparkContextRef.synchronized { - var count = 0 - while (ApplicationMaster.sparkContextRef.get() == null) { - logInfo("Waiting for spark context initialization ... " + count) - count = count + 1 - ApplicationMaster.sparkContextRef.wait(10000L) - } - sparkContext = ApplicationMaster.sparkContextRef.get() - assert(sparkContext != null) - this.yarnAllocator = YarnAllocationHandler.newAllocator(yarnConf, resourceManager, appAttemptId, args, sparkContext.preferredNodeLocationData) - } - - - logInfo("Allocating " + args.numWorkers + " workers.") - // Wait until all containers have finished - // TODO: This is a bit ugly. Can we make it nicer? - // TODO: Handle container failure - while(yarnAllocator.getNumWorkersRunning < args.numWorkers && - // If user thread exists, then quit ! - userThread.isAlive) { - - this.yarnAllocator.allocateContainers(math.max(args.numWorkers - yarnAllocator.getNumWorkersRunning, 0)) - ApplicationMaster.incrementAllocatorLoop(1) - Thread.sleep(100) - } - } finally { - // in case of exceptions, etc - ensure that count is atleast ALLOCATOR_LOOP_WAIT_COUNT : - // so that the loop (in ApplicationMaster.sparkContextInitialized) breaks - ApplicationMaster.incrementAllocatorLoop(ApplicationMaster.ALLOCATOR_LOOP_WAIT_COUNT) - } - logInfo("All workers have launched.") - - // Launch a progress reporter thread, else app will get killed after expiration (def: 10mins) timeout - if (userThread.isAlive) { - // ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapse. - - val timeoutInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000) - // must be <= timeoutInterval/ 2. - // On other hand, also ensure that we are reasonably responsive without causing too many requests to RM. - // so atleast 1 minute or timeoutInterval / 10 - whichever is higher. - val interval = math.min(timeoutInterval / 2, math.max(timeoutInterval/ 10, 60000L)) - launchReporterThread(interval) - } - } - - // TODO: We might want to extend this to allocate more containers in case they die ! - private def launchReporterThread(_sleepTime: Long): Thread = { - val sleepTime = if (_sleepTime <= 0 ) 0 else _sleepTime - - val t = new Thread { - override def run() { - while (userThread.isAlive) { - val missingWorkerCount = args.numWorkers - yarnAllocator.getNumWorkersRunning - if (missingWorkerCount > 0) { - logInfo("Allocating " + missingWorkerCount + " containers to make up for (potentially ?) lost containers") - yarnAllocator.allocateContainers(missingWorkerCount) - } - else sendProgress() - Thread.sleep(sleepTime) - } - } - } - // setting to daemon status, though this is usually not a good idea. - t.setDaemon(true) - t.start() - logInfo("Started progress reporter thread - sleep time : " + sleepTime) - return t - } - - private def sendProgress() { - logDebug("Sending progress") - // simulated with an allocate request with no nodes requested ... - yarnAllocator.allocateContainers(0) - } - - /* - def printContainers(containers: List[Container]) = { - for (container <- containers) { - logInfo("Launching shell command on a new container." - + ", containerId=" + container.getId() - + ", containerNode=" + container.getNodeId().getHost() - + ":" + container.getNodeId().getPort() - + ", containerNodeURI=" + container.getNodeHttpAddress() - + ", containerState" + container.getState() - + ", containerResourceMemory" - + container.getResource().getMemory()) - } - } - */ - - def finishApplicationMaster(status: FinalApplicationStatus) { - - synchronized { - if (isFinished) { - return - } - isFinished = true - } - - logInfo("finishApplicationMaster with " + status) - val finishReq = Records.newRecord(classOf[FinishApplicationMasterRequest]) - .asInstanceOf[FinishApplicationMasterRequest] - finishReq.setAppAttemptId(appAttemptId) - finishReq.setFinishApplicationStatus(status) - resourceManager.finishApplicationMaster(finishReq) - - } - -} - -object ApplicationMaster { - // number of times to wait for the allocator loop to complete. - // each loop iteration waits for 100ms, so maximum of 3 seconds. - // This is to ensure that we have reasonable number of containers before we start - // TODO: Currently, task to container is computed once (TaskSetManager) - which need not be optimal as more - // containers are available. Might need to handle this better. - private val ALLOCATOR_LOOP_WAIT_COUNT = 30 - def incrementAllocatorLoop(by: Int) { - val count = yarnAllocatorLoop.getAndAdd(by) - if (count >= ALLOCATOR_LOOP_WAIT_COUNT) { - yarnAllocatorLoop.synchronized { - // to wake threads off wait ... - yarnAllocatorLoop.notifyAll() - } - } - } - - private val applicationMasters = new CopyOnWriteArrayList[ApplicationMaster]() - - def register(master: ApplicationMaster) { - applicationMasters.add(master) - } - - val sparkContextRef: AtomicReference[SparkContext] = new AtomicReference[SparkContext](null) - val yarnAllocatorLoop: AtomicInteger = new AtomicInteger(0) - - def sparkContextInitialized(sc: SparkContext): Boolean = { - var modified = false - sparkContextRef.synchronized { - modified = sparkContextRef.compareAndSet(null, sc) - sparkContextRef.notifyAll() - } - - // Add a shutdown hook - as a best case effort in case users do not call sc.stop or do System.exit - // Should not really have to do this, but it helps yarn to evict resources earlier. - // not to mention, prevent Client declaring failure even though we exit'ed properly. - if (modified) { - Runtime.getRuntime().addShutdownHook(new Thread with Logging { - // This is not just to log, but also to ensure that log system is initialized for this instance when we actually are 'run' - logInfo("Adding shutdown hook for context " + sc) - override def run() { - logInfo("Invoking sc stop from shutdown hook") - sc.stop() - // best case ... - for (master <- applicationMasters) { - master.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED) - } - } - } ) - } - - // Wait for initialization to complete and atleast 'some' nodes can get allocated - yarnAllocatorLoop.synchronized { - while (yarnAllocatorLoop.get() <= ALLOCATOR_LOOP_WAIT_COUNT) { - yarnAllocatorLoop.wait(1000L) - } - } - modified - } - - def main(argStrings: Array[String]) { - val args = new ApplicationMasterArguments(argStrings) - new ApplicationMaster(args).run() - } -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMasterArguments.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMasterArguments.scala deleted file mode 100644 index 1b00208511..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ApplicationMasterArguments.scala +++ /dev/null @@ -1,77 +0,0 @@ -package spark.deploy.yarn - -import spark.util.IntParam -import collection.mutable.ArrayBuffer - -class ApplicationMasterArguments(val args: Array[String]) { - var userJar: String = null - var userClass: String = null - var userArgs: Seq[String] = Seq[String]() - var workerMemory = 1024 - var workerCores = 1 - var numWorkers = 2 - - parseArgs(args.toList) - - private def parseArgs(inputArgs: List[String]): Unit = { - val userArgsBuffer = new ArrayBuffer[String]() - - var args = inputArgs - - while (! args.isEmpty) { - - args match { - case ("--jar") :: value :: tail => - userJar = value - args = tail - - case ("--class") :: value :: tail => - userClass = value - args = tail - - case ("--args") :: value :: tail => - userArgsBuffer += value - args = tail - - case ("--num-workers") :: IntParam(value) :: tail => - numWorkers = value - args = tail - - case ("--worker-memory") :: IntParam(value) :: tail => - workerMemory = value - args = tail - - case ("--worker-cores") :: IntParam(value) :: tail => - workerCores = value - args = tail - - case Nil => - if (userJar == null || userClass == null) { - printUsageAndExit(1) - } - - case _ => - printUsageAndExit(1, args) - } - } - - userArgs = userArgsBuffer.readOnly - } - - def printUsageAndExit(exitCode: Int, unknownParam: Any = null) { - if (unknownParam != null) { - System.err.println("Unknown/unsupported param " + unknownParam) - } - System.err.println( - "Usage: spark.deploy.yarn.ApplicationMaster [options] \n" + - "Options:\n" + - " --jar JAR_PATH Path to your application's JAR file (required)\n" + - " --class CLASS_NAME Name of your application's main class (required)\n" + - " --args ARGS Arguments to be passed to your application's main class.\n" + - " Mutliple invocations are possible, each will be passed in order.\n" + - " --num-workers NUM Number of workers to start (Default: 2)\n" + - " --worker-cores NUM Number of cores for the workers (Default: 1)\n" + - " --worker-memory MEM Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n") - System.exit(exitCode) - } -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala deleted file mode 100644 index 514c17f241..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala +++ /dev/null @@ -1,310 +0,0 @@ -package spark.deploy.yarn - -import java.net.{InetSocketAddress, URI} -import java.nio.ByteBuffer -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} -import org.apache.hadoop.mapred.Master -import org.apache.hadoop.net.NetUtils -import org.apache.hadoop.io.DataOutputBuffer -import org.apache.hadoop.security.UserGroupInformation -import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.api.protocolrecords._ -import org.apache.hadoop.yarn.client.YarnClientImpl -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.yarn.ipc.YarnRPC -import scala.collection.mutable.HashMap -import scala.collection.JavaConversions._ -import spark.{Logging, Utils} -import org.apache.hadoop.yarn.util.{Apps, Records, ConverterUtils} -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment -import spark.deploy.SparkHadoopUtil - -class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl with Logging { - - def this(args: ClientArguments) = this(new Configuration(), args) - - var rpc: YarnRPC = YarnRPC.create(conf) - val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - val credentials = UserGroupInformation.getCurrentUser().getCredentials(); - - def run() { - init(yarnConf) - start() - logClusterResourceDetails() - - val newApp = super.getNewApplication() - val appId = newApp.getApplicationId() - - verifyClusterResources(newApp) - val appContext = createApplicationSubmissionContext(appId) - val localResources = prepareLocalResources(appId, "spark") - val env = setupLaunchEnv(localResources) - val amContainer = createContainerLaunchContext(newApp, localResources, env) - - appContext.setQueue(args.amQueue) - appContext.setAMContainerSpec(amContainer) - appContext.setUser(UserGroupInformation.getCurrentUser().getShortUserName()) - - submitApp(appContext) - - monitorApplication(appId) - System.exit(0) - } - - - def logClusterResourceDetails() { - val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics - logInfo("Got Cluster metric info from ASM, numNodeManagers=" + clusterMetrics.getNumNodeManagers) - - val queueInfo: QueueInfo = super.getQueueInfo(args.amQueue) - logInfo("Queue info .. queueName=" + queueInfo.getQueueName + ", queueCurrentCapacity=" + queueInfo.getCurrentCapacity + - ", queueMaxCapacity=" + queueInfo.getMaximumCapacity + ", queueApplicationCount=" + queueInfo.getApplications.size + - ", queueChildQueueCount=" + queueInfo.getChildQueues.size) - } - - - def verifyClusterResources(app: GetNewApplicationResponse) = { - val maxMem = app.getMaximumResourceCapability().getMemory() - logInfo("Max mem capabililty of a single resource in this cluster " + maxMem) - - // if we have requested more then the clusters max for a single resource then exit. - if (args.workerMemory > maxMem) { - logError("the worker size is to large to run on this cluster " + args.workerMemory); - System.exit(1) - } - val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD - if (amMem > maxMem) { - logError("AM size is to large to run on this cluster " + amMem) - System.exit(1) - } - - // We could add checks to make sure the entire cluster has enough resources but that involves getting - // all the node reports and computing ourselves - } - - def createApplicationSubmissionContext(appId: ApplicationId): ApplicationSubmissionContext = { - logInfo("Setting up application submission context for ASM") - val appContext = Records.newRecord(classOf[ApplicationSubmissionContext]) - appContext.setApplicationId(appId) - appContext.setApplicationName("Spark") - return appContext - } - - def prepareLocalResources(appId: ApplicationId, appName: String): HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - val locaResources = HashMap[String, LocalResource]() - // Upload Spark and the application JAR to the remote file system - // Add them as local resources to the AM - val fs = FileSystem.get(conf) - - val delegTokenRenewer = Master.getMasterPrincipal(conf); - if (UserGroupInformation.isSecurityEnabled()) { - if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) { - logError("Can't get Master Kerberos principal for use as renewer") - System.exit(1) - } - } - - Map("spark.jar" -> System.getenv("SPARK_JAR"), "app.jar" -> args.userJar, "log4j.properties" -> System.getenv("SPARK_LOG4J_CONF")) - .foreach { case(destName, _localPath) => - val localPath: String = if (_localPath != null) _localPath.trim() else "" - if (! localPath.isEmpty()) { - val src = new Path(localPath) - val pathSuffix = appName + "/" + appId.getId() + destName - val dst = new Path(fs.getHomeDirectory(), pathSuffix) - logInfo("Uploading " + src + " to " + dst) - fs.copyFromLocalFile(false, true, src, dst) - val destStatus = fs.getFileStatus(dst) - - // get tokens for anything we upload to hdfs - if (UserGroupInformation.isSecurityEnabled()) { - fs.addDelegationTokens(delegTokenRenewer, credentials); - } - - val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - amJarRsrc.setType(LocalResourceType.FILE) - amJarRsrc.setVisibility(LocalResourceVisibility.APPLICATION) - amJarRsrc.setResource(ConverterUtils.getYarnUrlFromPath(dst)) - amJarRsrc.setTimestamp(destStatus.getModificationTime()) - amJarRsrc.setSize(destStatus.getLen()) - locaResources(destName) = amJarRsrc - } - } - UserGroupInformation.getCurrentUser().addCredentials(credentials); - return locaResources - } - - def setupLaunchEnv(localResources: HashMap[String, LocalResource]): HashMap[String, String] = { - logInfo("Setting up the launch environment") - val log4jConfLocalRes = localResources.getOrElse("log4j.properties", null) - - val env = new HashMap[String, String]() - - // If log4j present, ensure ours overrides all others - if (log4jConfLocalRes != null) Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./") - - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./*") - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "$CLASSPATH") - Client.populateHadoopClasspath(yarnConf, env) - SparkHadoopUtil.setYarnMode(env) - env("SPARK_YARN_JAR_PATH") = - localResources("spark.jar").getResource().getScheme.toString() + "://" + - localResources("spark.jar").getResource().getFile().toString() - env("SPARK_YARN_JAR_TIMESTAMP") = localResources("spark.jar").getTimestamp().toString() - env("SPARK_YARN_JAR_SIZE") = localResources("spark.jar").getSize().toString() - - env("SPARK_YARN_USERJAR_PATH") = - localResources("app.jar").getResource().getScheme.toString() + "://" + - localResources("app.jar").getResource().getFile().toString() - env("SPARK_YARN_USERJAR_TIMESTAMP") = localResources("app.jar").getTimestamp().toString() - env("SPARK_YARN_USERJAR_SIZE") = localResources("app.jar").getSize().toString() - - if (log4jConfLocalRes != null) { - env("SPARK_YARN_LOG4J_PATH") = - log4jConfLocalRes.getResource().getScheme.toString() + "://" + log4jConfLocalRes.getResource().getFile().toString() - env("SPARK_YARN_LOG4J_TIMESTAMP") = log4jConfLocalRes.getTimestamp().toString() - env("SPARK_YARN_LOG4J_SIZE") = log4jConfLocalRes.getSize().toString() - } - - - // Add each SPARK-* key to the environment - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - return env - } - - def userArgsToString(clientArgs: ClientArguments): String = { - val prefix = " --args " - val args = clientArgs.userArgs - val retval = new StringBuilder() - for (arg <- args){ - retval.append(prefix).append(" '").append(arg).append("' ") - } - - retval.toString - } - - def createContainerLaunchContext(newApp: GetNewApplicationResponse, - localResources: HashMap[String, LocalResource], - env: HashMap[String, String]): ContainerLaunchContext = { - logInfo("Setting up container launch context") - val amContainer = Records.newRecord(classOf[ContainerLaunchContext]) - amContainer.setLocalResources(localResources) - amContainer.setEnvironment(env) - - val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory() - - var amMemory = ((args.amMemory / minResMemory) * minResMemory) + - (if (0 != (args.amMemory % minResMemory)) minResMemory else 0) - YarnAllocationHandler.MEMORY_OVERHEAD - - // Extra options for the JVM - var JAVA_OPTS = "" - - // Add Xmx for am memory - JAVA_OPTS += "-Xmx" + amMemory + "m " - - // Commenting it out for now - so that people can refer to the properties if required. Remove it once cpuset version is pushed out. - // The context is, default gc for server class machines end up using all cores to do gc - hence if there are multiple containers in same - // node, spark gc effects all other containers performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in multi-tenant environments. Not sure how default java gc behaves if it is - // limited to subset of cores on a node. - if (env.isDefinedAt("SPARK_USE_CONC_INCR_GC") && java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))) { - // In our expts, using (default) throughput collector has severe perf ramnifications in multi-tenant machines - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " - } - - // Command for the ApplicationMaster - var javaCommand = "java"; - val javaHome = System.getenv("JAVA_HOME") - if (javaHome != null && !javaHome.isEmpty()) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String](javaCommand + - " -server " + - JAVA_OPTS + - " spark.deploy.yarn.ApplicationMaster" + - " --class " + args.userClass + - " --jar " + args.userJar + - userArgsToString(args) + - " --worker-memory " + args.workerMemory + - " --worker-cores " + args.workerCores + - " --num-workers " + args.numWorkers + - " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" + - " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") - logInfo("Command for the ApplicationMaster: " + commands(0)) - amContainer.setCommands(commands) - - val capability = Records.newRecord(classOf[Resource]).asInstanceOf[Resource] - // Memory for the ApplicationMaster - capability.setMemory(args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD) - amContainer.setResource(capability) - - // Setup security tokens - val dob = new DataOutputBuffer() - credentials.writeTokenStorageToStream(dob) - amContainer.setContainerTokens(ByteBuffer.wrap(dob.getData())) - - return amContainer - } - - def submitApp(appContext: ApplicationSubmissionContext) = { - // Submit the application to the applications manager - logInfo("Submitting application to ASM") - super.submitApplication(appContext) - } - - def monitorApplication(appId: ApplicationId): Boolean = { - while(true) { - Thread.sleep(1000) - val report = super.getApplicationReport(appId) - - logInfo("Application report from ASM: \n" + - "\t application identifier: " + appId.toString() + "\n" + - "\t appId: " + appId.getId() + "\n" + - "\t clientToken: " + report.getClientToken() + "\n" + - "\t appDiagnostics: " + report.getDiagnostics() + "\n" + - "\t appMasterHost: " + report.getHost() + "\n" + - "\t appQueue: " + report.getQueue() + "\n" + - "\t appMasterRpcPort: " + report.getRpcPort() + "\n" + - "\t appStartTime: " + report.getStartTime() + "\n" + - "\t yarnAppState: " + report.getYarnApplicationState() + "\n" + - "\t distributedFinalState: " + report.getFinalApplicationStatus() + "\n" + - "\t appTrackingUrl: " + report.getTrackingUrl() + "\n" + - "\t appUser: " + report.getUser() - ) - - val state = report.getYarnApplicationState() - val dsStatus = report.getFinalApplicationStatus() - if (state == YarnApplicationState.FINISHED || - state == YarnApplicationState.FAILED || - state == YarnApplicationState.KILLED) { - return true - } - } - return true - } -} - -object Client { - def main(argStrings: Array[String]) { - val args = new ClientArguments(argStrings) - SparkHadoopUtil.setYarnMode() - new Client(args).run - } - - // Based on code from org.apache.hadoop.mapreduce.v2.util.MRApps - def populateHadoopClasspath(conf: Configuration, env: HashMap[String, String]) { - for (c <- conf.getStrings(YarnConfiguration.YARN_APPLICATION_CLASSPATH)) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, c.trim) - } - } -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala deleted file mode 100644 index 07e7edea36..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala +++ /dev/null @@ -1,99 +0,0 @@ -package spark.deploy.yarn - -import spark.util.MemoryParam -import spark.util.IntParam -import collection.mutable.{ArrayBuffer, HashMap} -import spark.scheduler.{InputFormatInfo, SplitInfo} - -// TODO: Add code and support for ensuring that yarn resource 'asks' are location aware ! -class ClientArguments(val args: Array[String]) { - var userJar: String = null - var userClass: String = null - var userArgs: Seq[String] = Seq[String]() - var workerMemory = 1024 - var workerCores = 1 - var numWorkers = 2 - var amQueue = System.getProperty("QUEUE", "default") - var amMemory: Int = 512 - // TODO - var inputFormatInfo: List[InputFormatInfo] = null - - parseArgs(args.toList) - - private def parseArgs(inputArgs: List[String]): Unit = { - val userArgsBuffer: ArrayBuffer[String] = new ArrayBuffer[String]() - val inputFormatMap: HashMap[String, InputFormatInfo] = new HashMap[String, InputFormatInfo]() - - var args = inputArgs - - while (! args.isEmpty) { - - args match { - case ("--jar") :: value :: tail => - userJar = value - args = tail - - case ("--class") :: value :: tail => - userClass = value - args = tail - - case ("--args") :: value :: tail => - userArgsBuffer += value - args = tail - - case ("--master-memory") :: MemoryParam(value) :: tail => - amMemory = value - args = tail - - case ("--num-workers") :: IntParam(value) :: tail => - numWorkers = value - args = tail - - case ("--worker-memory") :: MemoryParam(value) :: tail => - workerMemory = value - args = tail - - case ("--worker-cores") :: IntParam(value) :: tail => - workerCores = value - args = tail - - case ("--queue") :: value :: tail => - amQueue = value - args = tail - - case Nil => - if (userJar == null || userClass == null) { - printUsageAndExit(1) - } - - case _ => - printUsageAndExit(1, args) - } - } - - userArgs = userArgsBuffer.readOnly - inputFormatInfo = inputFormatMap.values.toList - } - - - def printUsageAndExit(exitCode: Int, unknownParam: Any = null) { - if (unknownParam != null) { - System.err.println("Unknown/unsupported param " + unknownParam) - } - System.err.println( - "Usage: spark.deploy.yarn.Client [options] \n" + - "Options:\n" + - " --jar JAR_PATH Path to your application's JAR file (required)\n" + - " --class CLASS_NAME Name of your application's main class (required)\n" + - " --args ARGS Arguments to be passed to your application's main class.\n" + - " Mutliple invocations are possible, each will be passed in order.\n" + - " --num-workers NUM Number of workers to start (Default: 2)\n" + - " --worker-cores NUM Number of cores for the workers (Default: 1). This is unsused right now.\n" + - " --master-memory MEM Memory for Master (e.g. 1000M, 2G) (Default: 512 Mb)\n" + - " --worker-memory MEM Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n" + - " --queue QUEUE The hadoop queue to use for allocation requests (Default: 'default')" - ) - System.exit(exitCode) - } - -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala deleted file mode 100644 index cc6f3344a1..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala +++ /dev/null @@ -1,200 +0,0 @@ -package spark.deploy.yarn - -import java.net.URI -import java.nio.ByteBuffer -import java.security.PrivilegedExceptionAction - -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} -import org.apache.hadoop.io.DataOutputBuffer -import org.apache.hadoop.net.NetUtils -import org.apache.hadoop.security.UserGroupInformation -import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.api.protocolrecords._ -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.yarn.ipc.YarnRPC -import org.apache.hadoop.yarn.util.{Apps, ConverterUtils, Records, ProtoUtils} -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment - -import scala.collection.JavaConversions._ -import scala.collection.mutable.HashMap - -import spark.{Logging, Utils} - -class WorkerRunnable(container: Container, conf: Configuration, masterAddress: String, - slaveId: String, hostname: String, workerMemory: Int, workerCores: Int) - extends Runnable with Logging { - - var rpc: YarnRPC = YarnRPC.create(conf) - var cm: ContainerManager = null - val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - - def run = { - logInfo("Starting Worker Container") - cm = connectToCM - startContainer - } - - def startContainer = { - logInfo("Setting up ContainerLaunchContext") - - val ctx = Records.newRecord(classOf[ContainerLaunchContext]) - .asInstanceOf[ContainerLaunchContext] - - ctx.setContainerId(container.getId()) - ctx.setResource(container.getResource()) - val localResources = prepareLocalResources - ctx.setLocalResources(localResources) - - val env = prepareEnvironment - ctx.setEnvironment(env) - - // Extra options for the JVM - var JAVA_OPTS = "" - // Set the JVM memory - val workerMemoryString = workerMemory + "m" - JAVA_OPTS += "-Xms" + workerMemoryString + " -Xmx" + workerMemoryString + " " - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " - } - // Commenting it out for now - so that people can refer to the properties if required. Remove it once cpuset version is pushed out. - // The context is, default gc for server class machines end up using all cores to do gc - hence if there are multiple containers in same - // node, spark gc effects all other containers performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in multi-tenant environments. Not sure how default java gc behaves if it is - // limited to subset of cores on a node. -/* - else { - // If no java_opts specified, default to using -XX:+CMSIncrementalMode - // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont want to mess with it. - // In our expts, using (default) throughput collector has severe perf ramnifications in multi-tennent machines - // The options are based on - // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } -*/ - - ctx.setUser(UserGroupInformation.getCurrentUser().getShortUserName()) - - val credentials = UserGroupInformation.getCurrentUser().getCredentials() - val dob = new DataOutputBuffer() - credentials.writeTokenStorageToStream(dob) - ctx.setContainerTokens(ByteBuffer.wrap(dob.getData())) - - var javaCommand = "java"; - val javaHome = System.getenv("JAVA_HOME") - if (javaHome != null && !javaHome.isEmpty()) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String](javaCommand + - " -server " + - // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. - // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in an inconsistent state. - // TODO: If the OOM is not recoverable by rescheduling it on different node, then do 'something' to fail job ... akin to blacklisting trackers in mapred ? - " -XX:OnOutOfMemoryError='kill %p' " + - JAVA_OPTS + - " spark.executor.StandaloneExecutorBackend " + - masterAddress + " " + - slaveId + " " + - hostname + " " + - workerCores + - " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" + - " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") - logInfo("Setting up worker with commands: " + commands) - ctx.setCommands(commands) - - // Send the start request to the ContainerManager - val startReq = Records.newRecord(classOf[StartContainerRequest]) - .asInstanceOf[StartContainerRequest] - startReq.setContainerLaunchContext(ctx) - cm.startContainer(startReq) - } - - - def prepareLocalResources: HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - val locaResources = HashMap[String, LocalResource]() - - // Spark JAR - val sparkJarResource = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - sparkJarResource.setType(LocalResourceType.FILE) - sparkJarResource.setVisibility(LocalResourceVisibility.APPLICATION) - sparkJarResource.setResource(ConverterUtils.getYarnUrlFromURI( - new URI(System.getenv("SPARK_YARN_JAR_PATH")))) - sparkJarResource.setTimestamp(System.getenv("SPARK_YARN_JAR_TIMESTAMP").toLong) - sparkJarResource.setSize(System.getenv("SPARK_YARN_JAR_SIZE").toLong) - locaResources("spark.jar") = sparkJarResource - // User JAR - val userJarResource = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - userJarResource.setType(LocalResourceType.FILE) - userJarResource.setVisibility(LocalResourceVisibility.APPLICATION) - userJarResource.setResource(ConverterUtils.getYarnUrlFromURI( - new URI(System.getenv("SPARK_YARN_USERJAR_PATH")))) - userJarResource.setTimestamp(System.getenv("SPARK_YARN_USERJAR_TIMESTAMP").toLong) - userJarResource.setSize(System.getenv("SPARK_YARN_USERJAR_SIZE").toLong) - locaResources("app.jar") = userJarResource - - // Log4j conf - if available - if (System.getenv("SPARK_YARN_LOG4J_PATH") != null) { - val log4jConfResource = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - log4jConfResource.setType(LocalResourceType.FILE) - log4jConfResource.setVisibility(LocalResourceVisibility.APPLICATION) - log4jConfResource.setResource(ConverterUtils.getYarnUrlFromURI( - new URI(System.getenv("SPARK_YARN_LOG4J_PATH")))) - log4jConfResource.setTimestamp(System.getenv("SPARK_YARN_LOG4J_TIMESTAMP").toLong) - log4jConfResource.setSize(System.getenv("SPARK_YARN_LOG4J_SIZE").toLong) - locaResources("log4j.properties") = log4jConfResource - } - - - logInfo("Prepared Local resources " + locaResources) - return locaResources - } - - def prepareEnvironment: HashMap[String, String] = { - val env = new HashMap[String, String]() - - // If log4j present, ensure ours overrides all others - if (System.getenv("SPARK_YARN_LOG4J_PATH") != null) { - // Which is correct ? - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./log4j.properties") - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./") - } - - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./*") - Apps.addToEnvironment(env, Environment.CLASSPATH.name, "$CLASSPATH") - Client.populateHadoopClasspath(yarnConf, env) - - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - return env - } - - def connectToCM: ContainerManager = { - val cmHostPortStr = container.getNodeId().getHost() + ":" + container.getNodeId().getPort() - val cmAddress = NetUtils.createSocketAddr(cmHostPortStr) - logInfo("Connecting to ContainerManager at " + cmHostPortStr) - - // use doAs and remoteUser here so we can add the container token and not - // pollute the current users credentials with all of the individual container tokens - val user = UserGroupInformation.createRemoteUser(container.getId().toString()); - val containerToken = container.getContainerToken(); - if (containerToken != null) { - user.addToken(ProtoUtils.convertFromProtoFormat(containerToken, cmAddress)) - } - - val proxy = user - .doAs(new PrivilegedExceptionAction[ContainerManager] { - def run: ContainerManager = { - return rpc.getProxy(classOf[ContainerManager], - cmAddress, conf).asInstanceOf[ContainerManager] - } - }); - return proxy; - } - -} diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/YarnAllocationHandler.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/YarnAllocationHandler.scala deleted file mode 100644 index 61dd72a651..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/YarnAllocationHandler.scala +++ /dev/null @@ -1,547 +0,0 @@ -package spark.deploy.yarn - -import spark.{Logging, Utils} -import spark.scheduler.SplitInfo -import scala.collection -import org.apache.hadoop.yarn.api.records.{AMResponse, ApplicationAttemptId, ContainerId, Priority, Resource, ResourceRequest, ContainerStatus, Container} -import spark.scheduler.cluster.{ClusterScheduler, StandaloneSchedulerBackend} -import org.apache.hadoop.yarn.api.protocolrecords.{AllocateRequest, AllocateResponse} -import org.apache.hadoop.yarn.util.{RackResolver, Records} -import java.util.concurrent.{CopyOnWriteArrayList, ConcurrentHashMap} -import java.util.concurrent.atomic.AtomicInteger -import org.apache.hadoop.yarn.api.AMRMProtocol -import collection.JavaConversions._ -import collection.mutable.{ArrayBuffer, HashMap, HashSet} -import org.apache.hadoop.conf.Configuration -import java.util.{Collections, Set => JSet} -import java.lang.{Boolean => JBoolean} - -object AllocationType extends Enumeration ("HOST", "RACK", "ANY") { - type AllocationType = Value - val HOST, RACK, ANY = Value -} - -// too many params ? refactor it 'somehow' ? -// needs to be mt-safe -// Need to refactor this to make it 'cleaner' ... right now, all computation is reactive : should make it -// more proactive and decoupled. -// Note that right now, we assume all node asks as uniform in terms of capabilities and priority -// Refer to http://developer.yahoo.com/blogs/hadoop/posts/2011/03/mapreduce-nextgen-scheduler/ for more info -// on how we are requesting for containers. -private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceManager: AMRMProtocol, - val appAttemptId: ApplicationAttemptId, - val maxWorkers: Int, val workerMemory: Int, val workerCores: Int, - val preferredHostToCount: Map[String, Int], - val preferredRackToCount: Map[String, Int]) - extends Logging { - - - // These three are locked on allocatedHostToContainersMap. Complementary data structures - // allocatedHostToContainersMap : containers which are running : host, Set<containerid> - // allocatedContainerToHostMap: container to host mapping - private val allocatedHostToContainersMap = new HashMap[String, collection.mutable.Set[ContainerId]]() - private val allocatedContainerToHostMap = new HashMap[ContainerId, String]() - // allocatedRackCount is populated ONLY if allocation happens (or decremented if this is an allocated node) - // As with the two data structures above, tightly coupled with them, and to be locked on allocatedHostToContainersMap - private val allocatedRackCount = new HashMap[String, Int]() - - // containers which have been released. - private val releasedContainerList = new CopyOnWriteArrayList[ContainerId]() - // containers to be released in next request to RM - private val pendingReleaseContainers = new ConcurrentHashMap[ContainerId, Boolean] - - private val numWorkersRunning = new AtomicInteger() - // Used to generate a unique id per worker - private val workerIdCounter = new AtomicInteger() - private val lastResponseId = new AtomicInteger() - - def getNumWorkersRunning: Int = numWorkersRunning.intValue - - - def isResourceConstraintSatisfied(container: Container): Boolean = { - container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD) - } - - def allocateContainers(workersToRequest: Int) { - // We need to send the request only once from what I understand ... but for now, not modifying this much. - - // Keep polling the Resource Manager for containers - val amResp = allocateWorkerResources(workersToRequest).getAMResponse - - val _allocatedContainers = amResp.getAllocatedContainers() - if (_allocatedContainers.size > 0) { - - - logDebug("Allocated " + _allocatedContainers.size + " containers, current count " + - numWorkersRunning.get() + ", to-be-released " + releasedContainerList + - ", pendingReleaseContainers : " + pendingReleaseContainers) - logDebug("Cluster Resources: " + amResp.getAvailableResources) - - val hostToContainers = new HashMap[String, ArrayBuffer[Container]]() - - // ignore if not satisfying constraints { - for (container <- _allocatedContainers) { - if (isResourceConstraintSatisfied(container)) { - // allocatedContainers += container - - val host = container.getNodeId.getHost - val containers = hostToContainers.getOrElseUpdate(host, new ArrayBuffer[Container]()) - - containers += container - } - // Add all ignored containers to released list - else releasedContainerList.add(container.getId()) - } - - // Find the appropriate containers to use - // Slightly non trivial groupBy I guess ... - val dataLocalContainers = new HashMap[String, ArrayBuffer[Container]]() - val rackLocalContainers = new HashMap[String, ArrayBuffer[Container]]() - val offRackContainers = new HashMap[String, ArrayBuffer[Container]]() - - for (candidateHost <- hostToContainers.keySet) - { - val maxExpectedHostCount = preferredHostToCount.getOrElse(candidateHost, 0) - val requiredHostCount = maxExpectedHostCount - allocatedContainersOnHost(candidateHost) - - var remainingContainers = hostToContainers.get(candidateHost).getOrElse(null) - assert(remainingContainers != null) - - if (requiredHostCount >= remainingContainers.size){ - // Since we got <= required containers, add all to dataLocalContainers - dataLocalContainers.put(candidateHost, remainingContainers) - // all consumed - remainingContainers = null - } - else if (requiredHostCount > 0) { - // container list has more containers than we need for data locality. - // Split into two : data local container count of (remainingContainers.size - requiredHostCount) - // and rest as remainingContainer - val (dataLocal, remaining) = remainingContainers.splitAt(remainingContainers.size - requiredHostCount) - dataLocalContainers.put(candidateHost, dataLocal) - // remainingContainers = remaining - - // yarn has nasty habit of allocating a tonne of containers on a host - discourage this : - // add remaining to release list. If we have insufficient containers, next allocation cycle - // will reallocate (but wont treat it as data local) - for (container <- remaining) releasedContainerList.add(container.getId()) - remainingContainers = null - } - - // now rack local - if (remainingContainers != null){ - val rack = YarnAllocationHandler.lookupRack(conf, candidateHost) - - if (rack != null){ - val maxExpectedRackCount = preferredRackToCount.getOrElse(rack, 0) - val requiredRackCount = maxExpectedRackCount - allocatedContainersOnRack(rack) - - rackLocalContainers.get(rack).getOrElse(List()).size - - - if (requiredRackCount >= remainingContainers.size){ - // Add all to dataLocalContainers - dataLocalContainers.put(rack, remainingContainers) - // all consumed - remainingContainers = null - } - else if (requiredRackCount > 0) { - // container list has more containers than we need for data locality. - // Split into two : data local container count of (remainingContainers.size - requiredRackCount) - // and rest as remainingContainer - val (rackLocal, remaining) = remainingContainers.splitAt(remainingContainers.size - requiredRackCount) - val existingRackLocal = rackLocalContainers.getOrElseUpdate(rack, new ArrayBuffer[Container]()) - - existingRackLocal ++= rackLocal - remainingContainers = remaining - } - } - } - - // If still not consumed, then it is off rack host - add to that list. - if (remainingContainers != null){ - offRackContainers.put(candidateHost, remainingContainers) - } - } - - // Now that we have split the containers into various groups, go through them in order : - // first host local, then rack local and then off rack (everything else). - // Note that the list we create below tries to ensure that not all containers end up within a host - // if there are sufficiently large number of hosts/containers. - - val allocatedContainers = new ArrayBuffer[Container](_allocatedContainers.size) - allocatedContainers ++= ClusterScheduler.prioritizeContainers(dataLocalContainers) - allocatedContainers ++= ClusterScheduler.prioritizeContainers(rackLocalContainers) - allocatedContainers ++= ClusterScheduler.prioritizeContainers(offRackContainers) - - // Run each of the allocated containers - for (container <- allocatedContainers) { - val numWorkersRunningNow = numWorkersRunning.incrementAndGet() - val workerHostname = container.getNodeId.getHost - val containerId = container.getId - - assert (container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)) - - if (numWorkersRunningNow > maxWorkers) { - logInfo("Ignoring container " + containerId + " at host " + workerHostname + - " .. we already have required number of containers") - releasedContainerList.add(containerId) - // reset counter back to old value. - numWorkersRunning.decrementAndGet() - } - else { - // deallocate + allocate can result in reusing id's wrongly - so use a different counter (workerIdCounter) - val workerId = workerIdCounter.incrementAndGet().toString - val driverUrl = "akka://spark@%s:%s/user/%s".format( - System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"), - StandaloneSchedulerBackend.ACTOR_NAME) - - logInfo("launching container on " + containerId + " host " + workerHostname) - // just to be safe, simply remove it from pendingReleaseContainers. Should not be there, but .. - pendingReleaseContainers.remove(containerId) - - val rack = YarnAllocationHandler.lookupRack(conf, workerHostname) - allocatedHostToContainersMap.synchronized { - val containerSet = allocatedHostToContainersMap.getOrElseUpdate(workerHostname, new HashSet[ContainerId]()) - - containerSet += containerId - allocatedContainerToHostMap.put(containerId, workerHostname) - if (rack != null) allocatedRackCount.put(rack, allocatedRackCount.getOrElse(rack, 0) + 1) - } - - new Thread( - new WorkerRunnable(container, conf, driverUrl, workerId, - workerHostname, workerMemory, workerCores) - ).start() - } - } - logDebug("After allocated " + allocatedContainers.size + " containers (orig : " + - _allocatedContainers.size + "), current count " + numWorkersRunning.get() + - ", to-be-released " + releasedContainerList + ", pendingReleaseContainers : " + pendingReleaseContainers) - } - - - val completedContainers = amResp.getCompletedContainersStatuses() - if (completedContainers.size > 0){ - logDebug("Completed " + completedContainers.size + " containers, current count " + numWorkersRunning.get() + - ", to-be-released " + releasedContainerList + ", pendingReleaseContainers : " + pendingReleaseContainers) - - for (completedContainer <- completedContainers){ - val containerId = completedContainer.getContainerId - - // Was this released by us ? If yes, then simply remove from containerSet and move on. - if (pendingReleaseContainers.containsKey(containerId)) { - pendingReleaseContainers.remove(containerId) - } - else { - // simply decrement count - next iteration of ReporterThread will take care of allocating ! - numWorkersRunning.decrementAndGet() - logInfo("Container completed ? nodeId: " + containerId + ", state " + completedContainer.getState + - " httpaddress: " + completedContainer.getDiagnostics) - } - - allocatedHostToContainersMap.synchronized { - if (allocatedContainerToHostMap.containsKey(containerId)) { - val host = allocatedContainerToHostMap.get(containerId).getOrElse(null) - assert (host != null) - - val containerSet = allocatedHostToContainersMap.get(host).getOrElse(null) - assert (containerSet != null) - - containerSet -= containerId - if (containerSet.isEmpty) allocatedHostToContainersMap.remove(host) - else allocatedHostToContainersMap.update(host, containerSet) - - allocatedContainerToHostMap -= containerId - - // doing this within locked context, sigh ... move to outside ? - val rack = YarnAllocationHandler.lookupRack(conf, host) - if (rack != null) { - val rackCount = allocatedRackCount.getOrElse(rack, 0) - 1 - if (rackCount > 0) allocatedRackCount.put(rack, rackCount) - else allocatedRackCount.remove(rack) - } - } - } - } - logDebug("After completed " + completedContainers.size + " containers, current count " + - numWorkersRunning.get() + ", to-be-released " + releasedContainerList + - ", pendingReleaseContainers : " + pendingReleaseContainers) - } - } - - def createRackResourceRequests(hostContainers: List[ResourceRequest]): List[ResourceRequest] = { - // First generate modified racks and new set of hosts under it : then issue requests - val rackToCounts = new HashMap[String, Int]() - - // Within this lock - used to read/write to the rack related maps too. - for (container <- hostContainers) { - val candidateHost = container.getHostName - val candidateNumContainers = container.getNumContainers - assert(YarnAllocationHandler.ANY_HOST != candidateHost) - - val rack = YarnAllocationHandler.lookupRack(conf, candidateHost) - if (rack != null) { - var count = rackToCounts.getOrElse(rack, 0) - count += candidateNumContainers - rackToCounts.put(rack, count) - } - } - - val requestedContainers: ArrayBuffer[ResourceRequest] = - new ArrayBuffer[ResourceRequest](rackToCounts.size) - for ((rack, count) <- rackToCounts){ - requestedContainers += - createResourceRequest(AllocationType.RACK, rack, count, YarnAllocationHandler.PRIORITY) - } - - requestedContainers.toList - } - - def allocatedContainersOnHost(host: String): Int = { - var retval = 0 - allocatedHostToContainersMap.synchronized { - retval = allocatedHostToContainersMap.getOrElse(host, Set()).size - } - retval - } - - def allocatedContainersOnRack(rack: String): Int = { - var retval = 0 - allocatedHostToContainersMap.synchronized { - retval = allocatedRackCount.getOrElse(rack, 0) - } - retval - } - - private def allocateWorkerResources(numWorkers: Int): AllocateResponse = { - - var resourceRequests: List[ResourceRequest] = null - - // default. - if (numWorkers <= 0 || preferredHostToCount.isEmpty) { - logDebug("numWorkers: " + numWorkers + ", host preferences ? " + preferredHostToCount.isEmpty) - resourceRequests = List( - createResourceRequest(AllocationType.ANY, null, numWorkers, YarnAllocationHandler.PRIORITY)) - } - else { - // request for all hosts in preferred nodes and for numWorkers - - // candidates.size, request by default allocation policy. - val hostContainerRequests: ArrayBuffer[ResourceRequest] = - new ArrayBuffer[ResourceRequest](preferredHostToCount.size) - for ((candidateHost, candidateCount) <- preferredHostToCount) { - val requiredCount = candidateCount - allocatedContainersOnHost(candidateHost) - - if (requiredCount > 0) { - hostContainerRequests += - createResourceRequest(AllocationType.HOST, candidateHost, requiredCount, YarnAllocationHandler.PRIORITY) - } - } - val rackContainerRequests: List[ResourceRequest] = createRackResourceRequests(hostContainerRequests.toList) - - val anyContainerRequests: ResourceRequest = - createResourceRequest(AllocationType.ANY, null, numWorkers, YarnAllocationHandler.PRIORITY) - - val containerRequests: ArrayBuffer[ResourceRequest] = - new ArrayBuffer[ResourceRequest](hostContainerRequests.size() + rackContainerRequests.size() + 1) - - containerRequests ++= hostContainerRequests - containerRequests ++= rackContainerRequests - containerRequests += anyContainerRequests - - resourceRequests = containerRequests.toList - } - - val req = Records.newRecord(classOf[AllocateRequest]) - req.setResponseId(lastResponseId.incrementAndGet) - req.setApplicationAttemptId(appAttemptId) - - req.addAllAsks(resourceRequests) - - val releasedContainerList = createReleasedContainerList() - req.addAllReleases(releasedContainerList) - - - - if (numWorkers > 0) { - logInfo("Allocating " + numWorkers + " worker containers with " + (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD) + " of memory each.") - } - else { - logDebug("Empty allocation req .. release : " + releasedContainerList) - } - - for (req <- resourceRequests) { - logInfo("rsrcRequest ... host : " + req.getHostName + ", numContainers : " + req.getNumContainers + - ", p = " + req.getPriority().getPriority + ", capability: " + req.getCapability) - } - resourceManager.allocate(req) - } - - - private def createResourceRequest(requestType: AllocationType.AllocationType, - resource:String, numWorkers: Int, priority: Int): ResourceRequest = { - - // If hostname specified, we need atleast two requests - node local and rack local. - // There must be a third request - which is ANY : that will be specially handled. - requestType match { - case AllocationType.HOST => { - assert (YarnAllocationHandler.ANY_HOST != resource) - - val hostname = resource - val nodeLocal = createResourceRequestImpl(hostname, numWorkers, priority) - - // add to host->rack mapping - YarnAllocationHandler.populateRackInfo(conf, hostname) - - nodeLocal - } - - case AllocationType.RACK => { - val rack = resource - createResourceRequestImpl(rack, numWorkers, priority) - } - - case AllocationType.ANY => { - createResourceRequestImpl(YarnAllocationHandler.ANY_HOST, numWorkers, priority) - } - - case _ => throw new IllegalArgumentException("Unexpected/unsupported request type .. " + requestType) - } - } - - private def createResourceRequestImpl(hostname:String, numWorkers: Int, priority: Int): ResourceRequest = { - - val rsrcRequest = Records.newRecord(classOf[ResourceRequest]) - val memCapability = Records.newRecord(classOf[Resource]) - // There probably is some overhead here, let's reserve a bit more memory. - memCapability.setMemory(workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD) - rsrcRequest.setCapability(memCapability) - - val pri = Records.newRecord(classOf[Priority]) - pri.setPriority(priority) - rsrcRequest.setPriority(pri) - - rsrcRequest.setHostName(hostname) - - rsrcRequest.setNumContainers(java.lang.Math.max(numWorkers, 0)) - rsrcRequest - } - - def createReleasedContainerList(): ArrayBuffer[ContainerId] = { - - val retval = new ArrayBuffer[ContainerId](1) - // iterator on COW list ... - for (container <- releasedContainerList.iterator()){ - retval += container - } - // remove from the original list. - if (! retval.isEmpty) { - releasedContainerList.removeAll(retval) - for (v <- retval) pendingReleaseContainers.put(v, true) - logInfo("Releasing " + retval.size + " containers. pendingReleaseContainers : " + - pendingReleaseContainers) - } - - retval - } -} - -object YarnAllocationHandler { - - val ANY_HOST = "*" - // all requests are issued with same priority : we do not (yet) have any distinction between - // request types (like map/reduce in hadoop for example) - val PRIORITY = 1 - - // Additional memory overhead - in mb - val MEMORY_OVERHEAD = 384 - - // host to rack map - saved from allocation requests - // We are expecting this not to change. - // Note that it is possible for this to change : and RM will indicate that to us via update - // response to allocate. But we are punting on handling that for now. - private val hostToRack = new ConcurrentHashMap[String, String]() - private val rackToHostSet = new ConcurrentHashMap[String, JSet[String]]() - - def newAllocator(conf: Configuration, - resourceManager: AMRMProtocol, appAttemptId: ApplicationAttemptId, - args: ApplicationMasterArguments, - map: collection.Map[String, collection.Set[SplitInfo]]): YarnAllocationHandler = { - - val (hostToCount, rackToCount) = generateNodeToWeight(conf, map) - - - new YarnAllocationHandler(conf, resourceManager, appAttemptId, args.numWorkers, - args.workerMemory, args.workerCores, hostToCount, rackToCount) - } - - def newAllocator(conf: Configuration, - resourceManager: AMRMProtocol, appAttemptId: ApplicationAttemptId, - maxWorkers: Int, workerMemory: Int, workerCores: Int, - map: collection.Map[String, collection.Set[SplitInfo]]): YarnAllocationHandler = { - - val (hostToCount, rackToCount) = generateNodeToWeight(conf, map) - - new YarnAllocationHandler(conf, resourceManager, appAttemptId, maxWorkers, - workerMemory, workerCores, hostToCount, rackToCount) - } - - // A simple method to copy the split info map. - private def generateNodeToWeight(conf: Configuration, input: collection.Map[String, collection.Set[SplitInfo]]) : - // host to count, rack to count - (Map[String, Int], Map[String, Int]) = { - - if (input == null) return (Map[String, Int](), Map[String, Int]()) - - val hostToCount = new HashMap[String, Int] - val rackToCount = new HashMap[String, Int] - - for ((host, splits) <- input) { - val hostCount = hostToCount.getOrElse(host, 0) - hostToCount.put(host, hostCount + splits.size) - - val rack = lookupRack(conf, host) - if (rack != null){ - val rackCount = rackToCount.getOrElse(host, 0) - rackToCount.put(host, rackCount + splits.size) - } - } - - (hostToCount.toMap, rackToCount.toMap) - } - - def lookupRack(conf: Configuration, host: String): String = { - if (! hostToRack.contains(host)) populateRackInfo(conf, host) - hostToRack.get(host) - } - - def fetchCachedHostsForRack(rack: String): Option[Set[String]] = { - val set = rackToHostSet.get(rack) - if (set == null) return None - - // No better way to get a Set[String] from JSet ? - val convertedSet: collection.mutable.Set[String] = set - Some(convertedSet.toSet) - } - - def populateRackInfo(conf: Configuration, hostname: String) { - Utils.checkHost(hostname) - - if (!hostToRack.containsKey(hostname)) { - // If there are repeated failures to resolve, all to an ignore list ? - val rackInfo = RackResolver.resolve(conf, hostname) - if (rackInfo != null && rackInfo.getNetworkLocation != null) { - val rack = rackInfo.getNetworkLocation - hostToRack.put(hostname, rack) - if (! rackToHostSet.containsKey(rack)) { - rackToHostSet.putIfAbsent(rack, Collections.newSetFromMap(new ConcurrentHashMap[String, JBoolean]())) - } - rackToHostSet.get(rack).add(hostname) - - // Since RackResolver caches, we are disabling this for now ... - } /* else { - // right ? Else we will keep calling rack resolver in case we cant resolve rack info ... - hostToRack.put(hostname, null) - } */ - } - } -} diff --git a/core/src/hadoop2-yarn/scala/spark/scheduler/cluster/YarnClusterScheduler.scala b/core/src/hadoop2-yarn/scala/spark/scheduler/cluster/YarnClusterScheduler.scala deleted file mode 100644 index ed732d36bf..0000000000 --- a/core/src/hadoop2-yarn/scala/spark/scheduler/cluster/YarnClusterScheduler.scala +++ /dev/null @@ -1,42 +0,0 @@ -package spark.scheduler.cluster - -import spark._ -import spark.deploy.yarn.{ApplicationMaster, YarnAllocationHandler} -import org.apache.hadoop.conf.Configuration - -/** - * - * This is a simple extension to ClusterScheduler - to ensure that appropriate initialization of ApplicationMaster, etc is done - */ -private[spark] class YarnClusterScheduler(sc: SparkContext, conf: Configuration) extends ClusterScheduler(sc) { - - def this(sc: SparkContext) = this(sc, new Configuration()) - - // Nothing else for now ... initialize application master : which needs sparkContext to determine how to allocate - // Note that only the first creation of SparkContext influences (and ideally, there must be only one SparkContext, right ?) - // Subsequent creations are ignored - since nodes are already allocated by then. - - - // By default, rack is unknown - override def getRackForHost(hostPort: String): Option[String] = { - val host = Utils.parseHostPort(hostPort)._1 - val retval = YarnAllocationHandler.lookupRack(conf, host) - if (retval != null) Some(retval) else None - } - - // By default, if rack is unknown, return nothing - override def getCachedHostsForRack(rack: String): Option[Set[String]] = { - if (rack == None || rack == null) return None - - YarnAllocationHandler.fetchCachedHostsForRack(rack) - } - - override def postStartHook() { - val sparkContextInitialized = ApplicationMaster.sparkContextInitialized(sc) - if (sparkContextInitialized){ - // Wait for a few seconds for the slaves to bootstrap and register with master - best case attempt - Thread.sleep(3000L) - } - logInfo("YarnClusterScheduler.postStartHook done") - } -} diff --git a/core/src/hadoop2/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala b/core/src/hadoop2/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala deleted file mode 100644 index a0652d7fc7..0000000000 --- a/core/src/hadoop2/scala/org/apache/hadoop/mapred/HadoopMapRedUtil.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.apache.hadoop.mapred - -trait HadoopMapRedUtil { - def newJobContext(conf: JobConf, jobId: JobID): JobContext = new JobContextImpl(conf, jobId) - - def newTaskAttemptContext(conf: JobConf, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContextImpl(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = new TaskAttemptID(jtIdentifier, - jobId, isMap, taskId, attemptId) -} diff --git a/core/src/hadoop2/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala b/core/src/hadoop2/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala deleted file mode 100644 index 7fdbe322fd..0000000000 --- a/core/src/hadoop2/scala/org/apache/hadoop/mapreduce/HadoopMapReduceUtil.scala +++ /dev/null @@ -1,13 +0,0 @@ -package org.apache.hadoop.mapreduce - -import org.apache.hadoop.conf.Configuration -import task.{TaskAttemptContextImpl, JobContextImpl} - -trait HadoopMapReduceUtil { - def newJobContext(conf: Configuration, jobId: JobID): JobContext = new JobContextImpl(conf, jobId) - - def newTaskAttemptContext(conf: Configuration, attemptId: TaskAttemptID): TaskAttemptContext = new TaskAttemptContextImpl(conf, attemptId) - - def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = new TaskAttemptID(jtIdentifier, - jobId, isMap, taskId, attemptId) -} diff --git a/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala deleted file mode 100644 index f1c86de4cc..0000000000 --- a/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala +++ /dev/null @@ -1,27 +0,0 @@ -package spark.deploy -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.mapred.JobConf - - -/** - * Contains util methods to interact with Hadoop from spark. - */ -object SparkHadoopUtil { - - def getUserNameFromEnvironment(): String = { - // defaulting to -D ... - System.getProperty("user.name") - } - - def runAsUser(func: (Product) => Unit, args: Product) { - - // Add support, if exists - for now, simply run func ! - func(args) - } - - // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems - def newConfiguration(): Configuration = new Configuration() - - // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster - def addCredentials(conf: JobConf) {} -} diff --git a/core/src/main/java/spark/network/netty/FileClient.java b/core/src/main/java/org/apache/spark/network/netty/FileClient.java index a4bb4bc701..20a7a3aa8c 100644 --- a/core/src/main/java/spark/network/netty/FileClient.java +++ b/core/src/main/java/org/apache/spark/network/netty/FileClient.java @@ -1,4 +1,21 @@ -package spark.network.netty; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; import io.netty.bootstrap.Bootstrap; import io.netty.channel.Channel; diff --git a/core/src/main/java/org/apache/spark/network/netty/FileClientChannelInitializer.java b/core/src/main/java/org/apache/spark/network/netty/FileClientChannelInitializer.java new file mode 100644 index 0000000000..65ee15d63b --- /dev/null +++ b/core/src/main/java/org/apache/spark/network/netty/FileClientChannelInitializer.java @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; + +import io.netty.buffer.BufType; +import io.netty.channel.ChannelInitializer; +import io.netty.channel.socket.SocketChannel; +import io.netty.handler.codec.string.StringEncoder; + + +class FileClientChannelInitializer extends ChannelInitializer<SocketChannel> { + + private FileClientHandler fhandler; + + public FileClientChannelInitializer(FileClientHandler handler) { + fhandler = handler; + } + + @Override + public void initChannel(SocketChannel channel) { + // file no more than 2G + channel.pipeline() + .addLast("encoder", new StringEncoder(BufType.BYTE)) + .addLast("handler", fhandler); + } +} diff --git a/core/src/main/java/spark/network/netty/FileClientHandler.java b/core/src/main/java/org/apache/spark/network/netty/FileClientHandler.java index 9fc9449827..c4aa2669e0 100644 --- a/core/src/main/java/spark/network/netty/FileClientHandler.java +++ b/core/src/main/java/org/apache/spark/network/netty/FileClientHandler.java @@ -1,4 +1,21 @@ -package spark.network.netty; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; import io.netty.buffer.ByteBuf; import io.netty.channel.ChannelHandlerContext; diff --git a/core/src/main/java/spark/network/netty/FileServer.java b/core/src/main/java/org/apache/spark/network/netty/FileServer.java index dd3a557ae5..666432474d 100644 --- a/core/src/main/java/spark/network/netty/FileServer.java +++ b/core/src/main/java/org/apache/spark/network/netty/FileServer.java @@ -1,4 +1,21 @@ -package spark.network.netty; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; import java.net.InetSocketAddress; diff --git a/core/src/main/java/org/apache/spark/network/netty/FileServerChannelInitializer.java b/core/src/main/java/org/apache/spark/network/netty/FileServerChannelInitializer.java new file mode 100644 index 0000000000..833af1632d --- /dev/null +++ b/core/src/main/java/org/apache/spark/network/netty/FileServerChannelInitializer.java @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; + +import io.netty.channel.ChannelInitializer; +import io.netty.channel.socket.SocketChannel; +import io.netty.handler.codec.DelimiterBasedFrameDecoder; +import io.netty.handler.codec.Delimiters; +import io.netty.handler.codec.string.StringDecoder; + + +class FileServerChannelInitializer extends ChannelInitializer<SocketChannel> { + + PathResolver pResolver; + + public FileServerChannelInitializer(PathResolver pResolver) { + this.pResolver = pResolver; + } + + @Override + public void initChannel(SocketChannel channel) { + channel.pipeline() + .addLast("framer", new DelimiterBasedFrameDecoder(8192, Delimiters.lineDelimiter())) + .addLast("strDecoder", new StringDecoder()) + .addLast("handler", new FileServerHandler(pResolver)); + } +} diff --git a/core/src/main/java/spark/network/netty/FileServerHandler.java b/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java index a78eddb1b5..d3d57a0255 100644 --- a/core/src/main/java/spark/network/netty/FileServerHandler.java +++ b/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java @@ -1,4 +1,21 @@ -package spark.network.netty; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty; import java.io.File; import java.io.FileInputStream; diff --git a/core/src/main/java/org/apache/spark/network/netty/PathResolver.java b/core/src/main/java/org/apache/spark/network/netty/PathResolver.java new file mode 100755 index 0000000000..94c034cad0 --- /dev/null +++ b/core/src/main/java/org/apache/spark/network/netty/PathResolver.java @@ -0,0 +1,29 @@ +/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.network.netty;
+
+
+public interface PathResolver {
+ /**
+ * Get the absolute path of the file
+ *
+ * @param fileId
+ * @return the absolute path of file
+ */
+ public String getAbsolutePath(String fileId);
+}
diff --git a/core/src/main/java/spark/network/netty/FileClientChannelInitializer.java b/core/src/main/java/spark/network/netty/FileClientChannelInitializer.java deleted file mode 100644 index af25baf641..0000000000 --- a/core/src/main/java/spark/network/netty/FileClientChannelInitializer.java +++ /dev/null @@ -1,24 +0,0 @@ -package spark.network.netty; - -import io.netty.buffer.BufType; -import io.netty.channel.ChannelInitializer; -import io.netty.channel.socket.SocketChannel; -import io.netty.handler.codec.string.StringEncoder; - - -class FileClientChannelInitializer extends ChannelInitializer<SocketChannel> { - - private FileClientHandler fhandler; - - public FileClientChannelInitializer(FileClientHandler handler) { - fhandler = handler; - } - - @Override - public void initChannel(SocketChannel channel) { - // file no more than 2G - channel.pipeline() - .addLast("encoder", new StringEncoder(BufType.BYTE)) - .addLast("handler", fhandler); - } -} diff --git a/core/src/main/java/spark/network/netty/FileServerChannelInitializer.java b/core/src/main/java/spark/network/netty/FileServerChannelInitializer.java deleted file mode 100644 index 8f1f5c65cd..0000000000 --- a/core/src/main/java/spark/network/netty/FileServerChannelInitializer.java +++ /dev/null @@ -1,25 +0,0 @@ -package spark.network.netty; - -import io.netty.channel.ChannelInitializer; -import io.netty.channel.socket.SocketChannel; -import io.netty.handler.codec.DelimiterBasedFrameDecoder; -import io.netty.handler.codec.Delimiters; -import io.netty.handler.codec.string.StringDecoder; - - -class FileServerChannelInitializer extends ChannelInitializer<SocketChannel> { - - PathResolver pResolver; - - public FileServerChannelInitializer(PathResolver pResolver) { - this.pResolver = pResolver; - } - - @Override - public void initChannel(SocketChannel channel) { - channel.pipeline() - .addLast("framer", new DelimiterBasedFrameDecoder(8192, Delimiters.lineDelimiter())) - .addLast("strDecoder", new StringDecoder()) - .addLast("handler", new FileServerHandler(pResolver)); - } -} diff --git a/core/src/main/java/spark/network/netty/PathResolver.java b/core/src/main/java/spark/network/netty/PathResolver.java deleted file mode 100755 index 302411672c..0000000000 --- a/core/src/main/java/spark/network/netty/PathResolver.java +++ /dev/null @@ -1,12 +0,0 @@ -package spark.network.netty;
-
-
-public interface PathResolver {
- /**
- * Get the absolute path of the file
- *
- * @param fileId
- * @return the absolute path of file
- */
- public String getAbsolutePath(String fileId);
-}
diff --git a/core/src/main/resources/org/apache/spark/ui/static/bootstrap.min.css b/core/src/main/resources/org/apache/spark/ui/static/bootstrap.min.css new file mode 100755 index 0000000000..13cef3d6f1 --- /dev/null +++ b/core/src/main/resources/org/apache/spark/ui/static/bootstrap.min.css @@ -0,0 +1,874 @@ +/*! + * Bootstrap v2.3.2 + * + * Copyright 2013 Twitter, Inc + * Licensed under the Apache License v2.0 + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Designed and built with all the love in the world @twitter by @mdo and @fat. + */ +.clearfix{*zoom:1;}.clearfix:before,.clearfix:after{display:table;content:"";line-height:0;} +.clearfix:after{clear:both;} +.hide-text{font:0/0 a;color:transparent;text-shadow:none;background-color:transparent;border:0;} +.input-block-level{display:block;width:100%;min-height:30px;-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box;} 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ul>li:first-child>a,.pagination-small ul>li:first-child>a,.pagination-mini ul>li:first-child>span,.pagination-small ul>li:first-child>span{-webkit-border-top-left-radius:3px;-moz-border-radius-topleft:3px;border-top-left-radius:3px;-webkit-border-bottom-left-radius:3px;-moz-border-radius-bottomleft:3px;border-bottom-left-radius:3px;} +.pagination-mini ul>li:last-child>a,.pagination-small ul>li:last-child>a,.pagination-mini ul>li:last-child>span,.pagination-small ul>li:last-child>span{-webkit-border-top-right-radius:3px;-moz-border-radius-topright:3px;border-top-right-radius:3px;-webkit-border-bottom-right-radius:3px;-moz-border-radius-bottomright:3px;border-bottom-right-radius:3px;} +.pagination-small ul>li>a,.pagination-small ul>li>span{padding:2px 10px;font-size:11.9px;} +.pagination-mini ul>li>a,.pagination-mini ul>li>span{padding:0 6px;font-size:10.5px;} +.pager{margin:20px 0;list-style:none;text-align:center;*zoom:1;}.pager:before,.pager:after{display:table;content:"";line-height:0;} +.pager:after{clear:both;} +.pager li{display:inline;} +.pager li>a,.pager li>span{display:inline-block;padding:5px 14px;background-color:#fff;border:1px solid #ddd;-webkit-border-radius:15px;-moz-border-radius:15px;border-radius:15px;} +.pager li>a:hover,.pager li>a:focus{text-decoration:none;background-color:#f5f5f5;} +.pager .next>a,.pager .next>span{float:right;} +.pager .previous>a,.pager .previous>span{float:left;} +.pager .disabled>a,.pager .disabled>a:hover,.pager .disabled>a:focus,.pager .disabled>span{color:#999999;background-color:#fff;cursor:default;} +.thumbnails{margin-left:-20px;list-style:none;*zoom:1;}.thumbnails:before,.thumbnails:after{display:table;content:"";line-height:0;} +.thumbnails:after{clear:both;} +.row-fluid .thumbnails{margin-left:0;} +.thumbnails>li{float:left;margin-bottom:20px;margin-left:20px;} +.thumbnail{display:block;padding:4px;line-height:20px;border:1px solid #ddd;-webkit-border-radius:4px;-moz-border-radius:4px;border-radius:4px;-webkit-box-shadow:0 1px 3px rgba(0, 0, 0, 0.055);-moz-box-shadow:0 1px 3px rgba(0, 0, 0, 0.055);box-shadow:0 1px 3px rgba(0, 0, 0, 0.055);-webkit-transition:all 0.2s ease-in-out;-moz-transition:all 0.2s ease-in-out;-o-transition:all 0.2s ease-in-out;transition:all 0.2s ease-in-out;} +a.thumbnail:hover,a.thumbnail:focus{border-color:#0088cc;-webkit-box-shadow:0 1px 4px rgba(0, 105, 214, 0.25);-moz-box-shadow:0 1px 4px rgba(0, 105, 214, 0.25);box-shadow:0 1px 4px rgba(0, 105, 214, 0.25);} +.thumbnail>img{display:block;max-width:100%;margin-left:auto;margin-right:auto;} +.thumbnail .caption{padding:9px;color:#555555;} +.alert{padding:8px 35px 8px 14px;margin-bottom:20px;text-shadow:0 1px 0 rgba(255, 255, 255, 0.5);background-color:#fcf8e3;border:1px solid #fbeed5;-webkit-border-radius:4px;-moz-border-radius:4px;border-radius:4px;} +.alert,.alert h4{color:#c09853;} +.alert h4{margin:0;} +.alert .close{position:relative;top:-2px;right:-21px;line-height:20px;} +.alert-success{background-color:#dff0d8;border-color:#d6e9c6;color:#468847;} +.alert-success h4{color:#468847;} +.alert-danger,.alert-error{background-color:#f2dede;border-color:#eed3d7;color:#b94a48;} +.alert-danger h4,.alert-error h4{color:#b94a48;} +.alert-info{background-color:#d9edf7;border-color:#bce8f1;color:#3a87ad;} +.alert-info h4{color:#3a87ad;} +.alert-block{padding-top:14px;padding-bottom:14px;} +.alert-block>p,.alert-block>ul{margin-bottom:0;} +.alert-block p+p{margin-top:5px;} +@-webkit-keyframes progress-bar-stripes{from{background-position:40px 0;} to{background-position:0 0;}}@-moz-keyframes progress-bar-stripes{from{background-position:40px 0;} to{background-position:0 0;}}@-ms-keyframes progress-bar-stripes{from{background-position:40px 0;} to{background-position:0 0;}}@-o-keyframes progress-bar-stripes{from{background-position:0 0;} to{background-position:40px 0;}}@keyframes progress-bar-stripes{from{background-position:40px 0;} to{background-position:0 0;}}.progress{overflow:hidden;height:20px;margin-bottom:20px;background-color:#f7f7f7;background-image:-moz-linear-gradient(top, #f5f5f5, #f9f9f9);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#f5f5f5), to(#f9f9f9));background-image:-webkit-linear-gradient(top, #f5f5f5, #f9f9f9);background-image:-o-linear-gradient(top, #f5f5f5, #f9f9f9);background-image:linear-gradient(to bottom, #f5f5f5, #f9f9f9);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#fff9f9f9', GradientType=0);-webkit-box-shadow:inset 0 1px 2px rgba(0, 0, 0, 0.1);-moz-box-shadow:inset 0 1px 2px rgba(0, 0, 0, 0.1);box-shadow:inset 0 1px 2px rgba(0, 0, 0, 0.1);-webkit-border-radius:4px;-moz-border-radius:4px;border-radius:4px;} +.progress .bar{width:0%;height:100%;color:#ffffff;float:left;font-size:12px;text-align:center;text-shadow:0 -1px 0 rgba(0, 0, 0, 0.25);background-color:#0e90d2;background-image:-moz-linear-gradient(top, #149bdf, #0480be);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#149bdf), to(#0480be));background-image:-webkit-linear-gradient(top, #149bdf, #0480be);background-image:-o-linear-gradient(top, #149bdf, #0480be);background-image:linear-gradient(to bottom, #149bdf, #0480be);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff149bdf', endColorstr='#ff0480be', GradientType=0);-webkit-box-shadow:inset 0 -1px 0 rgba(0, 0, 0, 0.15);-moz-box-shadow:inset 0 -1px 0 rgba(0, 0, 0, 0.15);box-shadow:inset 0 -1px 0 rgba(0, 0, 0, 0.15);-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box;-webkit-transition:width 0.6s ease;-moz-transition:width 0.6s ease;-o-transition:width 0.6s ease;transition:width 0.6s ease;} +.progress .bar+.bar{-webkit-box-shadow:inset 1px 0 0 rgba(0,0,0,.15), inset 0 -1px 0 rgba(0,0,0,.15);-moz-box-shadow:inset 1px 0 0 rgba(0,0,0,.15), inset 0 -1px 0 rgba(0,0,0,.15);box-shadow:inset 1px 0 0 rgba(0,0,0,.15), inset 0 -1px 0 rgba(0,0,0,.15);} +.progress-striped .bar{background-color:#149bdf;background-image:-webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));background-image:-webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);-webkit-background-size:40px 40px;-moz-background-size:40px 40px;-o-background-size:40px 40px;background-size:40px 40px;} +.progress.active .bar{-webkit-animation:progress-bar-stripes 2s linear infinite;-moz-animation:progress-bar-stripes 2s linear infinite;-ms-animation:progress-bar-stripes 2s linear infinite;-o-animation:progress-bar-stripes 2s linear infinite;animation:progress-bar-stripes 2s linear infinite;} +.progress-danger .bar,.progress .bar-danger{background-color:#dd514c;background-image:-moz-linear-gradient(top, #ee5f5b, #c43c35);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#ee5f5b), to(#c43c35));background-image:-webkit-linear-gradient(top, #ee5f5b, #c43c35);background-image:-o-linear-gradient(top, #ee5f5b, #c43c35);background-image:linear-gradient(to bottom, #ee5f5b, #c43c35);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffee5f5b', endColorstr='#ffc43c35', GradientType=0);} +.progress-danger.progress-striped .bar,.progress-striped .bar-danger{background-color:#ee5f5b;background-image:-webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));background-image:-webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);} +.progress-success .bar,.progress .bar-success{background-color:#5eb95e;background-image:-moz-linear-gradient(top, #62c462, #57a957);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#62c462), to(#57a957));background-image:-webkit-linear-gradient(top, #62c462, #57a957);background-image:-o-linear-gradient(top, #62c462, #57a957);background-image:linear-gradient(to bottom, #62c462, #57a957);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff62c462', endColorstr='#ff57a957', GradientType=0);} +.progress-success.progress-striped .bar,.progress-striped .bar-success{background-color:#62c462;background-image:-webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));background-image:-webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);} +.progress-info .bar,.progress .bar-info{background-color:#4bb1cf;background-image:-moz-linear-gradient(top, #5bc0de, #339bb9);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#5bc0de), to(#339bb9));background-image:-webkit-linear-gradient(top, #5bc0de, #339bb9);background-image:-o-linear-gradient(top, #5bc0de, #339bb9);background-image:linear-gradient(to bottom, #5bc0de, #339bb9);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff339bb9', GradientType=0);} +.progress-info.progress-striped .bar,.progress-striped .bar-info{background-color:#5bc0de;background-image:-webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));background-image:-webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);} +.progress-warning .bar,.progress .bar-warning{background-color:#faa732;background-image:-moz-linear-gradient(top, #fbb450, #f89406);background-image:-webkit-gradient(linear, 0 0, 0 100%, from(#fbb450), to(#f89406));background-image:-webkit-linear-gradient(top, #fbb450, #f89406);background-image:-o-linear-gradient(top, #fbb450, #f89406);background-image:linear-gradient(to bottom, #fbb450, #f89406);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffbb450', endColorstr='#fff89406', GradientType=0);} +.progress-warning.progress-striped .bar,.progress-striped .bar-warning{background-color:#fbb450;background-image:-webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));background-image:-webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);} +.hero-unit{padding:60px;margin-bottom:30px;font-size:18px;font-weight:200;line-height:30px;color:inherit;background-color:#eeeeee;-webkit-border-radius:6px;-moz-border-radius:6px;border-radius:6px;}.hero-unit h1{margin-bottom:0;font-size:60px;line-height:1;color:inherit;letter-spacing:-1px;} +.hero-unit li{line-height:30px;} +.media,.media-body{overflow:hidden;*overflow:visible;zoom:1;} +.media,.media .media{margin-top:15px;} +.media:first-child{margin-top:0;} +.media-object{display:block;} +.media-heading{margin:0 0 5px;} +.media>.pull-left{margin-right:10px;} +.media>.pull-right{margin-left:10px;} +.media-list{margin-left:0;list-style:none;} +.tooltip{position:absolute;z-index:1030;display:block;visibility:visible;font-size:11px;line-height:1.4;opacity:0;filter:alpha(opacity=0);}.tooltip.in{opacity:0.8;filter:alpha(opacity=80);} +.tooltip.top{margin-top:-3px;padding:5px 0;} +.tooltip.right{margin-left:3px;padding:0 5px;} +.tooltip.bottom{margin-top:3px;padding:5px 0;} +.tooltip.left{margin-left:-3px;padding:0 5px;} +.tooltip-inner{max-width:200px;padding:8px;color:#ffffff;text-align:center;text-decoration:none;background-color:#000000;-webkit-border-radius:4px;-moz-border-radius:4px;border-radius:4px;} +.tooltip-arrow{position:absolute;width:0;height:0;border-color:transparent;border-style:solid;} +.tooltip.top .tooltip-arrow{bottom:0;left:50%;margin-left:-5px;border-width:5px 5px 0;border-top-color:#000000;} +.tooltip.right .tooltip-arrow{top:50%;left:0;margin-top:-5px;border-width:5px 5px 5px 0;border-right-color:#000000;} +.tooltip.left .tooltip-arrow{top:50%;right:0;margin-top:-5px;border-width:5px 0 5px 5px;border-left-color:#000000;} +.tooltip.bottom .tooltip-arrow{top:0;left:50%;margin-left:-5px;border-width:0 5px 5px;border-bottom-color:#000000;} +.popover{position:absolute;top:0;left:0;z-index:1010;display:none;max-width:276px;padding:1px;text-align:left;background-color:#ffffff;-webkit-background-clip:padding-box;-moz-background-clip:padding;background-clip:padding-box;border:1px solid #ccc;border:1px solid rgba(0, 0, 0, 0.2);-webkit-border-radius:6px;-moz-border-radius:6px;border-radius:6px;-webkit-box-shadow:0 5px 10px rgba(0, 0, 0, 0.2);-moz-box-shadow:0 5px 10px rgba(0, 0, 0, 0.2);box-shadow:0 5px 10px rgba(0, 0, 0, 0.2);white-space:normal;}.popover.top{margin-top:-10px;} +.popover.right{margin-left:10px;} +.popover.bottom{margin-top:10px;} +.popover.left{margin-left:-10px;} +.popover-title{margin:0;padding:8px 14px;font-size:14px;font-weight:normal;line-height:18px;background-color:#f7f7f7;border-bottom:1px solid #ebebeb;-webkit-border-radius:5px 5px 0 0;-moz-border-radius:5px 5px 0 0;border-radius:5px 5px 0 0;}.popover-title:empty{display:none;} +.popover-content{padding:9px 14px;} +.popover .arrow,.popover .arrow:after{position:absolute;display:block;width:0;height:0;border-color:transparent;border-style:solid;} +.popover .arrow{border-width:11px;} +.popover .arrow:after{border-width:10px;content:"";} +.popover.top .arrow{left:50%;margin-left:-11px;border-bottom-width:0;border-top-color:#999;border-top-color:rgba(0, 0, 0, 0.25);bottom:-11px;}.popover.top .arrow:after{bottom:1px;margin-left:-10px;border-bottom-width:0;border-top-color:#ffffff;} +.popover.right .arrow{top:50%;left:-11px;margin-top:-11px;border-left-width:0;border-right-color:#999;border-right-color:rgba(0, 0, 0, 0.25);}.popover.right .arrow:after{left:1px;bottom:-10px;border-left-width:0;border-right-color:#ffffff;} +.popover.bottom .arrow{left:50%;margin-left:-11px;border-top-width:0;border-bottom-color:#999;border-bottom-color:rgba(0, 0, 0, 0.25);top:-11px;}.popover.bottom .arrow:after{top:1px;margin-left:-10px;border-top-width:0;border-bottom-color:#ffffff;} +.popover.left 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See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. 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- height: 50px; -} - -.navbar-inner .nav { - margin-top: 5px; - font-size: 15px; -} - - -#infolist { - margin-left: 400px; - margin-top: 14px; -} - -#infolist li { - display: inline; - list-style-type: none; - list-style-position: outside; - padding-right: 20px; - padding-top: 10px; - padding-bottom: 10px; -} - -.progress-cell { - width: 134px; - border-right: 0; - padding: 0; - padding-top: 7px; - padding-left: 4px; -} diff --git a/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala b/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala new file mode 100644 index 0000000000..f87460039b --- /dev/null +++ b/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.hadoop.mapred + +trait SparkHadoopMapRedUtil { + def newJobContext(conf: JobConf, jobId: JobID): JobContext = { + val klass = firstAvailableClass("org.apache.hadoop.mapred.JobContextImpl", "org.apache.hadoop.mapred.JobContext"); + val ctor = klass.getDeclaredConstructor(classOf[JobConf], classOf[org.apache.hadoop.mapreduce.JobID]) + ctor.newInstance(conf, jobId).asInstanceOf[JobContext] + } + + def newTaskAttemptContext(conf: JobConf, attemptId: TaskAttemptID): TaskAttemptContext = { + val klass = firstAvailableClass("org.apache.hadoop.mapred.TaskAttemptContextImpl", "org.apache.hadoop.mapred.TaskAttemptContext") + val ctor = klass.getDeclaredConstructor(classOf[JobConf], classOf[TaskAttemptID]) + ctor.newInstance(conf, attemptId).asInstanceOf[TaskAttemptContext] + } + + def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = { + new TaskAttemptID(jtIdentifier, jobId, isMap, taskId, attemptId) + } + + private def firstAvailableClass(first: String, second: String): Class[_] = { + try { + Class.forName(first) + } catch { + case e: ClassNotFoundException => + Class.forName(second) + } + } +} diff --git a/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala b/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala new file mode 100644 index 0000000000..93180307fa --- /dev/null +++ b/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala @@ -0,0 +1,69 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.hadoop.mapreduce + +import org.apache.hadoop.conf.Configuration +import java.lang.{Integer => JInteger, Boolean => JBoolean} + +trait SparkHadoopMapReduceUtil { + def newJobContext(conf: Configuration, jobId: JobID): JobContext = { + val klass = firstAvailableClass( + "org.apache.hadoop.mapreduce.task.JobContextImpl", // hadoop2, hadoop2-yarn + "org.apache.hadoop.mapreduce.JobContext") // hadoop1 + val ctor = klass.getDeclaredConstructor(classOf[Configuration], classOf[JobID]) + ctor.newInstance(conf, jobId).asInstanceOf[JobContext] + } + + def newTaskAttemptContext(conf: Configuration, attemptId: TaskAttemptID): TaskAttemptContext = { + val klass = firstAvailableClass( + "org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl", // hadoop2, hadoop2-yarn + "org.apache.hadoop.mapreduce.TaskAttemptContext") // hadoop1 + val ctor = klass.getDeclaredConstructor(classOf[Configuration], classOf[TaskAttemptID]) + ctor.newInstance(conf, attemptId).asInstanceOf[TaskAttemptContext] + } + + def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = { + val klass = Class.forName("org.apache.hadoop.mapreduce.TaskAttemptID"); + try { + // first, attempt to use the old-style constructor that takes a boolean isMap (not available in YARN) + val ctor = klass.getDeclaredConstructor(classOf[String], classOf[Int], classOf[Boolean], + classOf[Int], classOf[Int]) + ctor.newInstance(jtIdentifier, new JInteger(jobId), new JBoolean(isMap), new JInteger(taskId), new + JInteger(attemptId)).asInstanceOf[TaskAttemptID] + } catch { + case exc: NoSuchMethodException => { + // failed, look for the new ctor that takes a TaskType (not available in 1.x) + val taskTypeClass = Class.forName("org.apache.hadoop.mapreduce.TaskType").asInstanceOf[Class[Enum[_]]] + val taskType = taskTypeClass.getMethod("valueOf", classOf[String]).invoke(taskTypeClass, if(isMap) "MAP" else "REDUCE") + val ctor = klass.getDeclaredConstructor(classOf[String], classOf[Int], taskTypeClass, + classOf[Int], classOf[Int]) + ctor.newInstance(jtIdentifier, new JInteger(jobId), taskType, new JInteger(taskId), new + JInteger(attemptId)).asInstanceOf[TaskAttemptID] + } + } + } + + private def firstAvailableClass(first: String, second: String): Class[_] = { + try { + Class.forName(first) + } catch { + case e: ClassNotFoundException => + Class.forName(second) + } + } +} diff --git a/core/src/main/scala/spark/Accumulators.scala b/core/src/main/scala/org/apache/spark/Accumulators.scala index 57c6df35be..6e922a612a 100644 --- a/core/src/main/scala/spark/Accumulators.scala +++ b/core/src/main/scala/org/apache/spark/Accumulators.scala @@ -1,9 +1,27 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io._ import scala.collection.mutable.Map import scala.collection.generic.Growable +import org.apache.spark.serializer.JavaSerializer /** * A datatype that can be accumulated, i.e. has an commutative and associative "add" operation, @@ -11,7 +29,7 @@ import scala.collection.generic.Growable * * You must define how to add data, and how to merge two of these together. For some datatypes, * such as a counter, these might be the same operation. In that case, you can use the simpler - * [[spark.Accumulator]]. They won't always be the same, though -- e.g., imagine you are + * [[org.apache.spark.Accumulator]]. They won't always be the same, though -- e.g., imagine you are * accumulating a set. You will add items to the set, and you will union two sets together. * * @param initialValue initial value of accumulator @@ -159,7 +177,7 @@ class GrowableAccumulableParam[R <% Growable[T] with TraversableOnce[T] with Ser def zero(initialValue: R): R = { // We need to clone initialValue, but it's hard to specify that R should also be Cloneable. // Instead we'll serialize it to a buffer and load it back. - val ser = (new spark.JavaSerializer).newInstance() + val ser = new JavaSerializer().newInstance() val copy = ser.deserialize[R](ser.serialize(initialValue)) copy.clear() // In case it contained stuff copy @@ -167,7 +185,7 @@ class GrowableAccumulableParam[R <% Growable[T] with TraversableOnce[T] with Ser } /** - * A simpler value of [[spark.Accumulable]] where the result type being accumulated is the same + * A simpler value of [[org.apache.spark.Accumulable]] where the result type being accumulated is the same * as the types of elements being merged. * * @param initialValue initial value of accumulator @@ -178,7 +196,7 @@ class Accumulator[T](@transient initialValue: T, param: AccumulatorParam[T]) extends Accumulable[T,T](initialValue, param) /** - * A simpler version of [[spark.AccumulableParam]] where the only datatype you can add in is the same type + * A simpler version of [[org.apache.spark.AccumulableParam]] where the only datatype you can add in is the same type * as the accumulated value. An implicit AccumulatorParam object needs to be available when you create * Accumulators of a specific type. * diff --git a/core/src/main/scala/org/apache/spark/Aggregator.scala b/core/src/main/scala/org/apache/spark/Aggregator.scala new file mode 100644 index 0000000000..3ef402926e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/Aggregator.scala @@ -0,0 +1,61 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import java.util.{HashMap => JHashMap} + +import scala.collection.JavaConversions._ + +/** A set of functions used to aggregate data. + * + * @param createCombiner function to create the initial value of the aggregation. + * @param mergeValue function to merge a new value into the aggregation result. + * @param mergeCombiners function to merge outputs from multiple mergeValue function. + */ +case class Aggregator[K, V, C] ( + createCombiner: V => C, + mergeValue: (C, V) => C, + mergeCombiners: (C, C) => C) { + + def combineValuesByKey(iter: Iterator[_ <: Product2[K, V]]) : Iterator[(K, C)] = { + val combiners = new JHashMap[K, C] + for (kv <- iter) { + val oldC = combiners.get(kv._1) + if (oldC == null) { + combiners.put(kv._1, createCombiner(kv._2)) + } else { + combiners.put(kv._1, mergeValue(oldC, kv._2)) + } + } + combiners.iterator + } + + def combineCombinersByKey(iter: Iterator[(K, C)]) : Iterator[(K, C)] = { + val combiners = new JHashMap[K, C] + iter.foreach { case(k, c) => + val oldC = combiners.get(k) + if (oldC == null) { + combiners.put(k, c) + } else { + combiners.put(k, mergeCombiners(oldC, c)) + } + } + combiners.iterator + } +} + diff --git a/core/src/main/scala/spark/BlockStoreShuffleFetcher.scala b/core/src/main/scala/org/apache/spark/BlockStoreShuffleFetcher.scala index 3239f4c385..908ff56a6b 100644 --- a/core/src/main/scala/spark/BlockStoreShuffleFetcher.scala +++ b/core/src/main/scala/org/apache/spark/BlockStoreShuffleFetcher.scala @@ -1,18 +1,36 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashMap -import spark.executor.{ShuffleReadMetrics, TaskMetrics} -import spark.serializer.Serializer -import spark.storage.BlockManagerId -import spark.util.CompletionIterator +import org.apache.spark.executor.{ShuffleReadMetrics, TaskMetrics} +import org.apache.spark.serializer.Serializer +import org.apache.spark.storage.BlockManagerId +import org.apache.spark.util.CompletionIterator private[spark] class BlockStoreShuffleFetcher extends ShuffleFetcher with Logging { - override def fetch[K, V]( - shuffleId: Int, reduceId: Int, metrics: TaskMetrics, serializer: Serializer) = { + override def fetch[T](shuffleId: Int, reduceId: Int, metrics: TaskMetrics, serializer: Serializer) + : Iterator[T] = + { logDebug("Fetching outputs for shuffle %d, reduce %d".format(shuffleId, reduceId)) val blockManager = SparkEnv.get.blockManager @@ -32,12 +50,12 @@ private[spark] class BlockStoreShuffleFetcher extends ShuffleFetcher with Loggin (address, splits.map(s => ("shuffle_%d_%d_%d".format(shuffleId, s._1, reduceId), s._2))) } - def unpackBlock(blockPair: (String, Option[Iterator[Any]])) : Iterator[(K, V)] = { + def unpackBlock(blockPair: (String, Option[Iterator[Any]])) : Iterator[T] = { val blockId = blockPair._1 val blockOption = blockPair._2 blockOption match { case Some(block) => { - block.asInstanceOf[Iterator[(K, V)]] + block.asInstanceOf[Iterator[T]] } case None => { val regex = "shuffle_([0-9]*)_([0-9]*)_([0-9]*)".r @@ -56,7 +74,7 @@ private[spark] class BlockStoreShuffleFetcher extends ShuffleFetcher with Loggin val blockFetcherItr = blockManager.getMultiple(blocksByAddress, serializer) val itr = blockFetcherItr.flatMap(unpackBlock) - CompletionIterator[(K,V), Iterator[(K,V)]](itr, { + CompletionIterator[T, Iterator[T]](itr, { val shuffleMetrics = new ShuffleReadMetrics shuffleMetrics.shuffleFinishTime = System.currentTimeMillis shuffleMetrics.remoteFetchTime = blockFetcherItr.remoteFetchTime diff --git a/core/src/main/scala/spark/CacheManager.scala b/core/src/main/scala/org/apache/spark/CacheManager.scala index f7a2b7e802..e299a106ee 100644 --- a/core/src/main/scala/spark/CacheManager.scala +++ b/core/src/main/scala/org/apache/spark/CacheManager.scala @@ -1,7 +1,25 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import scala.collection.mutable.{ArrayBuffer, HashSet} -import spark.storage.{BlockManager, StorageLevel} +import org.apache.spark.storage.{BlockManager, StorageLevel} +import org.apache.spark.rdd.RDD /** Spark class responsible for passing RDDs split contents to the BlockManager and making diff --git a/core/src/main/scala/spark/Dependency.scala b/core/src/main/scala/org/apache/spark/Dependency.scala index 2af44aa383..cc30105940 100644 --- a/core/src/main/scala/spark/Dependency.scala +++ b/core/src/main/scala/org/apache/spark/Dependency.scala @@ -1,4 +1,23 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.apache.spark.rdd.RDD /** * Base class for dependencies. @@ -22,16 +41,15 @@ abstract class NarrowDependency[T](rdd: RDD[T]) extends Dependency(rdd) { /** * Represents a dependency on the output of a shuffle stage. - * @param shuffleId the shuffle id * @param rdd the parent RDD * @param partitioner partitioner used to partition the shuffle output * @param serializerClass class name of the serializer to use */ class ShuffleDependency[K, V]( - @transient rdd: RDD[(K, V)], + @transient rdd: RDD[_ <: Product2[K, V]], val partitioner: Partitioner, val serializerClass: String = null) - extends Dependency(rdd) { + extends Dependency(rdd.asInstanceOf[RDD[Product2[K, V]]]) { val shuffleId: Int = rdd.context.newShuffleId() } diff --git a/core/src/main/scala/org/apache/spark/FetchFailedException.scala b/core/src/main/scala/org/apache/spark/FetchFailedException.scala new file mode 100644 index 0000000000..d242047502 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/FetchFailedException.scala @@ -0,0 +1,44 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.apache.spark.storage.BlockManagerId + +private[spark] class FetchFailedException( + taskEndReason: TaskEndReason, + message: String, + cause: Throwable) + extends Exception { + + def this (bmAddress: BlockManagerId, shuffleId: Int, mapId: Int, reduceId: Int, cause: Throwable) = + this(FetchFailed(bmAddress, shuffleId, mapId, reduceId), + "Fetch failed: %s %d %d %d".format(bmAddress, shuffleId, mapId, reduceId), + cause) + + def this (shuffleId: Int, reduceId: Int, cause: Throwable) = + this(FetchFailed(null, shuffleId, -1, reduceId), + "Unable to fetch locations from master: %d %d".format(shuffleId, reduceId), cause) + + override def getMessage(): String = message + + + override def getCause(): Throwable = cause + + def toTaskEndReason: TaskEndReason = taskEndReason + +} diff --git a/core/src/main/scala/spark/HttpFileServer.scala b/core/src/main/scala/org/apache/spark/HttpFileServer.scala index 00901d95e2..ad1ee20045 100644 --- a/core/src/main/scala/spark/HttpFileServer.scala +++ b/core/src/main/scala/org/apache/spark/HttpFileServer.scala @@ -1,7 +1,25 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io.{File} import com.google.common.io.Files +import org.apache.spark.util.Utils private[spark] class HttpFileServer extends Logging { @@ -42,4 +60,4 @@ private[spark] class HttpFileServer extends Logging { return dir + "/" + file.getName } -}
\ No newline at end of file +} diff --git a/core/src/main/scala/spark/HttpServer.scala b/core/src/main/scala/org/apache/spark/HttpServer.scala index 4e0507c080..cdfc9dd54e 100644 --- a/core/src/main/scala/spark/HttpServer.scala +++ b/core/src/main/scala/org/apache/spark/HttpServer.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io.File import java.net.InetAddress @@ -9,6 +26,7 @@ import org.eclipse.jetty.server.handler.DefaultHandler import org.eclipse.jetty.server.handler.HandlerList import org.eclipse.jetty.server.handler.ResourceHandler import org.eclipse.jetty.util.thread.QueuedThreadPool +import org.apache.spark.util.Utils /** * Exception type thrown by HttpServer when it is in the wrong state for an operation. diff --git a/core/src/main/scala/spark/Logging.scala b/core/src/main/scala/org/apache/spark/Logging.scala index 0fc8c31463..6a973ea495 100644 --- a/core/src/main/scala/spark/Logging.scala +++ b/core/src/main/scala/org/apache/spark/Logging.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.slf4j.Logger import org.slf4j.LoggerFactory diff --git a/core/src/main/scala/spark/MapOutputTracker.scala b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala index 0fc6427307..1afb1870f1 100644 --- a/core/src/main/scala/spark/MapOutputTracker.scala +++ b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io._ import java.util.zip.{GZIPInputStream, GZIPOutputStream} @@ -15,9 +32,9 @@ import scala.concurrent.duration.Duration import akka.util.Timeout import scala.concurrent.duration._ -import spark.scheduler.MapStatus -import spark.storage.BlockManagerId -import spark.util.{MetadataCleaner, TimeStampedHashMap} +import org.apache.spark.scheduler.MapStatus +import org.apache.spark.storage.BlockManagerId +import org.apache.spark.util.{Utils, MetadataCleaner, TimeStampedHashMap} private[spark] sealed trait MapOutputTrackerMessage @@ -49,11 +66,11 @@ private[spark] class MapOutputTracker extends Logging { // Incremented every time a fetch fails so that client nodes know to clear // their cache of map output locations if this happens. - private var generation: Long = 0 - private val generationLock = new java.lang.Object + private var epoch: Long = 0 + private val epochLock = new java.lang.Object // Cache a serialized version of the output statuses for each shuffle to send them out faster - var cacheGeneration = generation + var cacheEpoch = epoch private val cachedSerializedStatuses = new TimeStampedHashMap[Int, Array[Byte]] val metadataCleaner = new MetadataCleaner("MapOutputTracker", this.cleanup) @@ -93,10 +110,10 @@ private[spark] class MapOutputTracker extends Logging { def registerMapOutputs( shuffleId: Int, statuses: Array[MapStatus], - changeGeneration: Boolean = false) { + changeEpoch: Boolean = false) { mapStatuses.put(shuffleId, Array[MapStatus]() ++ statuses) - if (changeGeneration) { - incrementGeneration() + if (changeEpoch) { + incrementEpoch() } } @@ -109,7 +126,7 @@ private[spark] class MapOutputTracker extends Logging { array(mapId) = null } } - incrementGeneration() + incrementEpoch() } else { throw new SparkException("unregisterMapOutput called for nonexistent shuffle ID") } @@ -191,58 +208,58 @@ private[spark] class MapOutputTracker extends Logging { trackerActor = null } - // Called on master to increment the generation number - def incrementGeneration() { - generationLock.synchronized { - generation += 1 - logDebug("Increasing generation to " + generation) + // Called on master to increment the epoch number + def incrementEpoch() { + epochLock.synchronized { + epoch += 1 + logDebug("Increasing epoch to " + epoch) } } - // Called on master or workers to get current generation number - def getGeneration: Long = { - generationLock.synchronized { - return generation + // Called on master or workers to get current epoch number + def getEpoch: Long = { + epochLock.synchronized { + return epoch } } - // Called on workers to update the generation number, potentially clearing old outputs - // because of a fetch failure. (Each Mesos task calls this with the latest generation + // Called on workers to update the epoch number, potentially clearing old outputs + // because of a fetch failure. (Each worker task calls this with the latest epoch // number on the master at the time it was created.) - def updateGeneration(newGen: Long) { - generationLock.synchronized { - if (newGen > generation) { - logInfo("Updating generation to " + newGen + " and clearing cache") + def updateEpoch(newEpoch: Long) { + epochLock.synchronized { + if (newEpoch > epoch) { + logInfo("Updating epoch to " + newEpoch + " and clearing cache") // mapStatuses = new TimeStampedHashMap[Int, Array[MapStatus]] mapStatuses.clear() - generation = newGen + epoch = newEpoch } } } def getSerializedLocations(shuffleId: Int): Array[Byte] = { var statuses: Array[MapStatus] = null - var generationGotten: Long = -1 - generationLock.synchronized { - if (generation > cacheGeneration) { + var epochGotten: Long = -1 + epochLock.synchronized { + if (epoch > cacheEpoch) { cachedSerializedStatuses.clear() - cacheGeneration = generation + cacheEpoch = epoch } cachedSerializedStatuses.get(shuffleId) match { case Some(bytes) => return bytes case None => statuses = mapStatuses(shuffleId) - generationGotten = generation + epochGotten = epoch } } // If we got here, we failed to find the serialized locations in the cache, so we pulled // out a snapshot of the locations as "locs"; let's serialize and return that val bytes = serializeStatuses(statuses) logInfo("Size of output statuses for shuffle %d is %d bytes".format(shuffleId, bytes.length)) - // Add them into the table only if the generation hasn't changed while we were working - generationLock.synchronized { - if (generation == generationGotten) { + // Add them into the table only if the epoch hasn't changed while we were working + epochLock.synchronized { + if (epoch == epochGotten) { cachedSerializedStatuses(shuffleId) = bytes } } diff --git a/core/src/main/scala/org/apache/spark/Partition.scala b/core/src/main/scala/org/apache/spark/Partition.scala new file mode 100644 index 0000000000..87914a061f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/Partition.scala @@ -0,0 +1,31 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +/** + * A partition of an RDD. + */ +trait Partition extends Serializable { + /** + * Get the split's index within its parent RDD + */ + def index: Int + + // A better default implementation of HashCode + override def hashCode(): Int = index +} diff --git a/core/src/main/scala/spark/Partitioner.scala b/core/src/main/scala/org/apache/spark/Partitioner.scala index fc811d85e1..62b608c088 100644 --- a/core/src/main/scala/spark/Partitioner.scala +++ b/core/src/main/scala/org/apache/spark/Partitioner.scala @@ -1,4 +1,24 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.apache.spark.util.Utils +import org.apache.spark.rdd.RDD import scala.reflect.ClassTag @@ -41,7 +61,7 @@ object Partitioner { } /** - * A [[spark.Partitioner]] that implements hash-based partitioning using Java's `Object.hashCode`. + * A [[org.apache.spark.Partitioner]] that implements hash-based partitioning using Java's `Object.hashCode`. * * Java arrays have hashCodes that are based on the arrays' identities rather than their contents, * so attempting to partition an RDD[Array[_]] or RDD[(Array[_], _)] using a HashPartitioner will @@ -50,17 +70,9 @@ object Partitioner { class HashPartitioner(partitions: Int) extends Partitioner { def numPartitions = partitions - def getPartition(key: Any): Int = { - if (key == null) { - return 0 - } else { - val mod = key.hashCode % partitions - if (mod < 0) { - mod + partitions - } else { - mod // Guard against negative hash codes - } - } + def getPartition(key: Any): Int = key match { + case null => 0 + case _ => Utils.nonNegativeMod(key.hashCode, numPartitions) } override def equals(other: Any): Boolean = other match { @@ -72,13 +84,13 @@ class HashPartitioner(partitions: Int) extends Partitioner { } /** - * A [[spark.Partitioner]] that partitions sortable records by range into roughly equal ranges. + * A [[org.apache.spark.Partitioner]] that partitions sortable records by range into roughly equal ranges. * Determines the ranges by sampling the RDD passed in. */ class RangePartitioner[K <% Ordered[K]: ClassTag, V]( partitions: Int, - @transient rdd: RDD[(K,V)], - private val ascending: Boolean = true) + @transient rdd: RDD[_ <: Product2[K,V]], + private val ascending: Boolean = true) extends Partitioner { // An array of upper bounds for the first (partitions - 1) partitions diff --git a/core/src/main/scala/org/apache/spark/SerializableWritable.scala b/core/src/main/scala/org/apache/spark/SerializableWritable.scala new file mode 100644 index 0000000000..fdd4c24e23 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/SerializableWritable.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import java.io._ + +import org.apache.hadoop.io.ObjectWritable +import org.apache.hadoop.io.Writable +import org.apache.hadoop.conf.Configuration + +class SerializableWritable[T <: Writable](@transient var t: T) extends Serializable { + def value = t + override def toString = t.toString + + private def writeObject(out: ObjectOutputStream) { + out.defaultWriteObject() + new ObjectWritable(t).write(out) + } + + private def readObject(in: ObjectInputStream) { + in.defaultReadObject() + val ow = new ObjectWritable() + ow.setConf(new Configuration()) + ow.readFields(in) + t = ow.get().asInstanceOf[T] + } +} diff --git a/core/src/main/scala/org/apache/spark/ShuffleFetcher.scala b/core/src/main/scala/org/apache/spark/ShuffleFetcher.scala new file mode 100644 index 0000000000..307c383a89 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ShuffleFetcher.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.apache.spark.executor.TaskMetrics +import org.apache.spark.serializer.Serializer + + +private[spark] abstract class ShuffleFetcher { + + /** + * Fetch the shuffle outputs for a given ShuffleDependency. + * @return An iterator over the elements of the fetched shuffle outputs. + */ + def fetch[T](shuffleId: Int, reduceId: Int, metrics: TaskMetrics, + serializer: Serializer = SparkEnv.get.serializerManager.default): Iterator[T] + + /** Stop the fetcher */ + def stop() {} +} diff --git a/core/src/main/scala/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index 01d9a70a78..04d172a989 100644 --- a/core/src/main/scala/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -1,23 +1,34 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io._ import java.net.URI import java.util.Properties -import java.util.concurrent.ConcurrentHashMap import java.util.concurrent.atomic.AtomicInteger -import scala.collection.JavaConversions._ import scala.collection.Map import scala.collection.generic.Growable -import scala.collection.mutable.HashMap import scala.collection.JavaConversions._ - +import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable.HashMap import scala.reflect.{ ClassTag, classTag} - import scala.util.DynamicVariable -import scala.collection.mutable.{ConcurrentMap, HashMap} - -import akka.actor.Actor._ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path @@ -39,20 +50,23 @@ import org.apache.hadoop.mapred.TextInputFormat import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} import org.apache.hadoop.mapreduce.{Job => NewHadoopJob} import org.apache.hadoop.mapreduce.lib.input.{FileInputFormat => NewFileInputFormat} -import org.apache.hadoop.security.UserGroupInformation import org.apache.mesos.MesosNativeLibrary -import spark.deploy.{LocalSparkCluster, SparkHadoopUtil} -import spark.partial.{ApproximateEvaluator, PartialResult} -import spark.rdd.{CheckpointRDD, HadoopRDD, NewHadoopRDD, UnionRDD, ParallelCollectionRDD} -import spark.scheduler.{DAGScheduler, ResultTask, ShuffleMapTask, SparkListener, SplitInfo, Stage, StageInfo, TaskScheduler} -import spark.scheduler.cluster.{StandaloneSchedulerBackend, SparkDeploySchedulerBackend, ClusterScheduler} -import spark.scheduler.local.LocalScheduler -import spark.scheduler.mesos.{CoarseMesosSchedulerBackend, MesosSchedulerBackend} -import spark.storage.{StorageStatus, StorageUtils, RDDInfo} -import spark.util.{MetadataCleaner, TimeStampedHashMap} -import ui.{SparkUI} +import org.apache.spark.deploy.LocalSparkCluster +import org.apache.spark.partial.{ApproximateEvaluator, PartialResult} +import org.apache.spark.rdd._ +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster.{StandaloneSchedulerBackend, SparkDeploySchedulerBackend, + ClusterScheduler, Schedulable, SchedulingMode} +import org.apache.spark.scheduler.local.LocalScheduler +import org.apache.spark.scheduler.mesos.{CoarseMesosSchedulerBackend, MesosSchedulerBackend} +import org.apache.spark.storage.{StorageUtils, BlockManagerSource} +import org.apache.spark.ui.SparkUI +import org.apache.spark.util.{ClosureCleaner, Utils, MetadataCleaner, TimeStampedHashMap} +import org.apache.spark.scheduler.StageInfo +import org.apache.spark.storage.RDDInfo +import org.apache.spark.storage.StorageStatus /** * Main entry point for Spark functionality. A SparkContext represents the connection to a Spark @@ -87,7 +101,7 @@ class SparkContext( System.setProperty("spark.driver.port", "0") } - private val isLocal = (master == "local" || master.startsWith("local[")) + val isLocal = (master == "local" || master.startsWith("local[")) // Create the Spark execution environment (cache, map output tracker, etc) private[spark] val env = SparkEnv.createFromSystemProperties( @@ -110,6 +124,8 @@ class SparkContext( private[spark] val ui = new SparkUI(this) ui.bind() + val startTime = System.currentTimeMillis() + // Add each JAR given through the constructor if (jars != null) { jars.foreach { addJar(_) } @@ -181,7 +197,7 @@ class SparkContext( case "yarn-standalone" => val scheduler = try { - val clazz = Class.forName("spark.scheduler.cluster.YarnClusterScheduler") + val clazz = Class.forName("org.apache.spark.scheduler.cluster.YarnClusterScheduler") val cons = clazz.getConstructor(classOf[SparkContext]) cons.newInstance(this).asInstanceOf[ClusterScheduler] } catch { @@ -221,7 +237,8 @@ class SparkContext( /** A default Hadoop Configuration for the Hadoop code (e.g. file systems) that we reuse. */ val hadoopConfiguration = { - val conf = SparkHadoopUtil.newConfiguration() + val env = SparkEnv.get + val conf = env.hadoop.newConfiguration() // Explicitly check for S3 environment variables if (System.getenv("AWS_ACCESS_KEY_ID") != null && System.getenv("AWS_SECRET_ACCESS_KEY") != null) { conf.set("fs.s3.awsAccessKeyId", System.getenv("AWS_ACCESS_KEY_ID")) @@ -247,15 +264,35 @@ class SparkContext( localProperties.value = new Properties() } - def addLocalProperties(key: String, value: String) { - if(localProperties.value == null) { + def setLocalProperty(key: String, value: String) { + if (localProperties.value == null) { localProperties.value = new Properties() } - localProperties.value.setProperty(key,value) + if (value == null) { + localProperties.value.remove(key) + } else { + localProperties.value.setProperty(key, value) + } + } + + /** Set a human readable description of the current job. */ + def setJobDescription(value: String) { + setLocalProperty(SparkContext.SPARK_JOB_DESCRIPTION, value) } + // Post init taskScheduler.postStartHook() + val dagSchedulerSource = new DAGSchedulerSource(this.dagScheduler) + val blockManagerSource = new BlockManagerSource(SparkEnv.get.blockManager) + + def initDriverMetrics() { + SparkEnv.get.metricsSystem.registerSource(dagSchedulerSource) + SparkEnv.get.metricsSystem.registerSource(blockManagerSource) + } + + initDriverMetrics() + // Methods for creating RDDs /** Distribute a local Scala collection to form an RDD. */ @@ -456,14 +493,14 @@ class SparkContext( // Methods for creating shared variables /** - * Create an [[spark.Accumulator]] variable of a given type, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] variable of a given type, which tasks can "add" values * to using the `+=` method. Only the driver can access the accumulator's `value`. */ def accumulator[T](initialValue: T)(implicit param: AccumulatorParam[T]) = new Accumulator(initialValue, param) /** - * Create an [[spark.Accumulable]] shared variable, to which tasks can add values with `+=`. + * Create an [[org.apache.spark.Accumulable]] shared variable, to which tasks can add values with `+=`. * Only the driver can access the accumuable's `value`. * @tparam T accumulator type * @tparam R type that can be added to the accumulator @@ -483,7 +520,7 @@ class SparkContext( } /** - * Broadcast a read-only variable to the cluster, returning a [[spark.broadcast.Broadcast]] object for + * Broadcast a read-only variable to the cluster, returning a [[org.apache.spark.broadcast.Broadcast]] object for * reading it in distributed functions. The variable will be sent to each cluster only once. */ def broadcast[T](value: T) = env.broadcastManager.newBroadcast[T](value, isLocal) @@ -511,7 +548,7 @@ class SparkContext( } def addSparkListener(listener: SparkListener) { - dagScheduler.sparkListeners += listener + dagScheduler.addSparkListener(listener) } /** @@ -532,6 +569,12 @@ class SparkContext( StorageUtils.rddInfoFromStorageStatus(getExecutorStorageStatus, this) } + /** + * Returns an immutable map of RDDs that have marked themselves as persistent via cache() call. + * Note that this does not necessarily mean the caching or computation was successful. + */ + def getPersistentRDDs: Map[Int, RDD[_]] = persistentRdds.toMap + def getStageInfo: Map[Stage,StageInfo] = { dagScheduler.stageToInfos } @@ -544,6 +587,28 @@ class SparkContext( } /** + * Return pools for fair scheduler + * TODO(xiajunluan): We should take nested pools into account + */ + def getAllPools: ArrayBuffer[Schedulable] = { + taskScheduler.rootPool.schedulableQueue + } + + /** + * Return the pool associated with the given name, if one exists + */ + def getPoolForName(pool: String): Option[Schedulable] = { + taskScheduler.rootPool.schedulableNameToSchedulable.get(pool) + } + + /** + * Return current scheduling mode + */ + def getSchedulingMode: SchedulingMode.SchedulingMode = { + taskScheduler.schedulingMode + } + + /** * Clear the job's list of files added by `addFile` so that they do not get downloaded to * any new nodes. */ @@ -552,19 +617,41 @@ class SparkContext( } /** + * Gets the locality information associated with the partition in a particular rdd + * @param rdd of interest + * @param partition to be looked up for locality + * @return list of preferred locations for the partition + */ + private [spark] def getPreferredLocs(rdd: RDD[_], partition: Int): Seq[TaskLocation] = { + dagScheduler.getPreferredLocs(rdd, partition) + } + + /** * Adds a JAR dependency for all tasks to be executed on this SparkContext in the future. * The `path` passed can be either a local file, a file in HDFS (or other Hadoop-supported * filesystems), or an HTTP, HTTPS or FTP URI. */ def addJar(path: String) { - if (null == path) { + if (path == null) { logWarning("null specified as parameter to addJar", new SparkException("null specified as parameter to addJar")) } else { - val uri = new URI(path) - val key = uri.getScheme match { - case null | "file" => env.httpFileServer.addJar(new File(uri.getPath)) - case _ => path + var key = "" + if (path.contains("\\")) { + // For local paths with backslashes on Windows, URI throws an exception + key = env.httpFileServer.addJar(new File(path)) + } else { + val uri = new URI(path) + key = uri.getScheme match { + case null | "file" => + if (env.hadoop.isYarnMode()) { + logWarning("local jar specified as parameter to addJar under Yarn mode") + return + } + env.httpFileServer.addJar(new File(uri.getPath)) + case _ => + path + } } addedJars(key) = System.currentTimeMillis logInfo("Added JAR " + path + " at " + key + " with timestamp " + addedJars(key)) @@ -742,8 +829,9 @@ class SparkContext( * prevent accidental overriding of checkpoint files in the existing directory. */ def setCheckpointDir(dir: String, useExisting: Boolean = false) { + val env = SparkEnv.get val path = new Path(dir) - val fs = path.getFileSystem(SparkHadoopUtil.newConfiguration()) + val fs = path.getFileSystem(env.hadoop.newConfiguration()) if (!useExisting) { if (fs.exists(path)) { throw new Exception("Checkpoint directory '" + path + "' already exists.") @@ -760,11 +848,11 @@ class SparkContext( /** Default min number of partitions for Hadoop RDDs when not given by user */ def defaultMinSplits: Int = math.min(defaultParallelism, 2) - private var nextShuffleId = new AtomicInteger(0) + private val nextShuffleId = new AtomicInteger(0) private[spark] def newShuffleId(): Int = nextShuffleId.getAndIncrement() - private var nextRddId = new AtomicInteger(0) + private val nextRddId = new AtomicInteger(0) /** Register a new RDD, returning its RDD ID */ private[spark] def newRddId(): Int = nextRddId.getAndIncrement() @@ -780,6 +868,7 @@ class SparkContext( * various Spark features. */ object SparkContext { + val SPARK_JOB_DESCRIPTION = "spark.job.description" implicit object DoubleAccumulatorParam extends AccumulatorParam[Double] { def addInPlace(t1: Double, t2: Double): Double = t1 + t2 @@ -812,7 +901,7 @@ object SparkContext { implicit def rddToOrderedRDDFunctions[K <% Ordered[K]: ClassTag, V: ClassTag]( rdd: RDD[(K, V)]) = - new OrderedRDDFunctions(rdd) + new OrderedRDDFunctions[K, V, (K, V)](rdd) implicit def doubleRDDToDoubleRDDFunctions(rdd: RDD[Double]) = new DoubleRDDFunctions(rdd) @@ -897,7 +986,6 @@ object SparkContext { } } - /** * A class encapsulating how to convert some type T to Writable. It stores both the Writable class * corresponding to T (e.g. IntWritable for Int) and a function for doing the conversion. @@ -909,3 +997,4 @@ private[spark] class WritableConverter[T]( val writableClass: ClassTag[T] => Class[_ <: Writable], val convert: Writable => T) extends Serializable + diff --git a/core/src/main/scala/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index 89d52064e1..1e63b54b7a 100644 --- a/core/src/main/scala/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import collection.mutable import serializer.Serializer @@ -6,13 +23,14 @@ import serializer.Serializer import akka.actor.{Actor, ActorRef, Props, ActorSystemImpl, ActorSystem} import akka.remote.RemoteActorRefProvider -import spark.broadcast.BroadcastManager -import spark.storage.BlockManager -import spark.storage.BlockManagerMaster -import spark.network.ConnectionManager -import spark.serializer.{Serializer, SerializerManager} -import spark.util.AkkaUtils -import spark.api.python.PythonWorkerFactory +import org.apache.spark.broadcast.BroadcastManager +import org.apache.spark.metrics.MetricsSystem +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.storage.{BlockManagerMasterActor, BlockManager, BlockManagerMaster} +import org.apache.spark.network.ConnectionManager +import org.apache.spark.serializer.{Serializer, SerializerManager} +import org.apache.spark.util.{Utils, AkkaUtils} +import org.apache.spark.api.python.PythonWorkerFactory /** @@ -36,13 +54,23 @@ class SparkEnv ( val connectionManager: ConnectionManager, val httpFileServer: HttpFileServer, val sparkFilesDir: String, - // To be set only as part of initialization of SparkContext. - // (executorId, defaultHostPort) => executorHostPort - // If executorId is NOT found, return defaultHostPort - var executorIdToHostPort: Option[(String, String) => String]) { + val metricsSystem: MetricsSystem) { private val pythonWorkers = mutable.HashMap[(String, Map[String, String]), PythonWorkerFactory]() + val hadoop = { + val yarnMode = java.lang.Boolean.valueOf(System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE"))) + if(yarnMode) { + try { + Class.forName("org.apache.spark.deploy.yarn.YarnSparkHadoopUtil").newInstance.asInstanceOf[SparkHadoopUtil] + } catch { + case th: Throwable => throw new SparkException("Unable to load YARN support", th) + } + } else { + new SparkHadoopUtil + } + } + def stop() { pythonWorkers.foreach { case(key, worker) => worker.stop() } httpFileServer.stop() @@ -51,6 +79,7 @@ class SparkEnv ( broadcastManager.stop() blockManager.stop() blockManager.master.stop() + metricsSystem.stop() actorSystem.shutdown() // Unfortunately Akka's awaitTermination doesn't actually wait for the Netty server to shut // down, but let's call it anyway in case it gets fixed in a later release @@ -64,27 +93,30 @@ class SparkEnv ( pythonWorkers.getOrElseUpdate(key, new PythonWorkerFactory(pythonExec, envVars)).create() } } - - def resolveExecutorIdToHostPort(executorId: String, defaultHostPort: String): String = { - val env = SparkEnv.get - if (env.executorIdToHostPort.isEmpty) { - // default to using host, not host port. Relevant to non cluster modes. - return defaultHostPort - } - - env.executorIdToHostPort.get(executorId, defaultHostPort) - } } object SparkEnv extends Logging { private val env = new ThreadLocal[SparkEnv] + @volatile private var lastSetSparkEnv : SparkEnv = _ def set(e: SparkEnv) { + lastSetSparkEnv = e env.set(e) } + /** + * Returns the ThreadLocal SparkEnv, if non-null. Else returns the SparkEnv + * previously set in any thread. + */ def get: SparkEnv = { - env.get() + Option(env.get()).getOrElse(lastSetSparkEnv) + } + + /** + * Returns the ThreadLocal SparkEnv. + */ + def getThreadLocal : SparkEnv = { + env.get() } def createFromSystemProperties( @@ -124,10 +156,10 @@ object SparkEnv extends Logging { val serializerManager = new SerializerManager val serializer = serializerManager.setDefault( - System.getProperty("spark.serializer", "spark.JavaSerializer")) + System.getProperty("spark.serializer", "org.apache.spark.serializer.JavaSerializer")) val closureSerializer = serializerManager.get( - System.getProperty("spark.closure.serializer", "spark.JavaSerializer")) + System.getProperty("spark.closure.serializer", "org.apache.spark.serializer.JavaSerializer")) def registerOrLookup(name: String, newActor: => Actor): ActorRef = { if (isDriver) { @@ -145,7 +177,7 @@ object SparkEnv extends Logging { val blockManagerMaster = new BlockManagerMaster(registerOrLookup( "BlockManagerMaster", - new spark.storage.BlockManagerMasterActor(isLocal))) + new BlockManagerMasterActor(isLocal))) val blockManager = new BlockManager(executorId, actorSystem, blockManagerMaster, serializer) val connectionManager = blockManager.connectionManager @@ -162,12 +194,19 @@ object SparkEnv extends Logging { new MapOutputTrackerActor(mapOutputTracker)) val shuffleFetcher = instantiateClass[ShuffleFetcher]( - "spark.shuffle.fetcher", "spark.BlockStoreShuffleFetcher") + "spark.shuffle.fetcher", "org.apache.spark.BlockStoreShuffleFetcher") val httpFileServer = new HttpFileServer() httpFileServer.initialize() System.setProperty("spark.fileserver.uri", httpFileServer.serverUri) + val metricsSystem = if (isDriver) { + MetricsSystem.createMetricsSystem("driver") + } else { + MetricsSystem.createMetricsSystem("executor") + } + metricsSystem.start() + // Set the sparkFiles directory, used when downloading dependencies. In local mode, // this is a temporary directory; in distributed mode, this is the executor's current working // directory. @@ -197,6 +236,6 @@ object SparkEnv extends Logging { connectionManager, httpFileServer, sparkFilesDir, - None) + metricsSystem) } } diff --git a/core/src/main/scala/org/apache/spark/SparkException.scala b/core/src/main/scala/org/apache/spark/SparkException.scala new file mode 100644 index 0000000000..d34e47e8ca --- /dev/null +++ b/core/src/main/scala/org/apache/spark/SparkException.scala @@ -0,0 +1,24 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +class SparkException(message: String, cause: Throwable) + extends Exception(message, cause) { + + def this(message: String) = this(message, null) +} diff --git a/core/src/main/scala/org/apache/spark/SparkFiles.java b/core/src/main/scala/org/apache/spark/SparkFiles.java new file mode 100644 index 0000000000..af9cf85e37 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/SparkFiles.java @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark; + +import java.io.File; + +/** + * Resolves paths to files added through `SparkContext.addFile()`. + */ +public class SparkFiles { + + private SparkFiles() {} + + /** + * Get the absolute path of a file added through `SparkContext.addFile()`. + */ + public static String get(String filename) { + return new File(getRootDirectory(), filename).getAbsolutePath(); + } + + /** + * Get the root directory that contains files added through `SparkContext.addFile()`. + */ + public static String getRootDirectory() { + return SparkEnv.get().sparkFilesDir(); + } +} diff --git a/core/src/main/scala/spark/HadoopWriter.scala b/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala index 5e8396edb9..2bab9d6e3d 100644 --- a/core/src/main/scala/spark/HadoopWriter.scala +++ b/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala @@ -1,3 +1,20 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + package org.apache.hadoop.mapred import org.apache.hadoop.fs.FileSystem @@ -8,8 +25,8 @@ import java.text.NumberFormat import java.io.IOException import java.util.Date -import spark.Logging -import spark.SerializableWritable +import org.apache.spark.Logging +import org.apache.spark.SerializableWritable /** * Internal helper class that saves an RDD using a Hadoop OutputFormat. This is only public @@ -19,7 +36,7 @@ import spark.SerializableWritable * Saves the RDD using a JobConf, which should contain an output key class, an output value class, * a filename to write to, etc, exactly like in a Hadoop MapReduce job. */ -class HadoopWriter(@transient jobConf: JobConf) extends Logging with HadoopMapRedUtil with Serializable { +class SparkHadoopWriter(@transient jobConf: JobConf) extends Logging with SparkHadoopMapRedUtil with Serializable { private val now = new Date() private val conf = new SerializableWritable(jobConf) @@ -148,7 +165,7 @@ class HadoopWriter(@transient jobConf: JobConf) extends Logging with HadoopMapRe splitID = splitid attemptID = attemptid - jID = new SerializableWritable[JobID](HadoopWriter.createJobID(now, jobid)) + jID = new SerializableWritable[JobID](SparkHadoopWriter.createJobID(now, jobid)) taID = new SerializableWritable[TaskAttemptID]( new TaskAttemptID(new TaskID(jID.value, true, splitID), attemptID)) } @@ -162,7 +179,7 @@ class HadoopWriter(@transient jobConf: JobConf) extends Logging with HadoopMapRe } } -object HadoopWriter { +object SparkHadoopWriter { def createJobID(time: Date, id: Int): JobID = { val formatter = new SimpleDateFormat("yyyyMMddHHmm") val jobtrackerID = formatter.format(new Date()) diff --git a/core/src/main/scala/org/apache/spark/TaskContext.scala b/core/src/main/scala/org/apache/spark/TaskContext.scala new file mode 100644 index 0000000000..b2dd668330 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/TaskContext.scala @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import executor.TaskMetrics +import scala.collection.mutable.ArrayBuffer + +class TaskContext( + val stageId: Int, + val splitId: Int, + val attemptId: Long, + val taskMetrics: TaskMetrics = TaskMetrics.empty() +) extends Serializable { + + @transient val onCompleteCallbacks = new ArrayBuffer[() => Unit] + + // Add a callback function to be executed on task completion. An example use + // is for HadoopRDD to register a callback to close the input stream. + def addOnCompleteCallback(f: () => Unit) { + onCompleteCallbacks += f + } + + def executeOnCompleteCallbacks() { + onCompleteCallbacks.foreach{_()} + } +} diff --git a/core/src/main/scala/spark/TaskEndReason.scala b/core/src/main/scala/org/apache/spark/TaskEndReason.scala index bb75ec208c..03bf268863 100644 --- a/core/src/main/scala/spark/TaskEndReason.scala +++ b/core/src/main/scala/org/apache/spark/TaskEndReason.scala @@ -1,7 +1,24 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark -import spark.executor.TaskMetrics -import spark.storage.BlockManagerId +import org.apache.spark.executor.TaskMetrics +import org.apache.spark.storage.BlockManagerId /** * Various possible reasons why a task ended. The low-level TaskScheduler is supposed to retry diff --git a/core/src/main/scala/spark/TaskState.scala b/core/src/main/scala/org/apache/spark/TaskState.scala index 44893ef089..0bf1e4a5e2 100644 --- a/core/src/main/scala/spark/TaskState.scala +++ b/core/src/main/scala/org/apache/spark/TaskState.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.apache.mesos.Protos.{TaskState => MesosTaskState} @@ -6,9 +23,11 @@ private[spark] object TaskState extends Enumeration { val LAUNCHING, RUNNING, FINISHED, FAILED, KILLED, LOST = Value + val FINISHED_STATES = Set(FINISHED, FAILED, KILLED, LOST) + type TaskState = Value - def isFinished(state: TaskState) = Seq(FINISHED, FAILED, LOST).contains(state) + def isFinished(state: TaskState) = FINISHED_STATES.contains(state) def toMesos(state: TaskState): MesosTaskState = state match { case LAUNCHING => MesosTaskState.TASK_STARTING diff --git a/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala index 3e88a9ccc7..f0a1960a1b 100644 --- a/core/src/main/scala/spark/api/java/JavaDoubleRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala @@ -1,14 +1,33 @@ -package spark.api.java +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java import scala.reflect.ClassTag -import spark.RDD -import spark.SparkContext.doubleRDDToDoubleRDDFunctions -import spark.api.java.function.{Function => JFunction} -import spark.util.StatCounter -import spark.partial.{BoundedDouble, PartialResult} -import spark.storage.StorageLevel + +import org.apache.spark.rdd.RDD +import org.apache.spark.SparkContext.doubleRDDToDoubleRDDFunctions +import org.apache.spark.api.java.function.{Function => JFunction} +import org.apache.spark.util.StatCounter +import org.apache.spark.partial.{BoundedDouble, PartialResult} +import org.apache.spark.storage.StorageLevel + import java.lang.Double -import spark.Partitioner +import org.apache.spark.Partitioner class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, JavaDoubleRDD] { @@ -99,33 +118,48 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[Double, Jav // Double RDD functions - /** Return the sum of the elements in this RDD. */ + /** Add up the elements in this RDD. */ def sum(): Double = srdd.sum() - /** Return a [[spark.StatCounter]] describing the elements in this RDD. */ + /** + * Return a [[org.apache.spark.util.StatCounter]] object that captures the mean, variance and count + * of the RDD's elements in one operation. + */ def stats(): StatCounter = srdd.stats() - /** Return the mean of the elements in this RDD. */ + /** Compute the mean of this RDD's elements. */ def mean(): Double = srdd.mean() - /** Return the variance of the elements in this RDD. */ + /** Compute the variance of this RDD's elements. */ def variance(): Double = srdd.variance() - /** Return the standard deviation of the elements in this RDD. */ + /** Compute the standard deviation of this RDD's elements. */ def stdev(): Double = srdd.stdev() + /** + * Compute the sample standard deviation of this RDD's elements (which corrects for bias in + * estimating the standard deviation by dividing by N-1 instead of N). + */ + def sampleStdev(): Double = srdd.sampleStdev() + + /** + * Compute the sample variance of this RDD's elements (which corrects for bias in + * estimating the standard variance by dividing by N-1 instead of N). + */ + def sampleVariance(): Double = srdd.sampleVariance() + /** Return the approximate mean of the elements in this RDD. */ def meanApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble] = srdd.meanApprox(timeout, confidence) - /** Return the approximate mean of the elements in this RDD. */ + /** (Experimental) Approximate operation to return the mean within a timeout. */ def meanApprox(timeout: Long): PartialResult[BoundedDouble] = srdd.meanApprox(timeout) - /** Return the approximate sum of the elements in this RDD. */ + /** (Experimental) Approximate operation to return the sum within a timeout. */ def sumApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble] = srdd.sumApprox(timeout, confidence) - /** Return the approximate sum of the elements in this RDD. */ + /** (Experimental) Approximate operation to return the sum within a timeout. */ def sumApprox(timeout: Long): PartialResult[BoundedDouble] = srdd.sumApprox(timeout) } diff --git a/core/src/main/scala/spark/api/java/JavaPairRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala index 0fa8162f3c..899e17d4fa 100644 --- a/core/src/main/scala/spark/api/java/JavaPairRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala @@ -1,4 +1,21 @@ -package spark.api.java +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java import java.util.{List => JList} import java.util.Comparator @@ -7,23 +24,25 @@ import scala.Tuple2 import scala.collection.JavaConversions._ import scala.reflect.ClassTag +import com.google.common.base.Optional import org.apache.hadoop.io.compress.CompressionCodec import org.apache.hadoop.mapred.JobConf import org.apache.hadoop.mapred.OutputFormat import org.apache.hadoop.mapreduce.{OutputFormat => NewOutputFormat} import org.apache.hadoop.conf.Configuration -import spark.api.java.function.{Function2 => JFunction2} -import spark.api.java.function.{Function => JFunction} -import spark.partial.BoundedDouble -import spark.partial.PartialResult -import spark.OrderedRDDFunctions -import spark.storage.StorageLevel -import spark.HashPartitioner -import spark.Partitioner -import spark.Partitioner._ -import spark.RDD -import spark.SparkContext.rddToPairRDDFunctions +import org.apache.spark.HashPartitioner +import org.apache.spark.Partitioner +import org.apache.spark.Partitioner._ +import org.apache.spark.SparkContext.rddToPairRDDFunctions +import org.apache.spark.api.java.function.{Function2 => JFunction2} +import org.apache.spark.api.java.function.{Function => JFunction} +import org.apache.spark.partial.BoundedDouble +import org.apache.spark.partial.PartialResult +import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.OrderedRDDFunctions +import org.apache.spark.storage.StorageLevel + class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K], implicit val vClassTag: ClassTag[V]) extends JavaRDDLike[(K, V), JavaPairRDD[K, V]] { @@ -236,11 +255,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K fromRDD(rdd.subtract(other, p)) /** - * Return a copy of the RDD partitioned using the specified partitioner. If `mapSideCombine` - * is true, Spark will group values of the same key together on the map side before the - * repartitioning, to only send each key over the network once. If a large number of - * duplicated keys are expected, and the size of the keys are large, `mapSideCombine` should - * be set to true. + * Return a copy of the RDD partitioned using the specified partitioner. */ def partitionBy(partitioner: Partitioner): JavaPairRDD[K, V] = fromRDD(rdd.partitionBy(partitioner)) @@ -260,8 +275,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * partition the output RDD. */ def leftOuterJoin[W](other: JavaPairRDD[K, W], partitioner: Partitioner) - : JavaPairRDD[K, (V, Option[W])] = - fromRDD(rdd.leftOuterJoin(other, partitioner)) + : JavaPairRDD[K, (V, Optional[W])] = { + val joinResult = rdd.leftOuterJoin(other, partitioner) + fromRDD(joinResult.mapValues{case (v, w) => (v, JavaUtils.optionToOptional(w))}) + } /** * Perform a right outer join of `this` and `other`. For each element (k, w) in `other`, the @@ -270,8 +287,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * partition the output RDD. */ def rightOuterJoin[W](other: JavaPairRDD[K, W], partitioner: Partitioner) - : JavaPairRDD[K, (Option[V], W)] = - fromRDD(rdd.rightOuterJoin(other, partitioner)) + : JavaPairRDD[K, (Optional[V], W)] = { + val joinResult = rdd.rightOuterJoin(other, partitioner) + fromRDD(joinResult.mapValues{case (v, w) => (JavaUtils.optionToOptional(v), w)}) + } /** * Simplified version of combineByKey that hash-partitions the resulting RDD using the existing @@ -324,8 +343,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * pair (k, (v, None)) if no elements in `other` have key k. Hash-partitions the output * using the existing partitioner/parallelism level. */ - def leftOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (V, Option[W])] = - fromRDD(rdd.leftOuterJoin(other)) + def leftOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (V, Optional[W])] = { + val joinResult = rdd.leftOuterJoin(other) + fromRDD(joinResult.mapValues{case (v, w) => (v, JavaUtils.optionToOptional(w))}) + } /** * Perform a left outer join of `this` and `other`. For each element (k, v) in `this`, the @@ -333,8 +354,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * pair (k, (v, None)) if no elements in `other` have key k. Hash-partitions the output * into `numPartitions` partitions. */ - def leftOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (V, Option[W])] = - fromRDD(rdd.leftOuterJoin(other, numPartitions)) + def leftOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (V, Optional[W])] = { + val joinResult = rdd.leftOuterJoin(other, numPartitions) + fromRDD(joinResult.mapValues{case (v, w) => (v, JavaUtils.optionToOptional(w))}) + } /** * Perform a right outer join of `this` and `other`. For each element (k, w) in `other`, the @@ -342,8 +365,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * pair (k, (None, w)) if no elements in `this` have key k. Hash-partitions the resulting * RDD using the existing partitioner/parallelism level. */ - def rightOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Option[V], W)] = - fromRDD(rdd.rightOuterJoin(other)) + def rightOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Optional[V], W)] = { + val joinResult = rdd.rightOuterJoin(other) + fromRDD(joinResult.mapValues{case (v, w) => (JavaUtils.optionToOptional(v), w)}) + } /** * Perform a right outer join of `this` and `other`. For each element (k, w) in `other`, the @@ -351,8 +376,10 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * pair (k, (None, w)) if no elements in `this` have key k. Hash-partitions the resulting * RDD into the given number of partitions. */ - def rightOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Option[V], W)] = - fromRDD(rdd.rightOuterJoin(other, numPartitions)) + def rightOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Optional[V], W)] = { + val joinResult = rdd.rightOuterJoin(other, numPartitions) + fromRDD(joinResult.mapValues{case (v, w) => (JavaUtils.optionToOptional(v), w)}) + } /** * Return the key-value pairs in this RDD to the master as a Map. @@ -538,7 +565,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K override def compare(b: K) = comp.compare(a, b) } implicit def toOrdered(x: K): Ordered[K] = new KeyOrdering(x) - fromRDD(new OrderedRDDFunctions(rdd).sortByKey(ascending)) + fromRDD(new OrderedRDDFunctions[K, V, (K, V)](rdd).sortByKey(ascending)) } /** diff --git a/core/src/main/scala/spark/api/java/JavaRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala index 6f44e018e9..9968bc8e5f 100644 --- a/core/src/main/scala/spark/api/java/JavaRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala @@ -1,9 +1,28 @@ -package spark.api.java +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java import scala.reflect.ClassTag -import spark._ -import spark.api.java.function.{Function => JFunction} -import spark.storage.StorageLevel + +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.api.java.function.{Function => JFunction} +import org.apache.spark.storage.StorageLevel class JavaRDD[T](val rdd: RDD[T])(implicit val classTag: ClassTag[T]) extends JavaRDDLike[T, JavaRDD[T]] { diff --git a/core/src/main/scala/spark/api/java/JavaRDDLike.scala b/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala index b0d094d564..feb2cab578 100644 --- a/core/src/main/scala/spark/api/java/JavaRDDLike.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala @@ -1,17 +1,36 @@ -package spark.api.java +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java import java.util.{List => JList, Comparator} import scala.Tuple2 import scala.collection.JavaConversions._ import scala.reflect.ClassTag -import org.apache.hadoop.io.compress.CompressionCodec -import spark.{SparkContext, Partition, RDD, TaskContext} -import spark.api.java.JavaPairRDD._ -import spark.api.java.function.{Function2 => JFunction2, Function => JFunction, _} -import spark.partial.{PartialResult, BoundedDouble} -import spark.storage.StorageLevel import com.google.common.base.Optional +import org.apache.hadoop.io.compress.CompressionCodec + +import org.apache.spark.{SparkContext, Partition, TaskContext} +import org.apache.spark.rdd.RDD +import org.apache.spark.api.java.JavaPairRDD._ +import org.apache.spark.api.java.function.{Function2 => JFunction2, Function => JFunction, _} +import org.apache.spark.partial.{PartialResult, BoundedDouble} +import org.apache.spark.storage.StorageLevel trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable { @@ -24,7 +43,7 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable { /** Set of partitions in this RDD. */ def splits: JList[Partition] = new java.util.ArrayList(rdd.partitions.toSeq) - /** The [[spark.SparkContext]] that this RDD was created on. */ + /** The [[org.apache.spark.SparkContext]] that this RDD was created on. */ def context: SparkContext = rdd.context /** A unique ID for this RDD (within its SparkContext). */ @@ -191,12 +210,12 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable { * of elements in each partition. */ def zipPartitions[U, V]( - f: FlatMapFunction2[java.util.Iterator[T], java.util.Iterator[U], V], - other: JavaRDDLike[U, _]): JavaRDD[V] = { + other: JavaRDDLike[U, _], + f: FlatMapFunction2[java.util.Iterator[T], java.util.Iterator[U], V]): JavaRDD[V] = { def fn = (x: Iterator[T], y: Iterator[U]) => asScalaIterator( f.apply(asJavaIterator(x), asJavaIterator(y)).iterator()) JavaRDD.fromRDD( - rdd.zipPartitions(fn, other.rdd)(other.classTag, f.elementType()))(f.elementType()) + rdd.zipPartitions(other.rdd)(fn)(other.classTag, f.elementType()))(f.elementType()) } // Actions (launch a job to return a value to the user program) @@ -350,10 +369,7 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable { * Gets the name of the file to which this RDD was checkpointed */ def getCheckpointFile(): Optional[String] = { - rdd.getCheckpointFile match { - case Some(file) => Optional.of(file) - case _ => Optional.absent() - } + JavaUtils.optionToOptional(rdd.getCheckpointFile) } /** A description of this RDD and its recursive dependencies for debugging. */ diff --git a/core/src/main/scala/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala index b633273eaf..d5b77357a2 100644 --- a/core/src/main/scala/spark/api/java/JavaSparkContext.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala @@ -1,4 +1,21 @@ -package spark.api.java +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java import java.util.{Map => JMap} @@ -10,14 +27,16 @@ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.mapred.InputFormat import org.apache.hadoop.mapred.JobConf import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} +import com.google.common.base.Optional -import spark.{Accumulable, AccumulableParam, Accumulator, AccumulatorParam, RDD, SparkContext} -import spark.SparkContext.IntAccumulatorParam -import spark.SparkContext.DoubleAccumulatorParam -import spark.broadcast.Broadcast +import org.apache.spark.{Accumulable, AccumulableParam, Accumulator, AccumulatorParam, SparkContext} +import org.apache.spark.SparkContext.IntAccumulatorParam +import org.apache.spark.SparkContext.DoubleAccumulatorParam +import org.apache.spark.broadcast.Broadcast +import org.apache.spark.rdd.RDD /** - * A Java-friendly version of [[spark.SparkContext]] that returns [[spark.api.java.JavaRDD]]s and + * A Java-friendly version of [[org.apache.spark.SparkContext]] that returns [[org.apache.spark.api.java.JavaRDD]]s and * works with Java collections instead of Scala ones. */ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWorkaround { @@ -265,48 +284,48 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork } /** - * Create an [[spark.Accumulator]] integer variable, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] integer variable, which tasks can "add" values * to using the `add` method. Only the master can access the accumulator's `value`. */ def intAccumulator(initialValue: Int): Accumulator[java.lang.Integer] = sc.accumulator(initialValue)(IntAccumulatorParam).asInstanceOf[Accumulator[java.lang.Integer]] /** - * Create an [[spark.Accumulator]] double variable, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] double variable, which tasks can "add" values * to using the `add` method. Only the master can access the accumulator's `value`. */ def doubleAccumulator(initialValue: Double): Accumulator[java.lang.Double] = sc.accumulator(initialValue)(DoubleAccumulatorParam).asInstanceOf[Accumulator[java.lang.Double]] /** - * Create an [[spark.Accumulator]] integer variable, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] integer variable, which tasks can "add" values * to using the `add` method. Only the master can access the accumulator's `value`. */ def accumulator(initialValue: Int): Accumulator[java.lang.Integer] = intAccumulator(initialValue) /** - * Create an [[spark.Accumulator]] double variable, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] double variable, which tasks can "add" values * to using the `add` method. Only the master can access the accumulator's `value`. */ def accumulator(initialValue: Double): Accumulator[java.lang.Double] = doubleAccumulator(initialValue) /** - * Create an [[spark.Accumulator]] variable of a given type, which tasks can "add" values + * Create an [[org.apache.spark.Accumulator]] variable of a given type, which tasks can "add" values * to using the `add` method. Only the master can access the accumulator's `value`. */ def accumulator[T](initialValue: T, accumulatorParam: AccumulatorParam[T]): Accumulator[T] = sc.accumulator(initialValue)(accumulatorParam) /** - * Create an [[spark.Accumulable]] shared variable of the given type, to which tasks can + * Create an [[org.apache.spark.Accumulable]] shared variable of the given type, to which tasks can * "add" values with `add`. Only the master can access the accumuable's `value`. */ def accumulable[T, R](initialValue: T, param: AccumulableParam[T, R]): Accumulable[T, R] = sc.accumulable(initialValue)(param) /** - * Broadcast a read-only variable to the cluster, returning a [[spark.Broadcast]] object for + * Broadcast a read-only variable to the cluster, returning a [[org.apache.spark.Broadcast]] object for * reading it in distributed functions. The variable will be sent to each cluster only once. */ def broadcast[T](value: T): Broadcast[T] = sc.broadcast(value) @@ -321,7 +340,7 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork * or the spark.home Java property, or the SPARK_HOME environment variable * (in that order of preference). If neither of these is set, return None. */ - def getSparkHome(): Option[String] = sc.getSparkHome() + def getSparkHome(): Optional[String] = JavaUtils.optionToOptional(sc.getSparkHome()) /** * Add a file to be downloaded with this Spark job on every node. diff --git a/core/src/main/scala/spark/api/java/JavaSparkContextVarargsWorkaround.java b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContextVarargsWorkaround.java index 97344e73da..c9cbce5624 100644 --- a/core/src/main/scala/spark/api/java/JavaSparkContextVarargsWorkaround.java +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContextVarargsWorkaround.java @@ -1,4 +1,21 @@ -package spark.api.java; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java; import java.util.Arrays; import java.util.ArrayList; diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala b/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala new file mode 100644 index 0000000000..ecbf18849a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java + +import com.google.common.base.Optional + +object JavaUtils { + def optionToOptional[T](option: Option[T]): Optional[T] = + option match { + case Some(value) => Optional.of(value) + case None => Optional.absent() + } +} diff --git a/core/src/main/scala/spark/api/java/StorageLevels.java b/core/src/main/scala/org/apache/spark/api/java/StorageLevels.java index 5e5845ac3a..0744269773 100644 --- a/core/src/main/scala/spark/api/java/StorageLevels.java +++ b/core/src/main/scala/org/apache/spark/api/java/StorageLevels.java @@ -1,6 +1,23 @@ -package spark.api.java; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java; -import spark.storage.StorageLevel; +import org.apache.spark.storage.StorageLevel; /** * Expose some commonly useful storage level constants. diff --git a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java new file mode 100644 index 0000000000..4830067f7a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java @@ -0,0 +1,37 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; + + +import scala.runtime.AbstractFunction1; + +import java.io.Serializable; + +/** + * A function that returns zero or more records of type Double from each input record. + */ +// DoubleFlatMapFunction does not extend FlatMapFunction because flatMap is +// overloaded for both FlatMapFunction and DoubleFlatMapFunction. +public abstract class DoubleFlatMapFunction<T> extends AbstractFunction1<T, Iterable<Double>> + implements Serializable { + + public abstract Iterable<Double> call(T t); + + @Override + public final Iterable<Double> apply(T t) { return call(t); } +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java new file mode 100644 index 0000000000..db34cd190a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java @@ -0,0 +1,34 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; + + +import scala.runtime.AbstractFunction1; + +import java.io.Serializable; + +/** + * A function that returns Doubles, and can be used to construct DoubleRDDs. + */ +// DoubleFunction does not extend Function because some UDF functions, like map, +// are overloaded for both Function and DoubleFunction. +public abstract class DoubleFunction<T> extends WrappedFunction1<T, Double> + implements Serializable { + + public abstract Double call(T t) throws Exception; +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala new file mode 100644 index 0000000000..b7c0d78e33 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala @@ -0,0 +1,30 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function + +import scala.reflect.ClassTag + +/** + * A function that returns zero or more output records from each input record. + */ +abstract class FlatMapFunction[T, R] extends Function[T, java.lang.Iterable[R]] { + @throws(classOf[Exception]) + def call(x: T) : java.lang.Iterable[R] + + def elementType() : ClassTag[R] = ClassTag.Any.asInstanceOf[ClassTag[R]] +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala new file mode 100644 index 0000000000..7a505df4be --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala @@ -0,0 +1,30 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function + +import scala.reflect.ClassTag + +/** + * A function that takes two inputs and returns zero or more output records. + */ +abstract class FlatMapFunction2[A, B, C] extends Function2[A, B, java.lang.Iterable[C]] { + @throws(classOf[Exception]) + def call(a: A, b:B) : java.lang.Iterable[C] + + def elementType() : ClassTag[C] = ClassTag.Any.asInstanceOf[ClassTag[C]] +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/Function.java b/core/src/main/scala/org/apache/spark/api/java/function/Function.java new file mode 100644 index 0000000000..f9dae6ed34 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/Function.java @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; + +import scala.reflect.ClassTag; +import scala.reflect.ClassTag$; +import scala.runtime.AbstractFunction1; + +import java.io.Serializable; + + +/** + * Base class for functions whose return types do not create special RDDs. PairFunction and + * DoubleFunction are handled separately, to allow PairRDDs and DoubleRDDs to be constructed + * when mapping RDDs of other types. + */ +public abstract class Function<T, R> extends WrappedFunction1<T, R> implements Serializable { + public abstract R call(T t) throws Exception; + + public ClassTag<R> returnType() { + return (ClassTag<R>) ClassTag$.MODULE$.apply(Object.class); + } +} + diff --git a/core/src/main/scala/org/apache/spark/api/java/function/Function2.java b/core/src/main/scala/org/apache/spark/api/java/function/Function2.java new file mode 100644 index 0000000000..1659bfc552 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/Function2.java @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; + +import scala.reflect.ClassTag; +import scala.reflect.ClassTag$; +import scala.runtime.AbstractFunction2; + +import java.io.Serializable; + +/** + * A two-argument function that takes arguments of type T1 and T2 and returns an R. + */ +public abstract class Function2<T1, T2, R> extends WrappedFunction2<T1, T2, R> + implements Serializable { + + public abstract R call(T1 t1, T2 t2) throws Exception; + + public ClassTag<R> returnType() { + return (ClassTag<R>) ClassTag$.MODULE$.apply(Object.class); + } +} + diff --git a/core/src/main/scala/spark/api/java/function/PairFlatMapFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java index 296a3b5044..5a5c9b6296 100644 --- a/core/src/main/scala/spark/api/java/function/PairFlatMapFunction.java +++ b/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java @@ -1,4 +1,21 @@ -package spark.api.java.function; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; import scala.Tuple2; import scala.reflect.ClassTag; diff --git a/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java new file mode 100644 index 0000000000..4c39f483e5 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function; + +import scala.Tuple2; +import scala.reflect.ClassTag; +import scala.reflect.ClassTag$; +import scala.runtime.AbstractFunction1; + +import java.io.Serializable; + +/** + * A function that returns key-value pairs (Tuple2<K, V>), and can be used to construct PairRDDs. + */ +// PairFunction does not extend Function because some UDF functions, like map, +// are overloaded for both Function and PairFunction. +public abstract class PairFunction<T, K, V> + extends WrappedFunction1<T, Tuple2<K, V>> + implements Serializable { + + public abstract Tuple2<K, V> call(T t) throws Exception; + + public ClassTag<K> keyType() { + return (ClassTag<K>) ClassTag$.MODULE$.apply(Object.class); + } + + public ClassTag<V> valueType() { + return (ClassTag<V>) ClassTag$.MODULE$.apply(Object.class); + } +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/VoidFunction.scala b/core/src/main/scala/org/apache/spark/api/java/function/VoidFunction.scala new file mode 100644 index 0000000000..ea94313a4a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/VoidFunction.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function + +/** + * A function with no return value. + */ +// This allows Java users to write void methods without having to return Unit. +abstract class VoidFunction[T] extends Serializable { + @throws(classOf[Exception]) + def call(t: T) : Unit +} + +// VoidFunction cannot extend AbstractFunction1 (because that would force users to explicitly +// return Unit), so it is implicitly converted to a Function1[T, Unit]: +object VoidFunction { + implicit def toFunction[T](f: VoidFunction[T]) : Function1[T, Unit] = ((x : T) => f.call(x)) +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction1.scala b/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction1.scala new file mode 100644 index 0000000000..cfe694f65d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction1.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function + +import scala.runtime.AbstractFunction1 + +/** + * Subclass of Function1 for ease of calling from Java. The main thing it does is re-expose the + * apply() method as call() and declare that it can throw Exception (since AbstractFunction1.apply + * isn't marked to allow that). + */ +private[spark] abstract class WrappedFunction1[T, R] extends AbstractFunction1[T, R] { + @throws(classOf[Exception]) + def call(t: T): R + + final def apply(t: T): R = call(t) +} diff --git a/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction2.scala b/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction2.scala new file mode 100644 index 0000000000..eb9277c6fb --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/java/function/WrappedFunction2.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.java.function + +import scala.runtime.AbstractFunction2 + +/** + * Subclass of Function2 for ease of calling from Java. The main thing it does is re-expose the + * apply() method as call() and declare that it can throw Exception (since AbstractFunction2.apply + * isn't marked to allow that). + */ +private[spark] abstract class WrappedFunction2[T1, T2, R] extends AbstractFunction2[T1, T2, R] { + @throws(classOf[Exception]) + def call(t1: T1, t2: T2): R + + final def apply(t1: T1, t2: T2): R = call(t1, t2) +} diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonPartitioner.scala b/core/src/main/scala/org/apache/spark/api/python/PythonPartitioner.scala new file mode 100644 index 0000000000..b090c6edf3 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/python/PythonPartitioner.scala @@ -0,0 +1,50 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.python + +import org.apache.spark.Partitioner +import java.util.Arrays +import org.apache.spark.util.Utils + +/** + * A [[org.apache.spark.Partitioner]] that performs handling of byte arrays, for use by the Python API. + * + * Stores the unique id() of the Python-side partitioning function so that it is incorporated into + * equality comparisons. Correctness requires that the id is a unique identifier for the + * lifetime of the program (i.e. that it is not re-used as the id of a different partitioning + * function). This can be ensured by using the Python id() function and maintaining a reference + * to the Python partitioning function so that its id() is not reused. + */ +private[spark] class PythonPartitioner( + override val numPartitions: Int, + val pyPartitionFunctionId: Long) + extends Partitioner { + + override def getPartition(key: Any): Int = key match { + case null => 0 + case key: Array[Byte] => Utils.nonNegativeMod(Arrays.hashCode(key), numPartitions) + case _ => Utils.nonNegativeMod(key.hashCode(), numPartitions) + } + + override def equals(other: Any): Boolean = other match { + case h: PythonPartitioner => + h.numPartitions == numPartitions && h.pyPartitionFunctionId == pyPartitionFunctionId + case _ => + false + } +} diff --git a/core/src/main/scala/spark/api/python/PythonRDD.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala index d15c75289d..cb2db77f39 100644 --- a/core/src/main/scala/spark/api/python/PythonRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala @@ -1,24 +1,41 @@ -package spark.api.python +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.python import java.io._ import java.net._ import java.util.{List => JList, ArrayList => JArrayList, Map => JMap, Collections} import scala.collection.JavaConversions._ - -import scala.io.Source import scala.reflect.ClassTag -import spark.api.java.{JavaSparkContext, JavaPairRDD, JavaRDD} -import spark.broadcast.Broadcast -import spark._ -import spark.rdd.PipedRDD - +import org.apache.spark.api.java.{JavaSparkContext, JavaPairRDD, JavaRDD} +import org.apache.spark.broadcast.Broadcast +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.PipedRDD +import org.apache.spark.util.Utils private[spark] class PythonRDD[T: ClassTag]( parent: RDD[T], command: Seq[String], envVars: JMap[String, String], + pythonIncludes: JList[String], preservePartitoning: Boolean, pythonExec: String, broadcastVars: JList[Broadcast[Array[Byte]]], @@ -30,10 +47,11 @@ private[spark] class PythonRDD[T: ClassTag]( // Similar to Runtime.exec(), if we are given a single string, split it into words // using a standard StringTokenizer (i.e. by spaces) def this(parent: RDD[T], command: String, envVars: JMap[String, String], + pythonIncludes: JList[String], preservePartitoning: Boolean, pythonExec: String, broadcastVars: JList[Broadcast[Array[Byte]]], accumulator: Accumulator[JList[Array[Byte]]]) = - this(parent, PipedRDD.tokenize(command), envVars, preservePartitoning, pythonExec, + this(parent, PipedRDD.tokenize(command), envVars, pythonIncludes, preservePartitoning, pythonExec, broadcastVars, accumulator) override def getPartitions = parent.partitions @@ -49,34 +67,47 @@ private[spark] class PythonRDD[T: ClassTag]( // Start a thread to feed the process input from our parent's iterator new Thread("stdin writer for " + pythonExec) { override def run() { - SparkEnv.set(env) - val stream = new BufferedOutputStream(worker.getOutputStream, bufferSize) - val dataOut = new DataOutputStream(stream) - val printOut = new PrintWriter(stream) - // Partition index - dataOut.writeInt(split.index) - // sparkFilesDir - PythonRDD.writeAsPickle(SparkFiles.getRootDirectory, dataOut) - // Broadcast variables - dataOut.writeInt(broadcastVars.length) - for (broadcast <- broadcastVars) { - dataOut.writeLong(broadcast.id) - dataOut.writeInt(broadcast.value.length) - dataOut.write(broadcast.value) - } - dataOut.flush() - // Serialized user code - for (elem <- command) { - printOut.println(elem) - } - printOut.flush() - // Data values - for (elem <- parent.iterator(split, context)) { - PythonRDD.writeAsPickle(elem, dataOut) + try { + SparkEnv.set(env) + val stream = new BufferedOutputStream(worker.getOutputStream, bufferSize) + val dataOut = new DataOutputStream(stream) + val printOut = new PrintWriter(stream) + // Partition index + dataOut.writeInt(split.index) + // sparkFilesDir + PythonRDD.writeAsPickle(SparkFiles.getRootDirectory, dataOut) + // Broadcast variables + dataOut.writeInt(broadcastVars.length) + for (broadcast <- broadcastVars) { + dataOut.writeLong(broadcast.id) + dataOut.writeInt(broadcast.value.length) + dataOut.write(broadcast.value) + } + // Python includes (*.zip and *.egg files) + dataOut.writeInt(pythonIncludes.length) + for (f <- pythonIncludes) { + PythonRDD.writeAsPickle(f, dataOut) + } + dataOut.flush() + // Serialized user code + for (elem <- command) { + printOut.println(elem) + } + printOut.flush() + // Data values + for (elem <- parent.iterator(split, context)) { + PythonRDD.writeAsPickle(elem, dataOut) + } + dataOut.flush() + printOut.flush() + worker.shutdownOutput() + } catch { + case e: IOException => + // This can happen for legitimate reasons if the Python code stops returning data before we are done + // passing elements through, e.g., for take(). Just log a message to say it happened. + logInfo("stdin writer to Python finished early") + logDebug("stdin writer to Python finished early", e) } - dataOut.flush() - printOut.flush() - worker.shutdownOutput() } }.start() @@ -269,7 +300,7 @@ private object Pickle { val APPENDS: Byte = 'e' } -private class BytesToString extends spark.api.java.function.Function[Array[Byte], String] { +private class BytesToString extends org.apache.spark.api.java.function.Function[Array[Byte], String] { override def call(arr: Array[Byte]) : String = new String(arr, "UTF-8") } diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala new file mode 100644 index 0000000000..67d45723ba --- /dev/null +++ b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala @@ -0,0 +1,223 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.python + +import java.io.{OutputStreamWriter, File, DataInputStream, IOException} +import java.net.{ServerSocket, Socket, SocketException, InetAddress} + +import scala.collection.JavaConversions._ + +import org.apache.spark._ + +private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String, String]) + extends Logging { + + // Because forking processes from Java is expensive, we prefer to launch a single Python daemon + // (pyspark/daemon.py) and tell it to fork new workers for our tasks. This daemon currently + // only works on UNIX-based systems now because it uses signals for child management, so we can + // also fall back to launching workers (pyspark/worker.py) directly. + val useDaemon = !System.getProperty("os.name").startsWith("Windows") + + var daemon: Process = null + val daemonHost = InetAddress.getByAddress(Array(127, 0, 0, 1)) + var daemonPort: Int = 0 + + def create(): Socket = { + if (useDaemon) { + createThroughDaemon() + } else { + createSimpleWorker() + } + } + + /** + * Connect to a worker launched through pyspark/daemon.py, which forks python processes itself + * to avoid the high cost of forking from Java. This currently only works on UNIX-based systems. + */ + private def createThroughDaemon(): Socket = { + synchronized { + // Start the daemon if it hasn't been started + startDaemon() + + // Attempt to connect, restart and retry once if it fails + try { + new Socket(daemonHost, daemonPort) + } catch { + case exc: SocketException => { + logWarning("Python daemon unexpectedly quit, attempting to restart") + stopDaemon() + startDaemon() + new Socket(daemonHost, daemonPort) + } + case e => throw e + } + } + } + + /** + * Launch a worker by executing worker.py directly and telling it to connect to us. + */ + private def createSimpleWorker(): Socket = { + var serverSocket: ServerSocket = null + try { + serverSocket = new ServerSocket(0, 1, InetAddress.getByAddress(Array(127, 0, 0, 1))) + + // Create and start the worker + val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME") + val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/worker.py")) + val workerEnv = pb.environment() + workerEnv.putAll(envVars) + val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH") + workerEnv.put("PYTHONPATH", pythonPath) + val worker = pb.start() + + // Redirect the worker's stderr to ours + new Thread("stderr reader for " + pythonExec) { + setDaemon(true) + override def run() { + scala.util.control.Exception.ignoring(classOf[IOException]) { + // FIXME: We copy the stream on the level of bytes to avoid encoding problems. + val in = worker.getErrorStream + val buf = new Array[Byte](1024) + var len = in.read(buf) + while (len != -1) { + System.err.write(buf, 0, len) + len = in.read(buf) + } + } + } + }.start() + + // Redirect worker's stdout to our stderr + new Thread("stdout reader for " + pythonExec) { + setDaemon(true) + override def run() { + scala.util.control.Exception.ignoring(classOf[IOException]) { + // FIXME: We copy the stream on the level of bytes to avoid encoding problems. + val in = worker.getInputStream + val buf = new Array[Byte](1024) + var len = in.read(buf) + while (len != -1) { + System.err.write(buf, 0, len) + len = in.read(buf) + } + } + } + }.start() + + // Tell the worker our port + val out = new OutputStreamWriter(worker.getOutputStream) + out.write(serverSocket.getLocalPort + "\n") + out.flush() + + // Wait for it to connect to our socket + serverSocket.setSoTimeout(10000) + try { + return serverSocket.accept() + } catch { + case e: Exception => + throw new SparkException("Python worker did not connect back in time", e) + } + } finally { + if (serverSocket != null) { + serverSocket.close() + } + } + null + } + + def stop() { + stopDaemon() + } + + private def startDaemon() { + synchronized { + // Is it already running? + if (daemon != null) { + return + } + + try { + // Create and start the daemon + val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME") + val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/daemon.py")) + val workerEnv = pb.environment() + workerEnv.putAll(envVars) + val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH") + workerEnv.put("PYTHONPATH", pythonPath) + daemon = pb.start() + + // Redirect the stderr to ours + new Thread("stderr reader for " + pythonExec) { + setDaemon(true) + override def run() { + scala.util.control.Exception.ignoring(classOf[IOException]) { + // FIXME: We copy the stream on the level of bytes to avoid encoding problems. + val in = daemon.getErrorStream + val buf = new Array[Byte](1024) + var len = in.read(buf) + while (len != -1) { + System.err.write(buf, 0, len) + len = in.read(buf) + } + } + } + }.start() + + val in = new DataInputStream(daemon.getInputStream) + daemonPort = in.readInt() + + // Redirect further stdout output to our stderr + new Thread("stdout reader for " + pythonExec) { + setDaemon(true) + override def run() { + scala.util.control.Exception.ignoring(classOf[IOException]) { + // FIXME: We copy the stream on the level of bytes to avoid encoding problems. + val buf = new Array[Byte](1024) + var len = in.read(buf) + while (len != -1) { + System.err.write(buf, 0, len) + len = in.read(buf) + } + } + } + }.start() + } catch { + case e => { + stopDaemon() + throw e + } + } + + // Important: don't close daemon's stdin (daemon.getOutputStream) so it can correctly + // detect our disappearance. + } + } + + private def stopDaemon() { + synchronized { + // Request shutdown of existing daemon by sending SIGTERM + if (daemon != null) { + daemon.destroy() + } + + daemon = null + daemonPort = 0 + } + } +} diff --git a/core/src/main/scala/spark/broadcast/BitTorrentBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/BitTorrentBroadcast.scala index adcb2d2415..93e7815ab5 100644 --- a/core/src/main/scala/spark/broadcast/BitTorrentBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/BitTorrentBroadcast.scala @@ -1,4 +1,21 @@ -package spark.broadcast +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast import java.io._ import java.net._ @@ -8,8 +25,9 @@ import java.util.concurrent.atomic.AtomicInteger import scala.collection.mutable.{ListBuffer, Map, Set} import scala.math -import spark._ -import spark.storage.StorageLevel +import org.apache.spark._ +import org.apache.spark.storage.StorageLevel +import org.apache.spark.util.Utils private[spark] class BitTorrentBroadcast[T](@transient var value_ : T, isLocal: Boolean, id: Long) extends Broadcast[T](id) diff --git a/core/src/main/scala/spark/broadcast/Broadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala index 415bde5d67..43c18294c5 100644 --- a/core/src/main/scala/spark/broadcast/Broadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala @@ -1,9 +1,26 @@ -package spark.broadcast +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast import java.io._ import java.util.concurrent.atomic.AtomicLong -import spark._ +import org.apache.spark._ abstract class Broadcast[T](private[spark] val id: Long) extends Serializable { def value: T @@ -11,7 +28,7 @@ abstract class Broadcast[T](private[spark] val id: Long) extends Serializable { // We cannot have an abstract readObject here due to some weird issues with // readObject having to be 'private' in sub-classes. - override def toString = "spark.Broadcast(" + id + ")" + override def toString = "Broadcast(" + id + ")" } private[spark] @@ -27,7 +44,7 @@ class BroadcastManager(val _isDriver: Boolean) extends Logging with Serializable synchronized { if (!initialized) { val broadcastFactoryClass = System.getProperty( - "spark.broadcast.factory", "spark.broadcast.HttpBroadcastFactory") + "spark.broadcast.factory", "org.apache.spark.broadcast.HttpBroadcastFactory") broadcastFactory = Class.forName(broadcastFactoryClass).newInstance.asInstanceOf[BroadcastFactory] diff --git a/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala b/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala new file mode 100644 index 0000000000..68bff75b90 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala @@ -0,0 +1,30 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast + +/** + * An interface for all the broadcast implementations in Spark (to allow + * multiple broadcast implementations). SparkContext uses a user-specified + * BroadcastFactory implementation to instantiate a particular broadcast for the + * entire Spark job. + */ +private[spark] trait BroadcastFactory { + def initialize(isDriver: Boolean): Unit + def newBroadcast[T](value: T, isLocal: Boolean, id: Long): Broadcast[T] + def stop(): Unit +} diff --git a/core/src/main/scala/spark/broadcast/HttpBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala index 7e30b8f7d2..9db26ae6de 100644 --- a/core/src/main/scala/spark/broadcast/HttpBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala @@ -1,20 +1,36 @@ -package spark.broadcast - -import com.ning.compress.lzf.{LZFInputStream, LZFOutputStream} - -import java.io._ -import java.net._ -import java.util.UUID +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast + +import java.io.{File, FileOutputStream, ObjectInputStream, OutputStream} +import java.net.URL import it.unimi.dsi.fastutil.io.FastBufferedInputStream import it.unimi.dsi.fastutil.io.FastBufferedOutputStream -import spark._ -import spark.storage.StorageLevel -import util.{MetadataCleaner, TimeStampedHashSet} +import org.apache.spark.{HttpServer, Logging, SparkEnv} +import org.apache.spark.io.CompressionCodec +import org.apache.spark.storage.StorageLevel +import org.apache.spark.util.{Utils, MetadataCleaner, TimeStampedHashSet} + private[spark] class HttpBroadcast[T](@transient var value_ : T, isLocal: Boolean, id: Long) -extends Broadcast[T](id) with Logging with Serializable { + extends Broadcast[T](id) with Logging with Serializable { def value = value_ @@ -68,6 +84,7 @@ private object HttpBroadcast extends Logging { private val files = new TimeStampedHashSet[String] private val cleaner = new MetadataCleaner("HttpBroadcast", cleanup) + private lazy val compressionCodec = CompressionCodec.createCodec() def initialize(isDriver: Boolean) { synchronized { @@ -105,10 +122,12 @@ private object HttpBroadcast extends Logging { def write(id: Long, value: Any) { val file = new File(broadcastDir, "broadcast-" + id) - val out: OutputStream = if (compress) { - new LZFOutputStream(new FileOutputStream(file)) // Does its own buffering - } else { - new FastBufferedOutputStream(new FileOutputStream(file), bufferSize) + val out: OutputStream = { + if (compress) { + compressionCodec.compressedOutputStream(new FileOutputStream(file)) + } else { + new FastBufferedOutputStream(new FileOutputStream(file), bufferSize) + } } val ser = SparkEnv.get.serializer.newInstance() val serOut = ser.serializeStream(out) @@ -119,10 +138,12 @@ private object HttpBroadcast extends Logging { def read[T](id: Long): T = { val url = serverUri + "/broadcast-" + id - var in = if (compress) { - new LZFInputStream(new URL(url).openStream()) // Does its own buffering - } else { - new FastBufferedInputStream(new URL(url).openStream(), bufferSize) + val in = { + if (compress) { + compressionCodec.compressedInputStream(new URL(url).openStream()) + } else { + new FastBufferedInputStream(new URL(url).openStream(), bufferSize) + } } val ser = SparkEnv.get.serializer.newInstance() val serIn = ser.deserializeStream(in) diff --git a/core/src/main/scala/spark/broadcast/MultiTracker.scala b/core/src/main/scala/org/apache/spark/broadcast/MultiTracker.scala index 3fd77af73f..21ec94659e 100644 --- a/core/src/main/scala/spark/broadcast/MultiTracker.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/MultiTracker.scala @@ -1,4 +1,21 @@ -package spark.broadcast +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast import java.io._ import java.net._ @@ -6,7 +23,8 @@ import java.util.Random import scala.collection.mutable.Map -import spark._ +import org.apache.spark._ +import org.apache.spark.util.Utils private object MultiTracker extends Logging { diff --git a/core/src/main/scala/spark/broadcast/SourceInfo.scala b/core/src/main/scala/org/apache/spark/broadcast/SourceInfo.scala index c79bb93c38..baa1fd6da4 100644 --- a/core/src/main/scala/spark/broadcast/SourceInfo.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/SourceInfo.scala @@ -1,8 +1,25 @@ -package spark.broadcast +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast import java.util.BitSet -import spark._ +import org.apache.spark._ /** * Used to keep and pass around information of peers involved in a broadcast diff --git a/core/src/main/scala/spark/broadcast/TreeBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/TreeBroadcast.scala index c55c476117..80c97ca073 100644 --- a/core/src/main/scala/spark/broadcast/TreeBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/TreeBroadcast.scala @@ -1,4 +1,21 @@ -package spark.broadcast +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.broadcast import java.io._ import java.net._ @@ -7,8 +24,9 @@ import java.util.{Comparator, Random, UUID} import scala.collection.mutable.{ListBuffer, Map, Set} import scala.math -import spark._ -import spark.storage.StorageLevel +import org.apache.spark._ +import org.apache.spark.storage.StorageLevel +import org.apache.spark.util.Utils private[spark] class TreeBroadcast[T](@transient var value_ : T, isLocal: Boolean, id: Long) extends Broadcast[T](id) with Logging with Serializable { diff --git a/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala new file mode 100644 index 0000000000..19d393a0db --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +private[spark] class ApplicationDescription( + val name: String, + val maxCores: Int, /* Integer.MAX_VALUE denotes an unlimited number of cores */ + val memoryPerSlave: Int, + val command: Command, + val sparkHome: String, + val appUiUrl: String) + extends Serializable { + + val user = System.getProperty("user.name", "<unknown>") + + override def toString: String = "ApplicationDescription(" + name + ")" +} diff --git a/core/src/main/scala/org/apache/spark/deploy/Command.scala b/core/src/main/scala/org/apache/spark/deploy/Command.scala new file mode 100644 index 0000000000..fa8af9a646 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/Command.scala @@ -0,0 +1,26 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +import scala.collection.Map + +private[spark] case class Command( + mainClass: String, + arguments: Seq[String], + environment: Map[String, String]) { +} diff --git a/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala b/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala new file mode 100644 index 0000000000..1cfff5e565 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala @@ -0,0 +1,134 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +import scala.collection.immutable.List + +import org.apache.spark.deploy.ExecutorState.ExecutorState +import org.apache.spark.deploy.master.{WorkerInfo, ApplicationInfo} +import org.apache.spark.deploy.worker.ExecutorRunner +import org.apache.spark.util.Utils + + +private[deploy] sealed trait DeployMessage extends Serializable + +private[deploy] object DeployMessages { + + // Worker to Master + + case class RegisterWorker( + id: String, + host: String, + port: Int, + cores: Int, + memory: Int, + webUiPort: Int, + publicAddress: String) + extends DeployMessage { + Utils.checkHost(host, "Required hostname") + assert (port > 0) + } + + case class ExecutorStateChanged( + appId: String, + execId: Int, + state: ExecutorState, + message: Option[String], + exitStatus: Option[Int]) + extends DeployMessage + + case class Heartbeat(workerId: String) extends DeployMessage + + // Master to Worker + + case class RegisteredWorker(masterWebUiUrl: String) extends DeployMessage + + case class RegisterWorkerFailed(message: String) extends DeployMessage + + case class KillExecutor(appId: String, execId: Int) extends DeployMessage + + case class LaunchExecutor( + appId: String, + execId: Int, + appDesc: ApplicationDescription, + cores: Int, + memory: Int, + sparkHome: String) + extends DeployMessage + + // Client to Master + + case class RegisterApplication(appDescription: ApplicationDescription) + extends DeployMessage + + // Master to Client + + case class RegisteredApplication(appId: String) extends DeployMessage + + // TODO(matei): replace hostPort with host + case class ExecutorAdded(id: Int, workerId: String, hostPort: String, cores: Int, memory: Int) { + Utils.checkHostPort(hostPort, "Required hostport") + } + + case class ExecutorUpdated(id: Int, state: ExecutorState, message: Option[String], + exitStatus: Option[Int]) + + case class ApplicationRemoved(message: String) + + // Internal message in Client + + case object StopClient + + // MasterWebUI To Master + + case object RequestMasterState + + // Master to MasterWebUI + + case class MasterStateResponse(host: String, port: Int, workers: Array[WorkerInfo], + activeApps: Array[ApplicationInfo], completedApps: Array[ApplicationInfo]) { + + Utils.checkHost(host, "Required hostname") + assert (port > 0) + + def uri = "spark://" + host + ":" + port + } + + // WorkerWebUI to Worker + + case object RequestWorkerState + + // Worker to WorkerWebUI + + case class WorkerStateResponse(host: String, port: Int, workerId: String, + executors: List[ExecutorRunner], finishedExecutors: List[ExecutorRunner], masterUrl: String, + cores: Int, memory: Int, coresUsed: Int, memoryUsed: Int, masterWebUiUrl: String) { + + Utils.checkHost(host, "Required hostname") + assert (port > 0) + } + + // Actor System to Master + + case object CheckForWorkerTimeOut + + case object RequestWebUIPort + + case class WebUIPortResponse(webUIBoundPort: Int) + +} diff --git a/core/src/main/scala/org/apache/spark/deploy/ExecutorState.scala b/core/src/main/scala/org/apache/spark/deploy/ExecutorState.scala new file mode 100644 index 0000000000..fcfea96ad6 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/ExecutorState.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +private[spark] object ExecutorState + extends Enumeration("LAUNCHING", "LOADING", "RUNNING", "KILLED", "FAILED", "LOST") { + + val LAUNCHING, LOADING, RUNNING, KILLED, FAILED, LOST = Value + + type ExecutorState = Value + + def isFinished(state: ExecutorState): Boolean = Seq(KILLED, FAILED, LOST).contains(state) +} diff --git a/core/src/main/scala/spark/deploy/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala index 607d34d111..a6be8efef1 100644 --- a/core/src/main/scala/spark/deploy/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala @@ -1,8 +1,28 @@ -package spark.deploy +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy -import master.{ApplicationInfo, WorkerInfo} import net.liftweb.json.JsonDSL._ -import worker.ExecutorRunner + +import org.apache.spark.deploy.DeployMessages.{MasterStateResponse, WorkerStateResponse} +import org.apache.spark.deploy.master.{ApplicationInfo, WorkerInfo} +import org.apache.spark.deploy.worker.ExecutorRunner + private[spark] object JsonProtocol { def writeWorkerInfo(obj: WorkerInfo) = { @@ -13,7 +33,8 @@ private[spark] object JsonProtocol { ("cores" -> obj.cores) ~ ("coresused" -> obj.coresUsed) ~ ("memory" -> obj.memory) ~ - ("memoryused" -> obj.memoryUsed) + ("memoryused" -> obj.memoryUsed) ~ + ("state" -> obj.state.toString) } def writeApplicationInfo(obj: ApplicationInfo) = { @@ -40,7 +61,7 @@ private[spark] object JsonProtocol { ("appdesc" -> writeApplicationDescription(obj.appDesc)) } - def writeMasterState(obj: MasterState) = { + def writeMasterState(obj: MasterStateResponse) = { ("url" -> ("spark://" + obj.uri)) ~ ("workers" -> obj.workers.toList.map(writeWorkerInfo)) ~ ("cores" -> obj.workers.map(_.cores).sum) ~ @@ -51,7 +72,7 @@ private[spark] object JsonProtocol { ("completedapps" -> obj.completedApps.toList.map(writeApplicationInfo)) } - def writeWorkerState(obj: WorkerState) = { + def writeWorkerState(obj: WorkerStateResponse) = { ("id" -> obj.workerId) ~ ("masterurl" -> obj.masterUrl) ~ ("masterwebuiurl" -> obj.masterWebUiUrl) ~ diff --git a/core/src/main/scala/spark/deploy/LocalSparkCluster.scala b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala index 494b1cc6f0..6a7d5a85ba 100644 --- a/core/src/main/scala/spark/deploy/LocalSparkCluster.scala +++ b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala @@ -1,11 +1,28 @@ -package spark.deploy +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy import akka.actor.{ActorRef, Props, Actor, ActorSystem, Terminated} -import spark.deploy.worker.Worker -import spark.deploy.master.Master -import spark.util.AkkaUtils -import spark.{Logging, Utils} +import org.apache.spark.deploy.worker.Worker +import org.apache.spark.deploy.master.Master +import org.apache.spark.util.{Utils, AkkaUtils} +import org.apache.spark.{Logging} import scala.collection.mutable.ArrayBuffer @@ -26,7 +43,7 @@ class LocalSparkCluster(numWorkers: Int, coresPerWorker: Int, memoryPerWorker: I logInfo("Starting a local Spark cluster with " + numWorkers + " workers.") /* Start the Master */ - val (masterSystem, masterPort) = Master.startSystemAndActor(localHostname, 0, 0) + val (masterSystem, masterPort, _) = Master.startSystemAndActor(localHostname, 0, 0) masterActorSystems += masterSystem val masterUrl = "spark://" + localHostname + ":" + masterPort diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala new file mode 100644 index 0000000000..0a5f4c368f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.mapred.JobConf + + +/** + * Contains util methods to interact with Hadoop from spark. + */ +class SparkHadoopUtil { + + // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems + def newConfiguration(): Configuration = new Configuration() + + // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster + def addCredentials(conf: JobConf) {} + + def isYarnMode(): Boolean = { false } + +} diff --git a/core/src/main/scala/org/apache/spark/deploy/WebUI.scala b/core/src/main/scala/org/apache/spark/deploy/WebUI.scala new file mode 100644 index 0000000000..ae258b58b9 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/WebUI.scala @@ -0,0 +1,47 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +import java.text.SimpleDateFormat +import java.util.Date + +/** + * Utilities used throughout the web UI. + */ +private[spark] object DeployWebUI { + val DATE_FORMAT = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss") + + def formatDate(date: Date): String = DATE_FORMAT.format(date) + + def formatDate(timestamp: Long): String = DATE_FORMAT.format(new Date(timestamp)) + + def formatDuration(milliseconds: Long): String = { + val seconds = milliseconds.toDouble / 1000 + if (seconds < 60) { + return "%.0f s".format(seconds) + } + val minutes = seconds / 60 + if (minutes < 10) { + return "%.1f min".format(minutes) + } else if (minutes < 60) { + return "%.0f min".format(minutes) + } + val hours = minutes / 60 + return "%.1f h".format(hours) + } +} diff --git a/core/src/main/scala/spark/deploy/client/Client.scala b/core/src/main/scala/org/apache/spark/deploy/client/Client.scala index 690bb20e50..14a90934f6 100644 --- a/core/src/main/scala/spark/deploy/client/Client.scala +++ b/core/src/main/scala/org/apache/spark/deploy/client/Client.scala @@ -1,19 +1,40 @@ -package spark.deploy.client +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.client + +import java.util.concurrent.TimeoutException -import spark.deploy._ -import akka.actor._ -import akka.pattern.ask import scala.concurrent.duration._ +import scala.concurrent.Await +import akka.actor._ +import akka.actor.Terminated import akka.pattern.AskTimeoutException -import spark.{SparkException, Logging} +import akka.pattern.ask +import akka.remote.RemoteClientDisconnected import akka.remote.RemoteClientLifeCycleEvent import akka.remote.RemoteClientShutdown -import spark.deploy.RegisterApplication -import spark.deploy.master.Master -import akka.remote.RemoteClientDisconnected -import akka.actor.Terminated -import scala.concurrent.Await + +import org.apache.spark.Logging +import org.apache.spark.deploy.{ApplicationDescription, ExecutorState} +import org.apache.spark.deploy.DeployMessages._ +import org.apache.spark.deploy.master.Master + /** * The main class used to talk to a Spark deploy cluster. Takes a master URL, an app description, @@ -117,7 +138,8 @@ private[spark] class Client( val future = actor.ask(StopClient)(timeout) Await.result(future, timeout) } catch { - case e: AskTimeoutException => // Ignore it, maybe master went away + case e: TimeoutException => + logInfo("Stop request to Master timed out; it may already be shut down.") } actor = null } diff --git a/core/src/main/scala/org/apache/spark/deploy/client/ClientListener.scala b/core/src/main/scala/org/apache/spark/deploy/client/ClientListener.scala new file mode 100644 index 0000000000..4605368c11 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/client/ClientListener.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.client + +/** + * Callbacks invoked by deploy client when various events happen. There are currently four events: + * connecting to the cluster, disconnecting, being given an executor, and having an executor + * removed (either due to failure or due to revocation). + * + * Users of this API should *not* block inside the callback methods. + */ +private[spark] trait ClientListener { + def connected(appId: String): Unit + + def disconnected(): Unit + + def executorAdded(fullId: String, workerId: String, hostPort: String, cores: Int, memory: Int): Unit + + def executorRemoved(fullId: String, message: String, exitStatus: Option[Int]): Unit +} diff --git a/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala b/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala new file mode 100644 index 0000000000..d5e9a0e095 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala @@ -0,0 +1,51 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.client + +import org.apache.spark.util.{Utils, AkkaUtils} +import org.apache.spark.{Logging} +import org.apache.spark.deploy.{Command, ApplicationDescription} + +private[spark] object TestClient { + + class TestListener extends ClientListener with Logging { + def connected(id: String) { + logInfo("Connected to master, got app ID " + id) + } + + def disconnected() { + logInfo("Disconnected from master") + System.exit(0) + } + + def executorAdded(id: String, workerId: String, hostPort: String, cores: Int, memory: Int) {} + + def executorRemoved(id: String, message: String, exitStatus: Option[Int]) {} + } + + def main(args: Array[String]) { + val url = args(0) + val (actorSystem, port) = AkkaUtils.createActorSystem("spark", Utils.localIpAddress, 0) + val desc = new ApplicationDescription( + "TestClient", 1, 512, Command("spark.deploy.client.TestExecutor", Seq(), Map()), "dummy-spark-home", "ignored") + val listener = new TestListener + val client = new Client(actorSystem, url, desc, listener) + client.start() + actorSystem.awaitTermination() + } +} diff --git a/core/src/main/scala/org/apache/spark/deploy/client/TestExecutor.scala b/core/src/main/scala/org/apache/spark/deploy/client/TestExecutor.scala new file mode 100644 index 0000000000..c5ac45c673 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/client/TestExecutor.scala @@ -0,0 +1,27 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.client + +private[spark] object TestExecutor { + def main(args: Array[String]) { + println("Hello world!") + while (true) { + Thread.sleep(1000) + } + } +} diff --git a/core/src/main/scala/spark/deploy/master/ApplicationInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala index 785c16e2be..bd5327627a 100644 --- a/core/src/main/scala/spark/deploy/master/ApplicationInfo.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala @@ -1,6 +1,23 @@ -package spark.deploy.master +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import spark.deploy.ApplicationDescription +package org.apache.spark.deploy.master + +import org.apache.spark.deploy.ApplicationDescription import java.util.Date import akka.actor.ActorRef import scala.collection.mutable @@ -17,6 +34,7 @@ private[spark] class ApplicationInfo( var executors = new mutable.HashMap[Int, ExecutorInfo] var coresGranted = 0 var endTime = -1L + val appSource = new ApplicationSource(this) private var nextExecutorId = 0 @@ -34,8 +52,10 @@ private[spark] class ApplicationInfo( } def removeExecutor(exec: ExecutorInfo) { - executors -= exec.id - coresGranted -= exec.cores + if (executors.contains(exec.id)) { + executors -= exec.id + coresGranted -= exec.cores + } } def coresLeft: Int = desc.maxCores - coresGranted diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ApplicationSource.scala b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationSource.scala new file mode 100644 index 0000000000..5a24042e14 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationSource.scala @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master + +import com.codahale.metrics.{Gauge, MetricRegistry} + +import org.apache.spark.metrics.source.Source + +class ApplicationSource(val application: ApplicationInfo) extends Source { + val metricRegistry = new MetricRegistry() + val sourceName = "%s.%s.%s".format("application", application.desc.name, + System.currentTimeMillis()) + + metricRegistry.register(MetricRegistry.name("status"), new Gauge[String] { + override def getValue: String = application.state.toString + }) + + metricRegistry.register(MetricRegistry.name("runtime_ms"), new Gauge[Long] { + override def getValue: Long = application.duration + }) + + metricRegistry.register(MetricRegistry.name("cores", "number"), new Gauge[Int] { + override def getValue: Int = application.coresGranted + }) + +} diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ApplicationState.scala b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationState.scala new file mode 100644 index 0000000000..7e804223cf --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationState.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master + +private[spark] object ApplicationState + extends Enumeration("WAITING", "RUNNING", "FINISHED", "FAILED") { + + type ApplicationState = Value + + val WAITING, RUNNING, FINISHED, FAILED = Value + + val MAX_NUM_RETRY = 10 +} diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala new file mode 100644 index 0000000000..cf384a985e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master + +import org.apache.spark.deploy.ExecutorState + +private[spark] class ExecutorInfo( + val id: Int, + val application: ApplicationInfo, + val worker: WorkerInfo, + val cores: Int, + val memory: Int) { + + var state = ExecutorState.LAUNCHING + + def fullId: String = application.id + "/" + id +} diff --git a/core/src/main/scala/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 315a00f244..2efd16bca0 100644 --- a/core/src/main/scala/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -1,25 +1,49 @@ -package spark.deploy.master +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master -import akka.actor._ -import akka.actor.Terminated -import akka.remote.{RemoteClientLifeCycleEvent, RemoteClientDisconnected, RemoteClientShutdown} -import scala.concurrent.duration._ - -import java.text.SimpleDateFormat import java.util.Date +import java.text.SimpleDateFormat import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} +import scala.concurrent.Await +import scala.concurrent.duration._ + +import akka.actor._ +import akka.actor.Terminated +import akka.pattern.ask +import akka.remote.{RemoteClientLifeCycleEvent, RemoteClientDisconnected, RemoteClientShutdown} -import spark.deploy._ -import spark.{Logging, SparkException, Utils} -import spark.util.AkkaUtils -import ui.MasterWebUI +import org.apache.spark.{Logging, SparkException} +import org.apache.spark.deploy.{ApplicationDescription, ExecutorState} +import org.apache.spark.deploy.DeployMessages._ +import org.apache.spark.deploy.master.ui.MasterWebUI +import org.apache.spark.metrics.MetricsSystem +import org.apache.spark.util.{Utils, AkkaUtils} +import akka.util.Timeout private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Actor with Logging { val DATE_FORMAT = new SimpleDateFormat("yyyyMMddHHmmss") // For application IDs val WORKER_TIMEOUT = System.getProperty("spark.worker.timeout", "60").toLong * 1000 - + val RETAINED_APPLICATIONS = System.getProperty("spark.deploy.retainedApplications", "200").toInt + val REAPER_ITERATIONS = System.getProperty("spark.dead.worker.persistence", "15").toInt + var nextAppNumber = 0 val workers = new HashSet[WorkerInfo] val idToWorker = new HashMap[String, WorkerInfo] @@ -36,10 +60,14 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act var firstApp: Option[ApplicationInfo] = None - val webUi = new MasterWebUI(self) - Utils.checkHost(host, "Expected hostname") + val masterMetricsSystem = MetricsSystem.createMetricsSystem("master") + val applicationMetricsSystem = MetricsSystem.createMetricsSystem("applications") + val masterSource = new MasterSource(this) + + val webUi = new MasterWebUI(this, webUiPort) + val masterPublicAddress = { val envVar = System.getenv("SPARK_PUBLIC_DNS") if (envVar != null) envVar else host @@ -56,17 +84,23 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act context.system.eventStream.subscribe(self, classOf[RemoteClientLifeCycleEvent]) webUi.start() import context.dispatcher - context.system.scheduler.schedule(0 millis, WORKER_TIMEOUT millis)(timeOutDeadWorkers()) + context.system.scheduler.schedule(0 millis, WORKER_TIMEOUT millis, self, CheckForWorkerTimeOut) + + masterMetricsSystem.registerSource(masterSource) + masterMetricsSystem.start() + applicationMetricsSystem.start() } override def postStop() { webUi.stop() + masterMetricsSystem.stop() + applicationMetricsSystem.stop() } override def receive = { case RegisterWorker(id, host, workerPort, cores, memory, worker_webUiPort, publicAddress) => { logInfo("Registering worker %s:%d with %d cores, %s RAM".format( - host, workerPort, cores, Utils.memoryMegabytesToString(memory))) + host, workerPort, cores, Utils.megabytesToString(memory))) if (idToWorker.contains(id)) { sender ! RegisterWorkerFailed("Duplicate worker ID") } else { @@ -144,7 +178,15 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act } case RequestMasterState => { - sender ! MasterState(host, port, workers.toArray, apps.toArray, completedApps.toArray) + sender ! MasterStateResponse(host, port, workers.toArray, apps.toArray, completedApps.toArray) + } + + case CheckForWorkerTimeOut => { + timeOutDeadWorkers() + } + + case RequestWebUIPort => { + sender ! WebUIPortResponse(webUi.boundPort.getOrElse(-1)) } } @@ -209,20 +251,27 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act def launchExecutor(worker: WorkerInfo, exec: ExecutorInfo, sparkHome: String) { logInfo("Launching executor " + exec.fullId + " on worker " + worker.id) worker.addExecutor(exec) - worker.actor ! LaunchExecutor(exec.application.id, exec.id, exec.application.desc, exec.cores, exec.memory, sparkHome) - exec.application.driver ! ExecutorAdded(exec.id, worker.id, worker.hostPort, exec.cores, exec.memory) + worker.actor ! LaunchExecutor( + exec.application.id, exec.id, exec.application.desc, exec.cores, exec.memory, sparkHome) + exec.application.driver ! ExecutorAdded( + exec.id, worker.id, worker.hostPort, exec.cores, exec.memory) } def addWorker(id: String, host: String, port: Int, cores: Int, memory: Int, webUiPort: Int, publicAddress: String): WorkerInfo = { - // There may be one or more refs to dead workers on this same node (w/ different ID's), remove them. - workers.filter(w => (w.host == host && w.port == port) && (w.state == WorkerState.DEAD)).foreach(workers -= _) + // There may be one or more refs to dead workers on this same node (w/ different ID's), + // remove them. + workers.filter { w => + (w.host == host && w.port == port) && (w.state == WorkerState.DEAD) + }.foreach { w => + workers -= w + } val worker = new WorkerInfo(id, host, port, cores, memory, sender, webUiPort, publicAddress) workers += worker idToWorker(worker.id) = worker actorToWorker(sender) = worker addressToWorker(sender.path.address) = worker - return worker + worker } def removeWorker(worker: WorkerInfo) { @@ -233,7 +282,8 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act addressToWorker -= worker.actor.path.address for (exec <- worker.executors.values) { logInfo("Telling app of lost executor: " + exec.id) - exec.application.driver ! ExecutorUpdated(exec.id, ExecutorState.LOST, Some("worker lost"), None) + exec.application.driver ! ExecutorUpdated( + exec.id, ExecutorState.LOST, Some("worker lost"), None) exec.application.removeExecutor(exec) } } @@ -242,6 +292,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act val now = System.currentTimeMillis() val date = new Date(now) val app = new ApplicationInfo(now, newApplicationId(date), desc, date, driver, desc.appUiUrl) + applicationMetricsSystem.registerSource(app.appSource) apps += app idToApp(app.id) = app actorToApp(driver) = app @@ -253,7 +304,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act if (workersAlive.size > 0 && !workersAlive.exists(_.memoryFree >= desc.memoryPerSlave)) { logWarning("Could not find any workers with enough memory for " + firstApp.get.id) } - return app + app } def finishApplication(app: ApplicationInfo) { @@ -267,7 +318,14 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act idToApp -= app.id actorToApp -= app.driver addressToApp -= app.driver.path.address - completedApps += app // Remember it in our history + if (completedApps.size >= RETAINED_APPLICATIONS) { + val toRemove = math.max(RETAINED_APPLICATIONS / 10, 1) + completedApps.take(toRemove).foreach( a => { + applicationMetricsSystem.removeSource(a.appSource) + }) + completedApps.trimStart(toRemove) + } + completedApps += app // Remember it in our history waitingApps -= app for (exec <- app.executors.values) { exec.worker.removeExecutor(exec) @@ -292,12 +350,17 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act /** Check for, and remove, any timed-out workers */ def timeOutDeadWorkers() { // Copy the workers into an array so we don't modify the hashset while iterating through it - val expirationTime = System.currentTimeMillis() - WORKER_TIMEOUT - val toRemove = workers.filter(_.lastHeartbeat < expirationTime).toArray + val currentTime = System.currentTimeMillis() + val toRemove = workers.filter(_.lastHeartbeat < currentTime - WORKER_TIMEOUT).toArray for (worker <- toRemove) { - logWarning("Removing %s because we got no heartbeat in %d seconds".format( - worker.id, WORKER_TIMEOUT)) - removeWorker(worker) + if (worker.state != WorkerState.DEAD) { + logWarning("Removing %s because we got no heartbeat in %d seconds".format( + worker.id, WORKER_TIMEOUT/1000)) + removeWorker(worker) + } else { + if (worker.lastHeartbeat < currentTime - ((REAPER_ITERATIONS + 1) * WORKER_TIMEOUT)) + workers -= worker // we've seen this DEAD worker in the UI, etc. for long enough; cull it + } } } } @@ -309,7 +372,7 @@ private[spark] object Master { def main(argStrings: Array[String]) { val args = new MasterArguments(argStrings) - val (actorSystem, _) = startSystemAndActor(args.host, args.port, args.webUiPort) + val (actorSystem, _, _) = startSystemAndActor(args.host, args.port, args.webUiPort) actorSystem.awaitTermination() } @@ -323,9 +386,14 @@ private[spark] object Master { } } - def startSystemAndActor(host: String, port: Int, webUiPort: Int): (ActorSystem, Int) = { + def startSystemAndActor(host: String, port: Int, webUiPort: Int): (ActorSystem, Int, Int) = { val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port) val actor = actorSystem.actorOf(Props(new Master(host, boundPort, webUiPort)), name = actorName) - (actorSystem, boundPort) + val timeoutDuration = Duration.create( + System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds") + implicit val timeout = Timeout(timeoutDuration) + val respFuture = actor ? RequestWebUIPort // ask pattern + val resp = Await.result(respFuture, timeoutDuration).asInstanceOf[WebUIPortResponse] + (actorSystem, boundPort, resp.webUIBoundPort) } } diff --git a/core/src/main/scala/spark/deploy/master/MasterArguments.scala b/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala index 3d28ecabb4..9d89b455fb 100644 --- a/core/src/main/scala/spark/deploy/master/MasterArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala @@ -1,7 +1,23 @@ -package spark.deploy.master +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master -import spark.util.IntParam -import spark.Utils +import org.apache.spark.util.{Utils, IntParam} /** * Command-line parser for the master. @@ -21,7 +37,10 @@ private[spark] class MasterArguments(args: Array[String]) { if (System.getenv("SPARK_MASTER_WEBUI_PORT") != null) { webUiPort = System.getenv("SPARK_MASTER_WEBUI_PORT").toInt } - + if (System.getProperty("master.ui.port") != null) { + webUiPort = System.getProperty("master.ui.port").toInt + } + parse(args.toList) def parse(args: List[String]): Unit = args match { diff --git a/core/src/main/scala/org/apache/spark/deploy/master/MasterSource.scala b/core/src/main/scala/org/apache/spark/deploy/master/MasterSource.scala new file mode 100644 index 0000000000..23d1cb77da --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/MasterSource.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master + +import com.codahale.metrics.{Gauge, MetricRegistry} + +import org.apache.spark.metrics.source.Source + +private[spark] class MasterSource(val master: Master) extends Source { + val metricRegistry = new MetricRegistry() + val sourceName = "master" + + // Gauge for worker numbers in cluster + metricRegistry.register(MetricRegistry.name("workers","number"), new Gauge[Int] { + override def getValue: Int = master.workers.size + }) + + // Gauge for application numbers in cluster + metricRegistry.register(MetricRegistry.name("apps", "number"), new Gauge[Int] { + override def getValue: Int = master.apps.size + }) + + // Gauge for waiting application numbers in cluster + metricRegistry.register(MetricRegistry.name("waitingApps", "number"), new Gauge[Int] { + override def getValue: Int = master.waitingApps.size + }) +} diff --git a/core/src/main/scala/spark/deploy/master/WorkerInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala index 0c08c5f417..6219f11f2a 100644 --- a/core/src/main/scala/spark/deploy/master/WorkerInfo.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala @@ -1,8 +1,25 @@ -package spark.deploy.master +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master import akka.actor.ActorRef import scala.collection.mutable -import spark.Utils +import org.apache.spark.util.Utils private[spark] class WorkerInfo( val id: String, diff --git a/core/src/main/scala/org/apache/spark/deploy/master/WorkerState.scala b/core/src/main/scala/org/apache/spark/deploy/master/WorkerState.scala new file mode 100644 index 0000000000..b5ee6dca79 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/WorkerState.scala @@ -0,0 +1,24 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master + +private[spark] object WorkerState extends Enumeration("ALIVE", "DEAD", "DECOMMISSIONED") { + type WorkerState = Value + + val ALIVE, DEAD, DECOMMISSIONED = Value +} diff --git a/core/src/main/scala/spark/deploy/master/ui/ApplicationPage.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala index 88a3db223a..3b983c19eb 100644 --- a/core/src/main/scala/spark/deploy/master/ui/ApplicationPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala @@ -1,4 +1,23 @@ -package spark.deploy.master.ui +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master.ui + +import scala.xml.Node import akka.pattern.ask @@ -9,20 +28,20 @@ import javax.servlet.http.HttpServletRequest import net.liftweb.json.JsonAST.JValue -import scala.xml.Node - -import spark.deploy.{RequestMasterState, JsonProtocol, MasterState} -import spark.deploy.master.ExecutorInfo -import spark.ui.UIUtils +import org.apache.spark.deploy.DeployMessages.{MasterStateResponse, RequestMasterState} +import org.apache.spark.deploy.JsonProtocol +import org.apache.spark.deploy.master.ExecutorInfo +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils private[spark] class ApplicationPage(parent: MasterWebUI) { - val master = parent.master + val master = parent.masterActorRef implicit val timeout = parent.timeout /** Executor details for a particular application */ def renderJson(request: HttpServletRequest): JValue = { val appId = request.getParameter("appId") - val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterState] + val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterStateResponse] val state = Await.result(stateFuture, 30 seconds) val app = state.activeApps.find(_.id == appId).getOrElse({ state.completedApps.find(_.id == appId).getOrElse(null) @@ -33,7 +52,7 @@ private[spark] class ApplicationPage(parent: MasterWebUI) { /** Executor details for a particular application */ def render(request: HttpServletRequest): Seq[Node] = { val appId = request.getParameter("appId") - val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterState] + val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterStateResponse] val state = Await.result(stateFuture, 30 seconds) val app = state.activeApps.find(_.id == appId).getOrElse({ state.completedApps.find(_.id == appId).getOrElse(null) @@ -44,24 +63,26 @@ private[spark] class ApplicationPage(parent: MasterWebUI) { val executorTable = UIUtils.listingTable(executorHeaders, executorRow, executors) val content = - <hr /> - <div class="row"> + <div class="row-fluid"> <div class="span12"> <ul class="unstyled"> <li><strong>ID:</strong> {app.id}</li> - <li><strong>Description:</strong> {app.desc.name}</li> + <li><strong>Name:</strong> {app.desc.name}</li> <li><strong>User:</strong> {app.desc.user}</li> <li><strong>Cores:</strong> { if (app.desc.maxCores == Integer.MAX_VALUE) { - "Unlimited %s granted".format(app.coresGranted) + "Unlimited (%s granted)".format(app.coresGranted) } else { "%s (%s granted, %s left)".format( app.desc.maxCores, app.coresGranted, app.coresLeft) } } </li> - <li><strong>Memory per Slave:</strong> {app.desc.memoryPerSlave}</li> + <li> + <strong>Executor Memory:</strong> + {Utils.megabytesToString(app.desc.memoryPerSlave)} + </li> <li><strong>Submit Date:</strong> {app.submitDate}</li> <li><strong>State:</strong> {app.state}</li> <li><strong><a href={app.appUiUrl}>Application Detail UI</a></strong></li> @@ -69,16 +90,13 @@ private[spark] class ApplicationPage(parent: MasterWebUI) { </div> </div> - <hr/> - - <div class="row"> <!-- Executors --> + <div class="row-fluid"> <!-- Executors --> <div class="span12"> - <h3> Executor Summary </h3> - <br/> + <h4> Executor Summary </h4> {executorTable} </div> </div>; - UIUtils.basicSparkPage(content, "Application Info: " + app.desc.name) + UIUtils.basicSparkPage(content, "Application: " + app.desc.name) } def executorRow(executor: ExecutorInfo): Seq[Node] = { diff --git a/core/src/main/scala/spark/deploy/master/ui/IndexPage.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/IndexPage.scala index 617e4021d5..65e7a14e7a 100644 --- a/core/src/main/scala/spark/deploy/master/ui/IndexPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/IndexPage.scala @@ -1,32 +1,59 @@ -package spark.deploy.master.ui +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master.ui + +import javax.servlet.http.HttpServletRequest + +import scala.xml.Node import scala.concurrent.Await import akka.pattern.ask import scala.concurrent.duration._ -import javax.servlet.http.HttpServletRequest - -import scala.xml.Node +import net.liftweb.json.JsonAST.JValue -import spark.deploy.{RequestMasterState, DeployWebUI, MasterState} -import spark.Utils -import spark.ui.UIUtils -import spark.deploy.master.{ApplicationInfo, WorkerInfo} +import org.apache.spark.deploy.DeployWebUI +import org.apache.spark.deploy.DeployMessages.{MasterStateResponse, RequestMasterState} +import org.apache.spark.deploy.JsonProtocol +import org.apache.spark.deploy.master.{ApplicationInfo, WorkerInfo} +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils private[spark] class IndexPage(parent: MasterWebUI) { - val master = parent.master + val master = parent.masterActorRef implicit val timeout = parent.timeout + def renderJson(request: HttpServletRequest): JValue = { + val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterStateResponse] + val state = Await.result(stateFuture, 30 seconds) + JsonProtocol.writeMasterState(state) + } + /** Index view listing applications and executors */ def render(request: HttpServletRequest): Seq[Node] = { - val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterState] + val stateFuture = (master ? RequestMasterState)(timeout).mapTo[MasterStateResponse] val state = Await.result(stateFuture, 30 seconds) val workerHeaders = Seq("Id", "Address", "State", "Cores", "Memory") val workers = state.workers.sortBy(_.id) val workerTable = UIUtils.listingTable(workerHeaders, workerRow, workers) - val appHeaders = Seq("ID", "Description", "Cores", "Memory per Node", "Submit Time", "User", + val appHeaders = Seq("ID", "Name", "Cores", "Memory per Node", "Submitted Time", "User", "State", "Duration") val activeApps = state.activeApps.sortBy(_.startTime).reverse val activeAppsTable = UIUtils.listingTable(appHeaders, appRow, activeApps) @@ -34,8 +61,7 @@ private[spark] class IndexPage(parent: MasterWebUI) { val completedAppsTable = UIUtils.listingTable(appHeaders, appRow, completedApps) val content = - <hr /> - <div class="row"> + <div class="row-fluid"> <div class="span12"> <ul class="unstyled"> <li><strong>URL:</strong> {state.uri}</li> @@ -43,8 +69,8 @@ private[spark] class IndexPage(parent: MasterWebUI) { <li><strong>Cores:</strong> {state.workers.map(_.cores).sum} Total, {state.workers.map(_.coresUsed).sum} Used</li> <li><strong>Memory:</strong> - {Utils.memoryMegabytesToString(state.workers.map(_.memory).sum)} Total, - {Utils.memoryMegabytesToString(state.workers.map(_.memoryUsed).sum)} Used</li> + {Utils.megabytesToString(state.workers.map(_.memory).sum)} Total, + {Utils.megabytesToString(state.workers.map(_.memoryUsed).sum)} Used</li> <li><strong>Applications:</strong> {state.activeApps.size} Running, {state.completedApps.size} Completed </li> @@ -52,34 +78,28 @@ private[spark] class IndexPage(parent: MasterWebUI) { </div> </div> - <div class="row"> + <div class="row-fluid"> <div class="span12"> - <h3> Workers </h3> - <br/> + <h4> Workers </h4> {workerTable} </div> </div> - <hr/> - - <div class="row"> + <div class="row-fluid"> <div class="span12"> - <h3> Running Applications </h3> - <br/> + <h4> Running Applications </h4> + {activeAppsTable} </div> </div> - <hr/> - - <div class="row"> + <div class="row-fluid"> <div class="span12"> - <h3> Completed Applications </h3> - <br/> + <h4> Completed Applications </h4> {completedAppsTable} </div> </div>; - UIUtils.basicSparkPage(content, "Spark Master: " + state.uri) + UIUtils.basicSparkPage(content, "Spark Master at " + state.uri) } def workerRow(worker: WorkerInfo): Seq[Node] = { @@ -91,8 +111,8 @@ private[spark] class IndexPage(parent: MasterWebUI) { <td>{worker.state}</td> <td>{worker.cores} ({worker.coresUsed} Used)</td> <td sorttable_customkey={"%s.%s".format(worker.memory, worker.memoryUsed)}> - {Utils.memoryMegabytesToString(worker.memory)} - ({Utils.memoryMegabytesToString(worker.memoryUsed)} Used) + {Utils.megabytesToString(worker.memory)} + ({Utils.megabytesToString(worker.memoryUsed)} Used) </td> </tr> } @@ -103,12 +123,14 @@ private[spark] class IndexPage(parent: MasterWebUI) { <td> <a href={"app?appId=" + app.id}>{app.id}</a> </td> - <td>{app.desc.name}</td> + <td> + <a href={app.appUiUrl}>{app.desc.name}</a> + </td> <td> {app.coresGranted} </td> <td sorttable_customkey={app.desc.memoryPerSlave.toString}> - {Utils.memoryMegabytesToString(app.desc.memoryPerSlave)} + {Utils.megabytesToString(app.desc.memoryPerSlave)} </td> <td>{DeployWebUI.formatDate(app.submitDate)}</td> <td>{app.desc.user}</td> diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala new file mode 100644 index 0000000000..a211ce2b42 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala @@ -0,0 +1,81 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.master.ui + +import scala.concurrent.duration._ + +import javax.servlet.http.HttpServletRequest + +import org.eclipse.jetty.server.{Handler, Server} + +import org.apache.spark.{Logging} +import org.apache.spark.deploy.master.Master +import org.apache.spark.ui.JettyUtils +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.util.Utils + +/** + * Web UI server for the standalone master. + */ +private[spark] +class MasterWebUI(val master: Master, requestedPort: Int) extends Logging { + implicit val timeout = Duration.create( + System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds") + val host = Utils.localHostName() + val port = requestedPort + + val masterActorRef = master.self + + var server: Option[Server] = None + var boundPort: Option[Int] = None + + val applicationPage = new ApplicationPage(this) + val indexPage = new IndexPage(this) + + def start() { + try { + val (srv, bPort) = JettyUtils.startJettyServer("0.0.0.0", port, handlers) + server = Some(srv) + boundPort = Some(bPort) + logInfo("Started Master web UI at http://%s:%d".format(host, boundPort.get)) + } catch { + case e: Exception => + logError("Failed to create Master JettyUtils", e) + System.exit(1) + } + } + + val metricsHandlers = master.masterMetricsSystem.getServletHandlers ++ + master.applicationMetricsSystem.getServletHandlers + + val handlers = metricsHandlers ++ Array[(String, Handler)]( + ("/static", createStaticHandler(MasterWebUI.STATIC_RESOURCE_DIR)), + ("/app/json", (request: HttpServletRequest) => applicationPage.renderJson(request)), + ("/app", (request: HttpServletRequest) => applicationPage.render(request)), + ("/json", (request: HttpServletRequest) => indexPage.renderJson(request)), + ("*", (request: HttpServletRequest) => indexPage.render(request)) + ) + + def stop() { + server.foreach(_.stop()) + } +} + +private[spark] object MasterWebUI { + val STATIC_RESOURCE_DIR = "org/apache/spark/ui/static" +} diff --git a/core/src/main/scala/spark/deploy/worker/ExecutorRunner.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala index 5d3d54c65e..e3dc30eefc 100644 --- a/core/src/main/scala/spark/deploy/worker/ExecutorRunner.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala @@ -1,15 +1,34 @@ -package spark.deploy.worker +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker import java.io._ import java.lang.System.getenv -import spark.deploy.{ExecutorState, ExecutorStateChanged, ApplicationDescription} + import akka.actor.ActorRef -import spark.{Utils, Logging} -import java.net.{URI, URL} -import org.apache.hadoop.fs.{Path, FileSystem} -import org.apache.hadoop.conf.Configuration -import scala.Some -import spark.deploy.ExecutorStateChanged + +import com.google.common.base.Charsets +import com.google.common.io.Files + +import org.apache.spark.{Logging} +import org.apache.spark.deploy.{ExecutorState, ApplicationDescription} +import org.apache.spark.deploy.DeployMessages.ExecutorStateChanged +import org.apache.spark.util.Utils /** * Manages the execution of one executor process. @@ -22,18 +41,19 @@ private[spark] class ExecutorRunner( val memory: Int, val worker: ActorRef, val workerId: String, - val hostPort: String, + val host: String, val sparkHome: File, val workDir: File) extends Logging { - Utils.checkHostPort(hostPort, "Expected hostport") - val fullId = appId + "/" + execId var workerThread: Thread = null var process: Process = null var shutdownHook: Thread = null + private def getAppEnv(key: String): Option[String] = + appDesc.command.environment.get(key).orElse(Option(getenv(key))) + def start() { workerThread = new Thread("ExecutorRunner for " + fullId) { override def run() { fetchAndRunExecutor() } @@ -71,14 +91,14 @@ private[spark] class ExecutorRunner( /** Replace variables such as {{EXECUTOR_ID}} and {{CORES}} in a command argument passed to us */ def substituteVariables(argument: String): String = argument match { case "{{EXECUTOR_ID}}" => execId.toString - case "{{HOSTNAME}}" => Utils.parseHostPort(hostPort)._1 + case "{{HOSTNAME}}" => host case "{{CORES}}" => cores.toString case other => other } def buildCommandSeq(): Seq[String] = { val command = appDesc.command - val runner = Option(getenv("JAVA_HOME")).map(_ + "/bin/java").getOrElse("java") + val runner = getAppEnv("JAVA_HOME").map(_ + "/bin/java").getOrElse("java") // SPARK-698: do not call the run.cmd script, as process.destroy() // fails to kill a process tree on Windows Seq(runner) ++ buildJavaOpts() ++ Seq(command.mainClass) ++ @@ -90,10 +110,11 @@ private[spark] class ExecutorRunner( * the way the JAVA_OPTS are assembled there. */ def buildJavaOpts(): Seq[String] = { - val libraryOpts = Option(getenv("SPARK_LIBRARY_PATH")) + val libraryOpts = getAppEnv("SPARK_LIBRARY_PATH") .map(p => List("-Djava.library.path=" + p)) .getOrElse(Nil) - val userOpts = Option(getenv("SPARK_JAVA_OPTS")).map(Utils.splitCommandString).getOrElse(Nil) + val workerLocalOpts = Option(getenv("SPARK_JAVA_OPTS")).map(Utils.splitCommandString).getOrElse(Nil) + val userOpts = getAppEnv("SPARK_JAVA_OPTS").map(Utils.splitCommandString).getOrElse(Nil) val memoryOpts = Seq("-Xms" + memory + "M", "-Xmx" + memory + "M") // Figure out our classpath with the external compute-classpath script @@ -102,12 +123,12 @@ private[spark] class ExecutorRunner( Seq(sparkHome + "/bin/compute-classpath" + ext), extraEnvironment=appDesc.command.environment) - Seq("-cp", classPath) ++ libraryOpts ++ userOpts ++ memoryOpts + Seq("-cp", classPath) ++ libraryOpts ++ workerLocalOpts ++ userOpts ++ memoryOpts } /** Spawn a thread that will redirect a given stream to a file */ def redirectStream(in: InputStream, file: File) { - val out = new FileOutputStream(file) + val out = new FileOutputStream(file, true) new Thread("redirect output to " + file) { override def run() { try { @@ -133,6 +154,7 @@ private[spark] class ExecutorRunner( // Launch the process val command = buildCommandSeq() + logInfo("Launch command: " + command.mkString("\"", "\" \"", "\"")) val builder = new ProcessBuilder(command: _*).directory(executorDir) val env = builder.environment() for ((key, value) <- appDesc.command.environment) { @@ -143,9 +165,16 @@ private[spark] class ExecutorRunner( env.put("SPARK_LAUNCH_WITH_SCALA", "0") process = builder.start() + val header = "Spark Executor Command: %s\n%s\n\n".format( + command.mkString("\"", "\" \"", "\""), "=" * 40) + // Redirect its stdout and stderr to files - redirectStream(process.getInputStream, new File(executorDir, "stdout")) - redirectStream(process.getErrorStream, new File(executorDir, "stderr")) + val stdout = new File(executorDir, "stdout") + redirectStream(process.getInputStream, stdout) + + val stderr = new File(executorDir, "stderr") + Files.write(header, stderr, Charsets.UTF_8) + redirectStream(process.getErrorStream, stderr) // Wait for it to exit; this is actually a bad thing if it happens, because we expect to run // long-lived processes only. However, in the future, we might restart the executor a few diff --git a/core/src/main/scala/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala index 3a65ccad27..a0a9d1040a 100644 --- a/core/src/main/scala/spark/deploy/worker/Worker.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala @@ -1,20 +1,40 @@ -package spark.deploy.worker +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker -import scala.collection.mutable.{ArrayBuffer, HashMap} -import akka.actor.{ActorRef, Props, Actor, ActorSystem, Terminated} -import scala.concurrent.duration._ -import spark.{Logging, Utils} -import spark.util.AkkaUtils -import spark.deploy._ -import akka.remote.{RemoteClientLifeCycleEvent, RemoteClientShutdown, RemoteClientDisconnected} import java.text.SimpleDateFormat import java.util.Date -import spark.deploy.RegisterWorker -import spark.deploy.LaunchExecutor -import spark.deploy.RegisterWorkerFailed -import spark.deploy.master.Master import java.io.File -import ui.WorkerWebUI + +import scala.collection.mutable.HashMap +import scala.concurrent.duration._ + +import akka.actor.{ActorRef, Props, Actor, ActorSystem, Terminated} +import akka.remote.{RemoteClientLifeCycleEvent, RemoteClientShutdown, RemoteClientDisconnected} + +import org.apache.spark.{Logging} +import org.apache.spark.deploy.ExecutorState +import org.apache.spark.deploy.DeployMessages._ +import org.apache.spark.deploy.master.Master +import org.apache.spark.deploy.worker.ui.WorkerWebUI +import org.apache.spark.metrics.MetricsSystem +import org.apache.spark.util.{Utils, AkkaUtils} + private[spark] class Worker( host: String, @@ -50,6 +70,9 @@ private[spark] class Worker( var coresUsed = 0 var memoryUsed = 0 + val metricsSystem = MetricsSystem.createMetricsSystem("worker") + val workerSource = new WorkerSource(this) + def coresFree: Int = cores - coresUsed def memoryFree: Int = memory - memoryUsed @@ -73,13 +96,17 @@ private[spark] class Worker( override def preStart() { logInfo("Starting Spark worker %s:%d with %d cores, %s RAM".format( - host, port, cores, Utils.memoryMegabytesToString(memory))) + host, port, cores, Utils.megabytesToString(memory))) sparkHome = new File(Option(System.getenv("SPARK_HOME")).getOrElse(".")) logInfo("Spark home: " + sparkHome) createWorkDir() webUi = new WorkerWebUI(this, workDir, Some(webUiPort)) + webUi.start() connectToMaster() + + metricsSystem.registerSource(workerSource) + metricsSystem.start() } def connectToMaster() { @@ -107,7 +134,7 @@ private[spark] class Worker( case LaunchExecutor(appId, execId, appDesc, cores_, memory_, execSparkHome_) => logInfo("Asked to launch executor %s/%d for %s".format(appId, execId, appDesc.name)) val manager = new ExecutorRunner( - appId, execId, appDesc, cores_, memory_, self, workerId, host + ":" + port, new File(execSparkHome_), workDir) + appId, execId, appDesc, cores_, memory_, self, workerId, host, new File(execSparkHome_), workDir) executors(appId + "/" + execId) = manager manager.start() coresUsed += cores_ @@ -142,7 +169,7 @@ private[spark] class Worker( masterDisconnected() case RequestWorkerState => { - sender ! WorkerState(host, port, workerId, executors.values.toList, + sender ! WorkerStateResponse(host, port, workerId, executors.values.toList, finishedExecutors.values.toList, masterUrl, cores, memory, coresUsed, memoryUsed, masterWebUiUrl) } @@ -163,6 +190,7 @@ private[spark] class Worker( override def postStop() { executors.values.foreach(_.kill()) webUi.stop() + metricsSystem.stop() } } diff --git a/core/src/main/scala/spark/deploy/worker/WorkerArguments.scala b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala index 2b96611ee3..0ae89a864f 100644 --- a/core/src/main/scala/spark/deploy/worker/WorkerArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala @@ -1,8 +1,23 @@ -package spark.deploy.worker +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker -import spark.util.IntParam -import spark.util.MemoryParam -import spark.Utils +import org.apache.spark.util.{Utils, IntParam, MemoryParam} import java.lang.management.ManagementFactory /** diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/WorkerSource.scala b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerSource.scala new file mode 100644 index 0000000000..df269fd047 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerSource.scala @@ -0,0 +1,51 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker + +import com.codahale.metrics.{Gauge, MetricRegistry} + +import org.apache.spark.metrics.source.Source + +private[spark] class WorkerSource(val worker: Worker) extends Source { + val sourceName = "worker" + val metricRegistry = new MetricRegistry() + + metricRegistry.register(MetricRegistry.name("executors", "number"), new Gauge[Int] { + override def getValue: Int = worker.executors.size + }) + + // Gauge for cores used of this worker + metricRegistry.register(MetricRegistry.name("coresUsed", "number"), new Gauge[Int] { + override def getValue: Int = worker.coresUsed + }) + + // Gauge for memory used of this worker + metricRegistry.register(MetricRegistry.name("memUsed", "MBytes"), new Gauge[Int] { + override def getValue: Int = worker.memoryUsed + }) + + // Gauge for cores free of this worker + metricRegistry.register(MetricRegistry.name("coresFree", "number"), new Gauge[Int] { + override def getValue: Int = worker.coresFree + }) + + // Gauge for memory free of this worker + metricRegistry.register(MetricRegistry.name("memFree", "MBytes"), new Gauge[Int] { + override def getValue: Int = worker.memoryFree + }) +} diff --git a/core/src/main/scala/spark/deploy/worker/ui/IndexPage.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ui/IndexPage.scala index 6247dd4065..1a768d501f 100644 --- a/core/src/main/scala/spark/deploy/worker/ui/IndexPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ui/IndexPage.scala @@ -1,20 +1,39 @@ -package spark.deploy.worker.ui +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker.ui + +import javax.servlet.http.HttpServletRequest + +import scala.xml.Node import scala.concurrent.duration._ import scala.concurrent.Await import akka.pattern.ask -import javax.servlet.http.HttpServletRequest - import net.liftweb.json.JsonAST.JValue -import scala.xml.Node +import org.apache.spark.deploy.JsonProtocol +import org.apache.spark.deploy.DeployMessages.{RequestWorkerState, WorkerStateResponse} +import org.apache.spark.deploy.worker.ExecutorRunner +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils -import spark.deploy.{RequestWorkerState, JsonProtocol, WorkerState} -import spark.deploy.worker.ExecutorRunner -import spark.Utils -import spark.ui.UIUtils private[spark] class IndexPage(parent: WorkerWebUI) { val workerActor = parent.worker.self @@ -22,13 +41,13 @@ private[spark] class IndexPage(parent: WorkerWebUI) { val timeout = parent.timeout def renderJson(request: HttpServletRequest): JValue = { - val stateFuture = (workerActor ? RequestWorkerState)(timeout).mapTo[WorkerState] + val stateFuture = (workerActor ? RequestWorkerState)(timeout).mapTo[WorkerStateResponse] val workerState = Await.result(stateFuture, 30 seconds) JsonProtocol.writeWorkerState(workerState) } def render(request: HttpServletRequest): Seq[Node] = { - val stateFuture = (workerActor ? RequestWorkerState)(timeout).mapTo[WorkerState] + val stateFuture = (workerActor ? RequestWorkerState)(timeout).mapTo[WorkerStateResponse] val workerState = Await.result(stateFuture, 30 seconds) val executorHeaders = Seq("ExecutorID", "Cores", "Memory", "Job Details", "Logs") @@ -38,8 +57,7 @@ private[spark] class IndexPage(parent: WorkerWebUI) { UIUtils.listingTable(executorHeaders, executorRow, workerState.finishedExecutors) val content = - <hr /> - <div class="row"> <!-- Worker Details --> + <div class="row-fluid"> <!-- Worker Details --> <div class="span12"> <ul class="unstyled"> <li><strong>ID:</strong> {workerState.workerId}</li> @@ -47,32 +65,29 @@ private[spark] class IndexPage(parent: WorkerWebUI) { Master URL:</strong> {workerState.masterUrl} </li> <li><strong>Cores:</strong> {workerState.cores} ({workerState.coresUsed} Used)</li> - <li><strong>Memory:</strong> {Utils.memoryMegabytesToString(workerState.memory)} - ({Utils.memoryMegabytesToString(workerState.memoryUsed)} Used)</li> + <li><strong>Memory:</strong> {Utils.megabytesToString(workerState.memory)} + ({Utils.megabytesToString(workerState.memoryUsed)} Used)</li> </ul> <p><a href={workerState.masterWebUiUrl}>Back to Master</a></p> </div> </div> - <hr/> - <div class="row"> <!-- Running Executors --> + <div class="row-fluid"> <!-- Running Executors --> <div class="span12"> - <h3> Running Executors {workerState.executors.size} </h3> - <br/> + <h4> Running Executors {workerState.executors.size} </h4> {runningExecutorTable} </div> </div> - <hr/> - <div class="row"> <!-- Finished Executors --> + <div class="row-fluid"> <!-- Finished Executors --> <div class="span12"> - <h3> Finished Executors </h3> - <br/> + <h4> Finished Executors </h4> {finishedExecutorTable} </div> </div>; - UIUtils.basicSparkPage(content, "Spark Worker on %s:%s".format(workerState.host, workerState.port)) + UIUtils.basicSparkPage(content, "Spark Worker at %s:%s".format( + workerState.host, workerState.port)) } def executorRow(executor: ExecutorRunner): Seq[Node] = { @@ -80,7 +95,7 @@ private[spark] class IndexPage(parent: WorkerWebUI) { <td>{executor.execId}</td> <td>{executor.cores}</td> <td sorttable_customkey={executor.memory.toString}> - {Utils.memoryMegabytesToString(executor.memory)} + {Utils.megabytesToString(executor.memory)} </td> <td> <ul class="unstyled"> diff --git a/core/src/main/scala/spark/deploy/worker/ui/WorkerWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala index 9d0a39bb1e..07bc479c83 100644 --- a/core/src/main/scala/spark/deploy/worker/ui/WorkerWebUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala @@ -1,4 +1,21 @@ -package spark.deploy.worker.ui +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.worker.ui import akka.actor.ActorRef import akka.util.Timeout @@ -11,18 +28,19 @@ import javax.servlet.http.HttpServletRequest import org.eclipse.jetty.server.{Handler, Server} -import spark.deploy.worker.Worker -import spark.{Utils, Logging} -import spark.ui.JettyUtils -import spark.ui.JettyUtils._ -import spark.ui.UIUtils +import org.apache.spark.deploy.worker.Worker +import org.apache.spark.{Logging} +import org.apache.spark.ui.JettyUtils +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils /** * Web UI server for the standalone worker. */ private[spark] class WorkerWebUI(val worker: Worker, val workDir: File, requestedPort: Option[Int] = None) - extends Logging { + extends Logging { implicit val timeout = Timeout( Duration.create(System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds")) val host = Utils.localHostName() @@ -34,7 +52,9 @@ class WorkerWebUI(val worker: Worker, val workDir: File, requestedPort: Option[I val indexPage = new IndexPage(this) - val handlers = Array[(String, Handler)]( + val metricsHandlers = worker.metricsSystem.getServletHandlers + + val handlers = metricsHandlers ++ Array[(String, Handler)]( ("/static", createStaticHandler(WorkerWebUI.STATIC_RESOURCE_DIR)), ("/log", (request: HttpServletRequest) => log(request)), ("/logPage", (request: HttpServletRequest) => logPage(request)), @@ -96,30 +116,37 @@ class WorkerWebUI(val worker: Worker, val workDir: File, requestedPort: Option[I if (startByte > 0) { <a href={"?appId=%s&executorId=%s&logType=%s&offset=%s&byteLength=%s" .format(appId, executorId, logType, math.max(startByte-byteLength, 0), - byteLength)}> - <button>Previous {Utils.memoryBytesToString(math.min(byteLength, startByte))}</button> + byteLength)}> + <button type="button" class="btn btn-default"> + Previous {Utils.bytesToString(math.min(byteLength, startByte))} + </button> </a> } else { - <button disabled="disabled">Previous 0 B</button> + <button type="button" class="btn btn-default" disabled="disabled"> + Previous 0 B + </button> } val nextButton = if (endByte < logLength) { <a href={"?appId=%s&executorId=%s&logType=%s&offset=%s&byteLength=%s". format(appId, executorId, logType, endByte, byteLength)}> - <button>Next {Utils.memoryBytesToString(math.min(byteLength, logLength-endByte))}</button> + <button type="button" class="btn btn-default"> + Next {Utils.bytesToString(math.min(byteLength, logLength-endByte))} + </button> </a> } else { - <button disabled="disabled">Next 0 B</button> + <button type="button" class="btn btn-default" disabled="disabled"> + Next 0 B + </button> } val content = <html> <body> {linkToMaster} - <hr /> <div> <div style="float:left;width:40%">{backButton}</div> <div style="float:left;">{range}</div> @@ -162,6 +189,6 @@ class WorkerWebUI(val worker: Worker, val workDir: File, requestedPort: Option[I } private[spark] object WorkerWebUI { - val STATIC_RESOURCE_DIR = "spark/ui/static" + val STATIC_RESOURCE_DIR = "org/apache/spark/ui/static" val DEFAULT_PORT="8081" } diff --git a/core/src/main/scala/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index 8360547a74..d365804994 100644 --- a/core/src/main/scala/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -1,23 +1,44 @@ -package spark.executor +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor -import java.io.{File, FileOutputStream} -import java.net.{URI, URL, URLClassLoader} +import java.io.{File} +import java.lang.management.ManagementFactory +import java.nio.ByteBuffer import java.util.concurrent._ -import org.apache.hadoop.fs.FileUtil +import scala.collection.JavaConversions._ +import scala.collection.mutable.HashMap -import scala.collection.mutable.{ArrayBuffer, Map, HashMap} +import org.apache.spark.scheduler._ +import org.apache.spark._ +import org.apache.spark.util.Utils -import spark.broadcast._ -import spark.scheduler._ -import spark._ -import java.nio.ByteBuffer /** * The Mesos executor for Spark. */ -private[spark] class Executor(executorId: String, slaveHostname: String, properties: Seq[(String, String)]) extends Logging { - +private[spark] class Executor( + executorId: String, + slaveHostname: String, + properties: Seq[(String, String)]) + extends Logging +{ // Application dependencies (added through SparkContext) that we've fetched so far on this node. // Each map holds the master's timestamp for the version of that file or JAR we got. private val currentFiles: HashMap[String, Long] = new HashMap[String, Long]() @@ -40,6 +61,13 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert System.setProperty(key, value) } + // If we are in yarn mode, systems can have different disk layouts so we must set it + // to what Yarn on this system said was available. This will be used later when SparkEnv + // created. + if (java.lang.Boolean.valueOf(System.getenv("SPARK_YARN_MODE"))) { + System.setProperty("spark.local.dir", getYarnLocalDirs()) + } + // Create our ClassLoader and set it on this thread private val urlClassLoader = createClassLoader() private val replClassLoader = addReplClassLoaderIfNeeded(urlClassLoader) @@ -52,7 +80,7 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert override def uncaughtException(thread: Thread, exception: Throwable) { try { logError("Uncaught exception in thread " + thread, exception) - + // We may have been called from a shutdown hook. If so, we must not call System.exit(). // (If we do, we will deadlock.) if (!Utils.inShutdown()) { @@ -70,9 +98,13 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert } ) + val executorSource = new ExecutorSource(this) + // Initialize Spark environment (using system properties read above) val env = SparkEnv.createFromSystemProperties(executorId, slaveHostname, 0, false, false) SparkEnv.set(env) + env.metricsSystem.registerSource(executorSource) + private val akkaFrameSize = env.actorSystem.settings.config.getBytes("akka.remote.netty.message-frame-size") // Start worker thread pool @@ -83,6 +115,21 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert threadPool.execute(new TaskRunner(context, taskId, serializedTask)) } + /** Get the Yarn approved local directories. */ + private def getYarnLocalDirs(): String = { + // Hadoop 0.23 and 2.x have different Environment variable names for the + // local dirs, so lets check both. We assume one of the 2 is set. + // LOCAL_DIRS => 2.X, YARN_LOCAL_DIRS => 0.23.X + val localDirs = Option(System.getenv("YARN_LOCAL_DIRS")) + .getOrElse(Option(System.getenv("LOCAL_DIRS")) + .getOrElse("")) + + if (localDirs.isEmpty()) { + throw new Exception("Yarn Local dirs can't be empty") + } + return localDirs + } + class TaskRunner(context: ExecutorBackend, taskId: Long, serializedTask: ByteBuffer) extends Runnable { @@ -95,6 +142,9 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert context.statusUpdate(taskId, TaskState.RUNNING, EMPTY_BYTE_BUFFER) var attemptedTask: Option[Task[Any]] = None var taskStart: Long = 0 + def getTotalGCTime = ManagementFactory.getGarbageCollectorMXBeans.map(g => g.getCollectionTime).sum + val startGCTime = getTotalGCTime + try { SparkEnv.set(env) Accumulators.clear() @@ -102,15 +152,16 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert updateDependencies(taskFiles, taskJars) val task = ser.deserialize[Task[Any]](taskBytes, Thread.currentThread.getContextClassLoader) attemptedTask = Some(task) - logInfo("Its generation is " + task.generation) - env.mapOutputTracker.updateGeneration(task.generation) + logInfo("Its epoch is " + task.epoch) + env.mapOutputTracker.updateEpoch(task.epoch) taskStart = System.currentTimeMillis() val value = task.run(taskId.toInt) val taskFinish = System.currentTimeMillis() - task.metrics.foreach{ m => + for (m <- task.metrics) { m.hostname = Utils.localHostName m.executorDeserializeTime = (taskStart - startTime).toInt m.executorRunTime = (taskFinish - taskStart).toInt + m.jvmGCTime = getTotalGCTime - startGCTime } //TODO I'd also like to track the time it takes to serialize the task results, but that is huge headache, b/c // we need to serialize the task metrics first. If TaskMetrics had a custom serialized format, we could @@ -134,7 +185,10 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert case t: Throwable => { val serviceTime = (System.currentTimeMillis() - taskStart).toInt val metrics = attemptedTask.flatMap(t => t.metrics) - metrics.foreach{m => m.executorRunTime = serviceTime} + for (m <- metrics) { + m.executorRunTime = serviceTime + m.jvmGCTime = getTotalGCTime - startGCTime + } val reason = ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace, metrics) context.statusUpdate(taskId, TaskState.FAILED, ser.serialize(reason)) @@ -172,13 +226,13 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert if (classUri != null) { logInfo("Using REPL class URI: " + classUri) try { - val klass = Class.forName("spark.repl.ExecutorClassLoader") + val klass = Class.forName("org.apache.spark.repl.ExecutorClassLoader") .asInstanceOf[Class[_ <: ClassLoader]] val constructor = klass.getConstructor(classOf[String], classOf[ClassLoader]) return constructor.newInstance(classUri, parent) } catch { case _: ClassNotFoundException => - logError("Could not find spark.repl.ExecutorClassLoader on classpath!") + logError("Could not find org.apache.spark.repl.ExecutorClassLoader on classpath!") System.exit(1) null } diff --git a/core/src/main/scala/org/apache/spark/executor/ExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/ExecutorBackend.scala new file mode 100644 index 0000000000..ad7dd34c76 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/executor/ExecutorBackend.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor + +import java.nio.ByteBuffer +import org.apache.spark.TaskState.TaskState + +/** + * A pluggable interface used by the Executor to send updates to the cluster scheduler. + */ +private[spark] trait ExecutorBackend { + def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) +} diff --git a/core/src/main/scala/spark/executor/ExecutorExitCode.scala b/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala index fd76029cb3..e5c9bbbe28 100644 --- a/core/src/main/scala/spark/executor/ExecutorExitCode.scala +++ b/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala @@ -1,4 +1,21 @@ -package spark.executor +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor /** * These are exit codes that executors should use to provide the master with information about diff --git a/core/src/main/scala/org/apache/spark/executor/ExecutorSource.scala b/core/src/main/scala/org/apache/spark/executor/ExecutorSource.scala new file mode 100644 index 0000000000..bf8fb4fd21 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/executor/ExecutorSource.scala @@ -0,0 +1,72 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor + +import com.codahale.metrics.{Gauge, MetricRegistry} + +import org.apache.hadoop.fs.FileSystem +import org.apache.hadoop.hdfs.DistributedFileSystem +import org.apache.hadoop.fs.LocalFileSystem + +import scala.collection.JavaConversions._ + +import org.apache.spark.metrics.source.Source + +class ExecutorSource(val executor: Executor) extends Source { + private def fileStats(scheme: String) : Option[FileSystem.Statistics] = + FileSystem.getAllStatistics().filter(s => s.getScheme.equals(scheme)).headOption + + private def registerFileSystemStat[T]( + scheme: String, name: String, f: FileSystem.Statistics => T, defaultValue: T) = { + metricRegistry.register(MetricRegistry.name("filesystem", scheme, name), new Gauge[T] { + override def getValue: T = fileStats(scheme).map(f).getOrElse(defaultValue) + }) + } + + val metricRegistry = new MetricRegistry() + val sourceName = "executor" + + // Gauge for executor thread pool's actively executing task counts + metricRegistry.register(MetricRegistry.name("threadpool", "activeTask", "count"), new Gauge[Int] { + override def getValue: Int = executor.threadPool.getActiveCount() + }) + + // Gauge for executor thread pool's approximate total number of tasks that have been completed + metricRegistry.register(MetricRegistry.name("threadpool", "completeTask", "count"), new Gauge[Long] { + override def getValue: Long = executor.threadPool.getCompletedTaskCount() + }) + + // Gauge for executor thread pool's current number of threads + metricRegistry.register(MetricRegistry.name("threadpool", "currentPool", "size"), new Gauge[Int] { + override def getValue: Int = executor.threadPool.getPoolSize() + }) + + // Gauge got executor thread pool's largest number of threads that have ever simultaneously been in th pool + metricRegistry.register(MetricRegistry.name("threadpool", "maxPool", "size"), new Gauge[Int] { + override def getValue: Int = executor.threadPool.getMaximumPoolSize() + }) + + // Gauge for file system stats of this executor + for (scheme <- Array("hdfs", "file")) { + registerFileSystemStat(scheme, "bytesRead", _.getBytesRead(), 0L) + registerFileSystemStat(scheme, "bytesWritten", _.getBytesWritten(), 0L) + registerFileSystemStat(scheme, "readOps", _.getReadOps(), 0) + registerFileSystemStat(scheme, "largeReadOps", _.getLargeReadOps(), 0) + registerFileSystemStat(scheme, "writeOps", _.getWriteOps(), 0) + } +} diff --git a/core/src/main/scala/org/apache/spark/executor/ExecutorURLClassLoader.scala b/core/src/main/scala/org/apache/spark/executor/ExecutorURLClassLoader.scala new file mode 100644 index 0000000000..f9bfe8ed2f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/executor/ExecutorURLClassLoader.scala @@ -0,0 +1,31 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor + +import java.net.{URLClassLoader, URL} + +/** + * The addURL method in URLClassLoader is protected. We subclass it to make this accessible. + */ +private[spark] class ExecutorURLClassLoader(urls: Array[URL], parent: ClassLoader) + extends URLClassLoader(urls, parent) { + + override def addURL(url: URL) { + super.addURL(url) + } +} diff --git a/core/src/main/scala/spark/executor/MesosExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala index 10f3531df0..da62091980 100644 --- a/core/src/main/scala/spark/executor/MesosExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala @@ -1,12 +1,30 @@ -package spark.executor +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor import java.nio.ByteBuffer import org.apache.mesos.{Executor => MesosExecutor, MesosExecutorDriver, MesosNativeLibrary, ExecutorDriver} import org.apache.mesos.Protos.{TaskState => MesosTaskState, TaskStatus => MesosTaskStatus, _} -import spark.TaskState.TaskState +import org.apache.spark.TaskState.TaskState import com.google.protobuf.ByteString -import spark.{Utils, Logging} -import spark.TaskState +import org.apache.spark.{Logging} +import org.apache.spark.TaskState +import org.apache.spark.util.Utils private[spark] class MesosExecutorBackend extends MesosExecutor diff --git a/core/src/main/scala/spark/executor/StandaloneExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/StandaloneExecutorBackend.scala index ebe2ac68d8..7839023868 100644 --- a/core/src/main/scala/spark/executor/StandaloneExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/StandaloneExecutorBackend.scala @@ -1,19 +1,32 @@ -package spark.executor +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor import java.nio.ByteBuffer -import spark.Logging -import spark.TaskState.TaskState -import spark.util.AkkaUtils + import akka.actor.{ActorRef, Actor, Props, Terminated} import akka.remote.{RemoteClientLifeCycleEvent, RemoteClientShutdown, RemoteClientDisconnected} -import java.util.concurrent.{TimeUnit, ThreadPoolExecutor, SynchronousQueue} -import spark.scheduler.cluster._ -import spark.scheduler.cluster.RegisteredExecutor -import spark.scheduler.cluster.LaunchTask -import spark.scheduler.cluster.RegisterExecutorFailed -import spark.scheduler.cluster.RegisterExecutor -import spark.Utils -import spark.deploy.SparkHadoopUtil + +import org.apache.spark.{Logging, SparkEnv} +import org.apache.spark.TaskState.TaskState +import org.apache.spark.scheduler.cluster.StandaloneClusterMessages._ +import org.apache.spark.util.{Utils, AkkaUtils} + private[spark] class StandaloneExecutorBackend( driverUrl: String, @@ -68,19 +81,6 @@ private[spark] class StandaloneExecutorBackend( private[spark] object StandaloneExecutorBackend { def run(driverUrl: String, executorId: String, hostname: String, cores: Int) { - SparkHadoopUtil.runAsUser(run0, Tuple4[Any, Any, Any, Any] (driverUrl, executorId, hostname, cores)) - } - - // This will be run 'as' the user - def run0(args: Product) { - assert(4 == args.productArity) - runImpl(args.productElement(0).asInstanceOf[String], - args.productElement(1).asInstanceOf[String], - args.productElement(2).asInstanceOf[String], - args.productElement(3).asInstanceOf[Int]) - } - - private def runImpl(driverUrl: String, executorId: String, hostname: String, cores: Int) { // Debug code Utils.checkHost(hostname) diff --git a/core/src/main/scala/spark/executor/TaskMetrics.scala b/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala index 1dc13754f9..f311141148 100644 --- a/core/src/main/scala/spark/executor/TaskMetrics.scala +++ b/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala @@ -1,4 +1,21 @@ -package spark.executor +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.executor class TaskMetrics extends Serializable { /** @@ -14,7 +31,7 @@ class TaskMetrics extends Serializable { /** * Time the executor spends actually running the task (including fetching shuffle data) */ - var executorRunTime:Int = _ + var executorRunTime: Int = _ /** * The number of bytes this task transmitted back to the driver as the TaskResult @@ -22,6 +39,11 @@ class TaskMetrics extends Serializable { var resultSize: Long = _ /** + * Amount of time the JVM spent in garbage collection while executing this task + */ + var jvmGCTime: Long = _ + + /** * If this task reads from shuffle output, metrics on getting shuffle data will be collected here */ var shuffleReadMetrics: Option[ShuffleReadMetrics] = None diff --git a/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala new file mode 100644 index 0000000000..570a979b56 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.io + +import java.io.{InputStream, OutputStream} + +import com.ning.compress.lzf.{LZFInputStream, LZFOutputStream} + +import org.xerial.snappy.{SnappyInputStream, SnappyOutputStream} + + +/** + * CompressionCodec allows the customization of choosing different compression implementations + * to be used in block storage. + */ +trait CompressionCodec { + + def compressedOutputStream(s: OutputStream): OutputStream + + def compressedInputStream(s: InputStream): InputStream +} + + +private[spark] object CompressionCodec { + + def createCodec(): CompressionCodec = { + createCodec(System.getProperty( + "spark.io.compression.codec", classOf[LZFCompressionCodec].getName)) + } + + def createCodec(codecName: String): CompressionCodec = { + Class.forName(codecName, true, Thread.currentThread.getContextClassLoader) + .newInstance().asInstanceOf[CompressionCodec] + } +} + + +/** + * LZF implementation of [[org.apache.spark.io.CompressionCodec]]. + */ +class LZFCompressionCodec extends CompressionCodec { + + override def compressedOutputStream(s: OutputStream): OutputStream = { + new LZFOutputStream(s).setFinishBlockOnFlush(true) + } + + override def compressedInputStream(s: InputStream): InputStream = new LZFInputStream(s) +} + + +/** + * Snappy implementation of [[org.apache.spark.io.CompressionCodec]]. + * Block size can be configured by spark.io.compression.snappy.block.size. + */ +class SnappyCompressionCodec extends CompressionCodec { + + override def compressedOutputStream(s: OutputStream): OutputStream = { + val blockSize = System.getProperty("spark.io.compression.snappy.block.size", "32768").toInt + new SnappyOutputStream(s, blockSize) + } + + override def compressedInputStream(s: InputStream): InputStream = new SnappyInputStream(s) +} diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala new file mode 100644 index 0000000000..0f9c4e00b1 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala @@ -0,0 +1,100 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics + +import java.util.Properties +import java.io.{File, FileInputStream, InputStream, IOException} + +import scala.collection.mutable +import scala.util.matching.Regex + +import org.apache.spark.Logging + +private[spark] class MetricsConfig(val configFile: Option[String]) extends Logging { + initLogging() + + val DEFAULT_PREFIX = "*" + val INSTANCE_REGEX = "^(\\*|[a-zA-Z]+)\\.(.+)".r + val METRICS_CONF = "metrics.properties" + + val properties = new Properties() + var propertyCategories: mutable.HashMap[String, Properties] = null + + private def setDefaultProperties(prop: Properties) { + prop.setProperty("*.sink.servlet.class", "org.apache.spark.metrics.sink.MetricsServlet") + prop.setProperty("*.sink.servlet.uri", "/metrics/json") + prop.setProperty("*.sink.servlet.sample", "false") + prop.setProperty("master.sink.servlet.uri", "/metrics/master/json") + prop.setProperty("applications.sink.servlet.uri", "/metrics/applications/json") + } + + def initialize() { + //Add default properties in case there's no properties file + setDefaultProperties(properties) + + // If spark.metrics.conf is not set, try to get file in class path + var is: InputStream = null + try { + is = configFile match { + case Some(f) => new FileInputStream(f) + case None => getClass.getClassLoader.getResourceAsStream(METRICS_CONF) + } + + if (is != null) { + properties.load(is) + } + } catch { + case e: Exception => logError("Error loading configure file", e) + } finally { + if (is != null) is.close() + } + + propertyCategories = subProperties(properties, INSTANCE_REGEX) + if (propertyCategories.contains(DEFAULT_PREFIX)) { + import scala.collection.JavaConversions._ + + val defaultProperty = propertyCategories(DEFAULT_PREFIX) + for { (inst, prop) <- propertyCategories + if (inst != DEFAULT_PREFIX) + (k, v) <- defaultProperty + if (prop.getProperty(k) == null) } { + prop.setProperty(k, v) + } + } + } + + def subProperties(prop: Properties, regex: Regex): mutable.HashMap[String, Properties] = { + val subProperties = new mutable.HashMap[String, Properties] + import scala.collection.JavaConversions._ + prop.foreach { kv => + if (regex.findPrefixOf(kv._1) != None) { + val regex(prefix, suffix) = kv._1 + subProperties.getOrElseUpdate(prefix, new Properties).setProperty(suffix, kv._2) + } + } + subProperties + } + + def getInstance(inst: String): Properties = { + propertyCategories.get(inst) match { + case Some(s) => s + case None => propertyCategories.getOrElse(DEFAULT_PREFIX, new Properties) + } + } +} + diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala new file mode 100644 index 0000000000..bec0c83be8 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala @@ -0,0 +1,163 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics + +import com.codahale.metrics.{Metric, MetricFilter, MetricRegistry} + +import java.util.Properties +import java.util.concurrent.TimeUnit + +import scala.collection.mutable + +import org.apache.spark.Logging +import org.apache.spark.metrics.sink.{MetricsServlet, Sink} +import org.apache.spark.metrics.source.Source + +/** + * Spark Metrics System, created by specific "instance", combined by source, + * sink, periodically poll source metrics data to sink destinations. + * + * "instance" specify "who" (the role) use metrics system. In spark there are several roles + * like master, worker, executor, client driver, these roles will create metrics system + * for monitoring. So instance represents these roles. Currently in Spark, several instances + * have already implemented: master, worker, executor, driver, applications. + * + * "source" specify "where" (source) to collect metrics data. In metrics system, there exists + * two kinds of source: + * 1. Spark internal source, like MasterSource, WorkerSource, etc, which will collect + * Spark component's internal state, these sources are related to instance and will be + * added after specific metrics system is created. + * 2. Common source, like JvmSource, which will collect low level state, is configured by + * configuration and loaded through reflection. + * + * "sink" specify "where" (destination) to output metrics data to. Several sinks can be + * coexisted and flush metrics to all these sinks. + * + * Metrics configuration format is like below: + * [instance].[sink|source].[name].[options] = xxxx + * + * [instance] can be "master", "worker", "executor", "driver", "applications" which means only + * the specified instance has this property. + * wild card "*" can be used to replace instance name, which means all the instances will have + * this property. + * + * [sink|source] means this property belongs to source or sink. This field can only be source or sink. + * + * [name] specify the name of sink or source, it is custom defined. + * + * [options] is the specific property of this source or sink. + */ +private[spark] class MetricsSystem private (val instance: String) extends Logging { + initLogging() + + val confFile = System.getProperty("spark.metrics.conf") + val metricsConfig = new MetricsConfig(Option(confFile)) + + val sinks = new mutable.ArrayBuffer[Sink] + val sources = new mutable.ArrayBuffer[Source] + val registry = new MetricRegistry() + + // Treat MetricsServlet as a special sink as it should be exposed to add handlers to web ui + private var metricsServlet: Option[MetricsServlet] = None + + /** Get any UI handlers used by this metrics system. */ + def getServletHandlers = metricsServlet.map(_.getHandlers).getOrElse(Array()) + + metricsConfig.initialize() + registerSources() + registerSinks() + + def start() { + sinks.foreach(_.start) + } + + def stop() { + sinks.foreach(_.stop) + } + + def registerSource(source: Source) { + sources += source + try { + registry.register(source.sourceName, source.metricRegistry) + } catch { + case e: IllegalArgumentException => logInfo("Metrics already registered", e) + } + } + + def removeSource(source: Source) { + sources -= source + registry.removeMatching(new MetricFilter { + def matches(name: String, metric: Metric): Boolean = name.startsWith(source.sourceName) + }) + } + + def registerSources() { + val instConfig = metricsConfig.getInstance(instance) + val sourceConfigs = metricsConfig.subProperties(instConfig, MetricsSystem.SOURCE_REGEX) + + // Register all the sources related to instance + sourceConfigs.foreach { kv => + val classPath = kv._2.getProperty("class") + try { + val source = Class.forName(classPath).newInstance() + registerSource(source.asInstanceOf[Source]) + } catch { + case e: Exception => logError("Source class " + classPath + " cannot be instantialized", e) + } + } + } + + def registerSinks() { + val instConfig = metricsConfig.getInstance(instance) + val sinkConfigs = metricsConfig.subProperties(instConfig, MetricsSystem.SINK_REGEX) + + sinkConfigs.foreach { kv => + val classPath = kv._2.getProperty("class") + try { + val sink = Class.forName(classPath) + .getConstructor(classOf[Properties], classOf[MetricRegistry]) + .newInstance(kv._2, registry) + if (kv._1 == "servlet") { + metricsServlet = Some(sink.asInstanceOf[MetricsServlet]) + } else { + sinks += sink.asInstanceOf[Sink] + } + } catch { + case e: Exception => logError("Sink class " + classPath + " cannot be instantialized", e) + } + } + } +} + +private[spark] object MetricsSystem { + val SINK_REGEX = "^sink\\.(.+)\\.(.+)".r + val SOURCE_REGEX = "^source\\.(.+)\\.(.+)".r + + val MINIMAL_POLL_UNIT = TimeUnit.SECONDS + val MINIMAL_POLL_PERIOD = 1 + + def checkMinimalPollingPeriod(pollUnit: TimeUnit, pollPeriod: Int) { + val period = MINIMAL_POLL_UNIT.convert(pollPeriod, pollUnit) + if (period < MINIMAL_POLL_PERIOD) { + throw new IllegalArgumentException("Polling period " + pollPeriod + " " + pollUnit + + " below than minimal polling period ") + } + } + + def createMetricsSystem(instance: String): MetricsSystem = new MetricsSystem(instance) +} diff --git a/core/src/main/scala/org/apache/spark/metrics/sink/ConsoleSink.scala b/core/src/main/scala/org/apache/spark/metrics/sink/ConsoleSink.scala new file mode 100644 index 0000000000..bce257d6e6 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/sink/ConsoleSink.scala @@ -0,0 +1,59 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.sink + +import com.codahale.metrics.{ConsoleReporter, MetricRegistry} + +import java.util.Properties +import java.util.concurrent.TimeUnit + +import org.apache.spark.metrics.MetricsSystem + +class ConsoleSink(val property: Properties, val registry: MetricRegistry) extends Sink { + val CONSOLE_DEFAULT_PERIOD = 10 + val CONSOLE_DEFAULT_UNIT = "SECONDS" + + val CONSOLE_KEY_PERIOD = "period" + val CONSOLE_KEY_UNIT = "unit" + + val pollPeriod = Option(property.getProperty(CONSOLE_KEY_PERIOD)) match { + case Some(s) => s.toInt + case None => CONSOLE_DEFAULT_PERIOD + } + + val pollUnit = Option(property.getProperty(CONSOLE_KEY_UNIT)) match { + case Some(s) => TimeUnit.valueOf(s.toUpperCase()) + case None => TimeUnit.valueOf(CONSOLE_DEFAULT_UNIT) + } + + MetricsSystem.checkMinimalPollingPeriod(pollUnit, pollPeriod) + + val reporter: ConsoleReporter = ConsoleReporter.forRegistry(registry) + .convertDurationsTo(TimeUnit.MILLISECONDS) + .convertRatesTo(TimeUnit.SECONDS) + .build() + + override def start() { + reporter.start(pollPeriod, pollUnit) + } + + override def stop() { + reporter.stop() + } +} + diff --git a/core/src/main/scala/org/apache/spark/metrics/sink/CsvSink.scala b/core/src/main/scala/org/apache/spark/metrics/sink/CsvSink.scala new file mode 100644 index 0000000000..3d1a06a395 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/sink/CsvSink.scala @@ -0,0 +1,68 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.sink + +import com.codahale.metrics.{CsvReporter, MetricRegistry} + +import java.io.File +import java.util.{Locale, Properties} +import java.util.concurrent.TimeUnit + +import org.apache.spark.metrics.MetricsSystem + +class CsvSink(val property: Properties, val registry: MetricRegistry) extends Sink { + val CSV_KEY_PERIOD = "period" + val CSV_KEY_UNIT = "unit" + val CSV_KEY_DIR = "directory" + + val CSV_DEFAULT_PERIOD = 10 + val CSV_DEFAULT_UNIT = "SECONDS" + val CSV_DEFAULT_DIR = "/tmp/" + + val pollPeriod = Option(property.getProperty(CSV_KEY_PERIOD)) match { + case Some(s) => s.toInt + case None => CSV_DEFAULT_PERIOD + } + + val pollUnit = Option(property.getProperty(CSV_KEY_UNIT)) match { + case Some(s) => TimeUnit.valueOf(s.toUpperCase()) + case None => TimeUnit.valueOf(CSV_DEFAULT_UNIT) + } + + MetricsSystem.checkMinimalPollingPeriod(pollUnit, pollPeriod) + + val pollDir = Option(property.getProperty(CSV_KEY_DIR)) match { + case Some(s) => s + case None => CSV_DEFAULT_DIR + } + + val reporter: CsvReporter = CsvReporter.forRegistry(registry) + .formatFor(Locale.US) + .convertDurationsTo(TimeUnit.MILLISECONDS) + .convertRatesTo(TimeUnit.SECONDS) + .build(new File(pollDir)) + + override def start() { + reporter.start(pollPeriod, pollUnit) + } + + override def stop() { + reporter.stop() + } +} + diff --git a/core/src/main/scala/org/apache/spark/metrics/sink/JmxSink.scala b/core/src/main/scala/org/apache/spark/metrics/sink/JmxSink.scala new file mode 100644 index 0000000000..621d086d41 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/sink/JmxSink.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.sink + +import com.codahale.metrics.{JmxReporter, MetricRegistry} + +import java.util.Properties + +class JmxSink(val property: Properties, val registry: MetricRegistry) extends Sink { + val reporter: JmxReporter = JmxReporter.forRegistry(registry).build() + + override def start() { + reporter.start() + } + + override def stop() { + reporter.stop() + } + +} diff --git a/core/src/main/scala/org/apache/spark/metrics/sink/MetricsServlet.scala b/core/src/main/scala/org/apache/spark/metrics/sink/MetricsServlet.scala new file mode 100644 index 0000000000..4e90dd4323 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/sink/MetricsServlet.scala @@ -0,0 +1,55 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.sink + +import com.codahale.metrics.MetricRegistry +import com.codahale.metrics.json.MetricsModule + +import com.fasterxml.jackson.databind.ObjectMapper + +import java.util.Properties +import java.util.concurrent.TimeUnit +import javax.servlet.http.HttpServletRequest + +import org.eclipse.jetty.server.Handler + +import org.apache.spark.ui.JettyUtils + +class MetricsServlet(val property: Properties, val registry: MetricRegistry) extends Sink { + val SERVLET_KEY_URI = "uri" + val SERVLET_KEY_SAMPLE = "sample" + + val servletURI = property.getProperty(SERVLET_KEY_URI) + + val servletShowSample = property.getProperty(SERVLET_KEY_SAMPLE).toBoolean + + val mapper = new ObjectMapper().registerModule( + new MetricsModule(TimeUnit.SECONDS, TimeUnit.MILLISECONDS, servletShowSample)) + + def getHandlers = Array[(String, Handler)]( + (servletURI, JettyUtils.createHandler(request => getMetricsSnapshot(request), "text/json")) + ) + + def getMetricsSnapshot(request: HttpServletRequest): String = { + mapper.writeValueAsString(registry) + } + + override def start() { } + + override def stop() { } +} diff --git a/core/src/main/scala/org/apache/spark/metrics/sink/Sink.scala b/core/src/main/scala/org/apache/spark/metrics/sink/Sink.scala new file mode 100644 index 0000000000..3a739aa563 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/sink/Sink.scala @@ -0,0 +1,23 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.sink + +trait Sink { + def start: Unit + def stop: Unit +} diff --git a/core/src/main/scala/org/apache/spark/metrics/source/JvmSource.scala b/core/src/main/scala/org/apache/spark/metrics/source/JvmSource.scala new file mode 100644 index 0000000000..75cb2b8973 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/source/JvmSource.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.source + +import com.codahale.metrics.MetricRegistry +import com.codahale.metrics.jvm.{GarbageCollectorMetricSet, MemoryUsageGaugeSet} + +class JvmSource extends Source { + val sourceName = "jvm" + val metricRegistry = new MetricRegistry() + + val gcMetricSet = new GarbageCollectorMetricSet + val memGaugeSet = new MemoryUsageGaugeSet + + metricRegistry.registerAll(gcMetricSet) + metricRegistry.registerAll(memGaugeSet) +} diff --git a/core/src/main/scala/org/apache/spark/metrics/source/Source.scala b/core/src/main/scala/org/apache/spark/metrics/source/Source.scala new file mode 100644 index 0000000000..3fee55cc6d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/metrics/source/Source.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics.source + +import com.codahale.metrics.MetricRegistry + +trait Source { + def sourceName: String + def metricRegistry: MetricRegistry +} diff --git a/core/src/main/scala/spark/network/BufferMessage.scala b/core/src/main/scala/org/apache/spark/network/BufferMessage.scala index 7b0e489a6c..f736bb3713 100644 --- a/core/src/main/scala/spark/network/BufferMessage.scala +++ b/core/src/main/scala/org/apache/spark/network/BufferMessage.scala @@ -1,10 +1,27 @@ -package spark.network +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network import java.nio.ByteBuffer import scala.collection.mutable.ArrayBuffer -import spark.storage.BlockManager +import org.apache.spark.storage.BlockManager private[spark] @@ -91,4 +108,4 @@ class BufferMessage(id_ : Int, val buffers: ArrayBuffer[ByteBuffer], var ackId: "BufferMessage(id = " + id + ", size = " + size + ")" } } -}
\ No newline at end of file +} diff --git a/core/src/main/scala/spark/network/Connection.scala b/core/src/main/scala/org/apache/spark/network/Connection.scala index 6e28f677a3..95cb0206ac 100644 --- a/core/src/main/scala/spark/network/Connection.scala +++ b/core/src/main/scala/org/apache/spark/network/Connection.scala @@ -1,6 +1,23 @@ -package spark.network - -import spark._ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network + +import org.apache.spark._ import scala.collection.mutable.{HashMap, Queue, ArrayBuffer} @@ -28,12 +45,15 @@ abstract class Connection(val channel: SocketChannel, val selector: Selector, channel.socket.setKeepAlive(true) /*channel.socket.setReceiveBufferSize(32768) */ + @volatile private var closed = false var onCloseCallback: Connection => Unit = null var onExceptionCallback: (Connection, Exception) => Unit = null var onKeyInterestChangeCallback: (Connection, Int) => Unit = null val remoteAddress = getRemoteAddress() + def resetForceReregister(): Boolean + // Read channels typically do not register for write and write does not for read // Now, we do have write registering for read too (temporarily), but this is to detect // channel close NOT to actually read/consume data on it ! @@ -78,6 +98,7 @@ abstract class Connection(val channel: SocketChannel, val selector: Selector, } def close() { + closed = true val k = key() if (k != null) { k.cancel() @@ -86,6 +107,8 @@ abstract class Connection(val channel: SocketChannel, val selector: Selector, callOnCloseCallback() } + protected def isClosed: Boolean = closed + def onClose(callback: Connection => Unit) { onCloseCallback = callback } @@ -151,7 +174,7 @@ class SendingConnection(val address: InetSocketAddress, selector_ : Selector, remoteId_ : ConnectionManagerId) extends Connection(SocketChannel.open, selector_, remoteId_) { - class Outbox(fair: Int = 0) { + private class Outbox(fair: Int = 0) { val messages = new Queue[Message]() val defaultChunkSize = 65536 //32768 //16384 var nextMessageToBeUsed = 0 @@ -228,7 +251,17 @@ class SendingConnection(val address: InetSocketAddress, selector_ : Selector, } } + // outbox is used as a lock - ensure that it is always used as a leaf (since methods which + // lock it are invoked in context of other locks) private val outbox = new Outbox(1) + /* + This is orthogonal to whether we have pending bytes to write or not - and satisfies a slightly + different purpose. This flag is to see if we need to force reregister for write even when we + do not have any pending bytes to write to socket. + This can happen due to a race between adding pending buffers, and checking for existing of + data as detailed in https://github.com/mesos/spark/pull/791 + */ + private var needForceReregister = false val currentBuffers = new ArrayBuffer[ByteBuffer]() /*channel.socket.setSendBufferSize(256 * 1024)*/ @@ -250,9 +283,19 @@ class SendingConnection(val address: InetSocketAddress, selector_ : Selector, def send(message: Message) { outbox.synchronized { outbox.addMessage(message) - if (channel.isConnected) { - registerInterest() - } + needForceReregister = true + } + if (channel.isConnected) { + registerInterest() + } + } + + // return previous value after resetting it. + def resetForceReregister(): Boolean = { + outbox.synchronized { + val result = needForceReregister + needForceReregister = false + result } } @@ -305,7 +348,11 @@ class SendingConnection(val address: InetSocketAddress, selector_ : Selector, outbox.synchronized { outbox.getChunk() match { case Some(chunk) => { - currentBuffers ++= chunk.buffers + val buffers = chunk.buffers + // If we have 'seen' pending messages, then reset flag - since we handle that as normal + // registering of event (below) + if (needForceReregister && buffers.exists(_.remaining() > 0)) resetForceReregister() + currentBuffers ++= buffers } case None => { // changeConnectionKeyInterest(0) @@ -367,7 +414,7 @@ class SendingConnection(val address: InetSocketAddress, selector_ : Selector, override def changeInterestForRead(): Boolean = false - override def changeInterestForWrite(): Boolean = true + override def changeInterestForWrite(): Boolean = ! isClosed } @@ -517,6 +564,7 @@ private[spark] class ReceivingConnection(channel_ : SocketChannel, selector_ : S def onReceive(callback: (Connection, Message) => Unit) {onReceiveCallback = callback} + // override def changeInterestForRead(): Boolean = ! isClosed override def changeInterestForRead(): Boolean = true override def changeInterestForWrite(): Boolean = { @@ -532,4 +580,7 @@ private[spark] class ReceivingConnection(channel_ : SocketChannel, selector_ : S override def unregisterInterest() { changeConnectionKeyInterest(0) } + + // For read conn, always false. + override def resetForceReregister(): Boolean = false } diff --git a/core/src/main/scala/spark/network/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala index cc5c62a542..c24fd48c04 100644 --- a/core/src/main/scala/spark/network/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala @@ -1,6 +1,23 @@ -package spark.network - -import spark._ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network + +import org.apache.spark._ import java.nio._ import java.nio.channels._ @@ -18,6 +35,7 @@ import scala.concurrent.{Await, Promise, ExecutionContext, Future} import scala.concurrent.duration.Duration import scala.concurrent.duration._ +import org.apache.spark.util.Utils private[spark] class ConnectionManager(port: Int) extends Logging { @@ -106,7 +124,8 @@ private[spark] class ConnectionManager(port: Int) extends Logging { } finally { writeRunnableStarted.synchronized { writeRunnableStarted -= key - if (register && conn.changeInterestForWrite()) { + val needReregister = register || conn.resetForceReregister() + if (needReregister && conn.changeInterestForWrite()) { conn.registerInterest() } } diff --git a/core/src/main/scala/org/apache/spark/network/ConnectionManagerId.scala b/core/src/main/scala/org/apache/spark/network/ConnectionManagerId.scala new file mode 100644 index 0000000000..50dd9bc2d1 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/network/ConnectionManagerId.scala @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network + +import java.net.InetSocketAddress + +import org.apache.spark.util.Utils + + +private[spark] case class ConnectionManagerId(host: String, port: Int) { + // DEBUG code + Utils.checkHost(host) + assert (port > 0) + + def toSocketAddress() = new InetSocketAddress(host, port) +} + + +private[spark] object ConnectionManagerId { + def fromSocketAddress(socketAddress: InetSocketAddress): ConnectionManagerId = { + new ConnectionManagerId(socketAddress.getHostName(), socketAddress.getPort()) + } +} diff --git a/core/src/main/scala/spark/network/ConnectionManagerTest.scala b/core/src/main/scala/org/apache/spark/network/ConnectionManagerTest.scala index 1b5b0935c2..4f5742d29b 100644 --- a/core/src/main/scala/spark/network/ConnectionManagerTest.scala +++ b/core/src/main/scala/org/apache/spark/network/ConnectionManagerTest.scala @@ -1,7 +1,24 @@ -package spark.network +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import spark._ -import spark.SparkContext._ +package org.apache.spark.network + +import org.apache.spark._ +import org.apache.spark.SparkContext._ import scala.io.Source diff --git a/core/src/main/scala/spark/network/Message.scala b/core/src/main/scala/org/apache/spark/network/Message.scala index d4f03610eb..f2ecc6d439 100644 --- a/core/src/main/scala/spark/network/Message.scala +++ b/core/src/main/scala/org/apache/spark/network/Message.scala @@ -1,4 +1,21 @@ -package spark.network +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network import java.nio.ByteBuffer import java.net.InetSocketAddress diff --git a/core/src/main/scala/org/apache/spark/network/MessageChunk.scala b/core/src/main/scala/org/apache/spark/network/MessageChunk.scala new file mode 100644 index 0000000000..e0fe57b80d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/network/MessageChunk.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network + +import java.nio.ByteBuffer + +import scala.collection.mutable.ArrayBuffer + + +private[network] +class MessageChunk(val header: MessageChunkHeader, val buffer: ByteBuffer) { + + val size = if (buffer == null) 0 else buffer.remaining + + lazy val buffers = { + val ab = new ArrayBuffer[ByteBuffer]() + ab += header.buffer + if (buffer != null) { + ab += buffer + } + ab + } + + override def toString = { + "" + this.getClass.getSimpleName + " (id = " + header.id + ", size = " + size + ")" + } +} diff --git a/core/src/main/scala/spark/network/MessageChunkHeader.scala b/core/src/main/scala/org/apache/spark/network/MessageChunkHeader.scala index 3693d509d6..235fbc39b3 100644 --- a/core/src/main/scala/spark/network/MessageChunkHeader.scala +++ b/core/src/main/scala/org/apache/spark/network/MessageChunkHeader.scala @@ -1,4 +1,21 @@ -package spark.network +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network import java.net.InetAddress import java.net.InetSocketAddress diff --git a/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala b/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala new file mode 100644 index 0000000000..781715108b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala @@ -0,0 +1,37 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network + +import java.nio.ByteBuffer +import java.net.InetAddress + +private[spark] object ReceiverTest { + + def main(args: Array[String]) { + val manager = new ConnectionManager(9999) + println("Started connection manager with id = " + manager.id) + + manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { + /*println("Received [" + msg + "] from [" + id + "] at " + System.currentTimeMillis)*/ + val buffer = ByteBuffer.wrap("response".getBytes()) + Some(Message.createBufferMessage(buffer, msg.id)) + }) + Thread.currentThread.join() + } +} + diff --git a/core/src/main/scala/spark/network/SenderTest.scala b/core/src/main/scala/org/apache/spark/network/SenderTest.scala index a4ff69e4d2..777574980f 100644 --- a/core/src/main/scala/spark/network/SenderTest.scala +++ b/core/src/main/scala/org/apache/spark/network/SenderTest.scala @@ -1,4 +1,21 @@ -package spark.network +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network import java.nio.ByteBuffer import java.net.InetAddress diff --git a/core/src/main/scala/spark/network/netty/FileHeader.scala b/core/src/main/scala/org/apache/spark/network/netty/FileHeader.scala index aed4254234..3c29700920 100644 --- a/core/src/main/scala/spark/network/netty/FileHeader.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/FileHeader.scala @@ -1,8 +1,25 @@ -package spark.network.netty +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty import io.netty.buffer._ -import spark.Logging +import org.apache.spark.Logging private[spark] class FileHeader ( val fileLen: Int, diff --git a/core/src/main/scala/spark/network/netty/ShuffleCopier.scala b/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala index 8d5194a737..9493ccffd9 100644 --- a/core/src/main/scala/spark/network/netty/ShuffleCopier.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala @@ -1,4 +1,21 @@ -package spark.network.netty +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty import java.util.concurrent.Executors @@ -6,8 +23,8 @@ import io.netty.buffer.ByteBuf import io.netty.channel.ChannelHandlerContext import io.netty.util.CharsetUtil -import spark.Logging -import spark.network.ConnectionManagerId +import org.apache.spark.Logging +import org.apache.spark.network.ConnectionManagerId import scala.collection.JavaConverters._ diff --git a/core/src/main/scala/spark/network/netty/ShuffleSender.scala b/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala index d6fa4b1e80..537f225469 100644 --- a/core/src/main/scala/spark/network/netty/ShuffleSender.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala @@ -1,8 +1,25 @@ -package spark.network.netty +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.netty import java.io.File -import spark.Logging +import org.apache.spark.Logging private[spark] class ShuffleSender(portIn: Int, val pResolver: PathResolver) extends Logging { diff --git a/core/src/main/scala/org/apache/spark/package.scala b/core/src/main/scala/org/apache/spark/package.scala new file mode 100644 index 0000000000..f132e2b735 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/package.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +/** + * Core Spark functionality. [[org.apache.spark.SparkContext]] serves as the main entry point to + * Spark, while [[org.apache.spark.rdd.RDD]] is the data type representing a distributed collection, + * and provides most parallel operations. + * + * In addition, [[org.apache.spark.rdd.PairRDDFunctions]] contains operations available only on RDDs + * of key-value pairs, such as `groupByKey` and `join`; [[org.apache.spark.rdd.DoubleRDDFunctions]] + * contains operations available only on RDDs of Doubles; and + * [[org.apache.spark.rdd.SequenceFileRDDFunctions]] contains operations available on RDDs that can + * be saved as SequenceFiles. These operations are automatically available on any RDD of the right + * type (e.g. RDD[(Int, Int)] through implicit conversions when you + * `import org.apache.spark.SparkContext._`. + */ +package object spark { + // For package docs only +} diff --git a/core/src/main/scala/spark/partial/ApproximateActionListener.scala b/core/src/main/scala/org/apache/spark/partial/ApproximateActionListener.scala index de2dce161a..d71069444a 100644 --- a/core/src/main/scala/spark/partial/ApproximateActionListener.scala +++ b/core/src/main/scala/org/apache/spark/partial/ApproximateActionListener.scala @@ -1,7 +1,25 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial -import spark._ -import spark.scheduler.JobListener +import org.apache.spark._ +import org.apache.spark.scheduler.JobListener +import org.apache.spark.rdd.RDD /** * A JobListener for an approximate single-result action, such as count() or non-parallel reduce(). diff --git a/core/src/main/scala/org/apache/spark/partial/ApproximateEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/ApproximateEvaluator.scala new file mode 100644 index 0000000000..9c2859c8b9 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/partial/ApproximateEvaluator.scala @@ -0,0 +1,27 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial + +/** + * An object that computes a function incrementally by merging in results of type U from multiple + * tasks. Allows partial evaluation at any point by calling currentResult(). + */ +private[spark] trait ApproximateEvaluator[U, R] { + def merge(outputId: Int, taskResult: U): Unit + def currentResult(): R +} diff --git a/core/src/main/scala/org/apache/spark/partial/BoundedDouble.scala b/core/src/main/scala/org/apache/spark/partial/BoundedDouble.scala new file mode 100644 index 0000000000..5f4450859c --- /dev/null +++ b/core/src/main/scala/org/apache/spark/partial/BoundedDouble.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial + +/** + * A Double with error bars on it. + */ +class BoundedDouble(val mean: Double, val confidence: Double, val low: Double, val high: Double) { + override def toString(): String = "[%.3f, %.3f]".format(low, high) +} diff --git a/core/src/main/scala/spark/partial/CountEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/CountEvaluator.scala index daf2c5170c..3155dfe165 100644 --- a/core/src/main/scala/spark/partial/CountEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/CountEvaluator.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import cern.jet.stat.Probability diff --git a/core/src/main/scala/spark/partial/GroupedCountEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/GroupedCountEvaluator.scala index 01fbb8a11b..e519e3a548 100644 --- a/core/src/main/scala/spark/partial/GroupedCountEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/GroupedCountEvaluator.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import java.util.{HashMap => JHashMap} import java.util.{Map => JMap} diff --git a/core/src/main/scala/spark/partial/GroupedMeanEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/GroupedMeanEvaluator.scala index c622df5220..cf8a5680b6 100644 --- a/core/src/main/scala/spark/partial/GroupedMeanEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/GroupedMeanEvaluator.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import java.util.{HashMap => JHashMap} import java.util.{Map => JMap} @@ -7,7 +24,7 @@ import scala.collection.mutable.HashMap import scala.collection.Map import scala.collection.JavaConversions.mapAsScalaMap -import spark.util.StatCounter +import org.apache.spark.util.StatCounter /** * An ApproximateEvaluator for means by key. Returns a map of key to confidence interval. diff --git a/core/src/main/scala/spark/partial/GroupedSumEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/GroupedSumEvaluator.scala index 20fa55cff2..8225a5d933 100644 --- a/core/src/main/scala/spark/partial/GroupedSumEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/GroupedSumEvaluator.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import java.util.{HashMap => JHashMap} import java.util.{Map => JMap} @@ -7,7 +24,7 @@ import scala.collection.mutable.HashMap import scala.collection.Map import scala.collection.JavaConversions.mapAsScalaMap -import spark.util.StatCounter +import org.apache.spark.util.StatCounter /** * An ApproximateEvaluator for sums by key. Returns a map of key to confidence interval. diff --git a/core/src/main/scala/spark/partial/MeanEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/MeanEvaluator.scala index 762c85400d..d24959cba8 100644 --- a/core/src/main/scala/spark/partial/MeanEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/MeanEvaluator.scala @@ -1,8 +1,25 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import cern.jet.stat.Probability -import spark.util.StatCounter +import org.apache.spark.util.StatCounter /** * An ApproximateEvaluator for means. diff --git a/core/src/main/scala/spark/partial/PartialResult.scala b/core/src/main/scala/org/apache/spark/partial/PartialResult.scala index 200ed4ea1e..5ce49b8100 100644 --- a/core/src/main/scala/spark/partial/PartialResult.scala +++ b/core/src/main/scala/org/apache/spark/partial/PartialResult.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial class PartialResult[R](initialVal: R, isFinal: Boolean) { private var finalValue: Option[R] = if (isFinal) Some(initialVal) else None diff --git a/core/src/main/scala/spark/partial/StudentTCacher.scala b/core/src/main/scala/org/apache/spark/partial/StudentTCacher.scala index 443abba5cd..92915ee66d 100644 --- a/core/src/main/scala/spark/partial/StudentTCacher.scala +++ b/core/src/main/scala/org/apache/spark/partial/StudentTCacher.scala @@ -1,4 +1,21 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import cern.jet.stat.Probability diff --git a/core/src/main/scala/spark/partial/SumEvaluator.scala b/core/src/main/scala/org/apache/spark/partial/SumEvaluator.scala index 58fb60f441..a74f800944 100644 --- a/core/src/main/scala/spark/partial/SumEvaluator.scala +++ b/core/src/main/scala/org/apache/spark/partial/SumEvaluator.scala @@ -1,8 +1,25 @@ -package spark.partial +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.partial import cern.jet.stat.Probability -import spark.util.StatCounter +import org.apache.spark.util.StatCounter /** * An ApproximateEvaluator for sums. It estimates the mean and the cont and multiplies them diff --git a/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala b/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala new file mode 100644 index 0000000000..bca6956a18 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala @@ -0,0 +1,51 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{SparkContext, SparkEnv, Partition, TaskContext} +import org.apache.spark.storage.BlockManager + +private[spark] class BlockRDDPartition(val blockId: String, idx: Int) extends Partition { + val index = idx +} + +private[spark] +class BlockRDD[T: ClassManifest](sc: SparkContext, @transient blockIds: Array[String]) + extends RDD[T](sc, Nil) { + + @transient lazy val locations_ = BlockManager.blockIdsToHosts(blockIds, SparkEnv.get) + + override def getPartitions: Array[Partition] = (0 until blockIds.size).map(i => { + new BlockRDDPartition(blockIds(i), i).asInstanceOf[Partition] + }).toArray + + override def compute(split: Partition, context: TaskContext): Iterator[T] = { + val blockManager = SparkEnv.get.blockManager + val blockId = split.asInstanceOf[BlockRDDPartition].blockId + blockManager.get(blockId) match { + case Some(block) => block.asInstanceOf[Iterator[T]] + case None => + throw new Exception("Could not compute split, block " + blockId + " not found") + } + } + + override def getPreferredLocations(split: Partition): Seq[String] = { + locations_(split.asInstanceOf[BlockRDDPartition].blockId) + } +} + diff --git a/core/src/main/scala/spark/rdd/CartesianRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala index 20a7487c48..4fb7f3aace 100644 --- a/core/src/main/scala/spark/rdd/CartesianRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala @@ -1,10 +1,25 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import java.io.{ObjectOutputStream, IOException} +package org.apache.spark.rdd +import java.io.{ObjectOutputStream, IOException} import scala.reflect.ClassTag - -import spark._ +import org.apache.spark._ private[spark] @@ -50,7 +65,7 @@ class CartesianRDD[T: ClassTag, U:ClassTag]( override def getPreferredLocations(split: Partition): Seq[String] = { val currSplit = split.asInstanceOf[CartesianPartition] - rdd1.preferredLocations(currSplit.s1) ++ rdd2.preferredLocations(currSplit.s2) + (rdd1.preferredLocations(currSplit.s1) ++ rdd2.preferredLocations(currSplit.s2)).distinct } override def compute(split: Partition, context: TaskContext) = { diff --git a/core/src/main/scala/spark/rdd/CheckpointRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala index efd29fa561..3f4d4ad46a 100644 --- a/core/src/main/scala/spark/rdd/CheckpointRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala @@ -1,7 +1,24 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.reflect.ClassTag -import spark._ +import org.apache.spark._ import org.apache.hadoop.mapred.{FileInputFormat, SequenceFileInputFormat, JobConf, Reporter} import org.apache.hadoop.conf.Configuration import org.apache.hadoop.io.{NullWritable, BytesWritable} @@ -9,7 +26,6 @@ import org.apache.hadoop.util.ReflectionUtils import org.apache.hadoop.fs.Path import java.io.{File, IOException, EOFException} import java.text.NumberFormat -import spark.deploy.SparkHadoopUtil private[spark] class CheckpointRDDPartition(val index: Int) extends Partition {} @@ -66,8 +82,9 @@ private[spark] object CheckpointRDD extends Logging { } def writeToFile[T](path: String, blockSize: Int = -1)(ctx: TaskContext, iterator: Iterator[T]) { + val env = SparkEnv.get val outputDir = new Path(path) - val fs = outputDir.getFileSystem(SparkHadoopUtil.newConfiguration()) + val fs = outputDir.getFileSystem(env.hadoop.newConfiguration()) val finalOutputName = splitIdToFile(ctx.splitId) val finalOutputPath = new Path(outputDir, finalOutputName) @@ -85,7 +102,7 @@ private[spark] object CheckpointRDD extends Logging { // This is mainly for testing purpose fs.create(tempOutputPath, false, bufferSize, fs.getDefaultReplication, blockSize) } - val serializer = SparkEnv.get.serializer.newInstance() + val serializer = env.serializer.newInstance() val serializeStream = serializer.serializeStream(fileOutputStream) serializeStream.writeAll(iterator) serializeStream.close() @@ -105,10 +122,11 @@ private[spark] object CheckpointRDD extends Logging { } def readFromFile[T](path: Path, context: TaskContext): Iterator[T] = { - val fs = path.getFileSystem(SparkHadoopUtil.newConfiguration()) + val env = SparkEnv.get + val fs = path.getFileSystem(env.hadoop.newConfiguration()) val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt val fileInputStream = fs.open(path, bufferSize) - val serializer = SparkEnv.get.serializer.newInstance() + val serializer = env.serializer.newInstance() val deserializeStream = serializer.deserializeStream(fileInputStream) // Register an on-task-completion callback to close the input stream. @@ -121,13 +139,14 @@ private[spark] object CheckpointRDD extends Logging { // each split file having multiple blocks. This needs to be run on a // cluster (mesos or standalone) using HDFS. def main(args: Array[String]) { - import spark._ + import org.apache.spark._ val Array(cluster, hdfsPath) = args + val env = SparkEnv.get val sc = new SparkContext(cluster, "CheckpointRDD Test") val rdd = sc.makeRDD(1 to 10, 10).flatMap(x => 1 to 10000) val path = new Path(hdfsPath, "temp") - val fs = path.getFileSystem(SparkHadoopUtil.newConfiguration()) + val fs = path.getFileSystem(env.hadoop.newConfiguration()) sc.runJob(rdd, CheckpointRDD.writeToFile(path.toString, 1024) _) val cpRDD = new CheckpointRDD[Int](sc, path.toString) assert(cpRDD.partitions.length == rdd.partitions.length, "Number of partitions is not the same") diff --git a/core/src/main/scala/spark/rdd/CoGroupedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala index 8966f9f86e..0187256a8e 100644 --- a/core/src/main/scala/spark/rdd/CoGroupedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.io.{ObjectOutputStream, IOException} import java.util.{HashMap => JHashMap} @@ -6,8 +23,8 @@ import java.util.{HashMap => JHashMap} import scala.collection.JavaConversions import scala.collection.mutable.ArrayBuffer -import spark.{Aggregator, Partition, Partitioner, RDD, SparkEnv, TaskContext} -import spark.{Dependency, OneToOneDependency, ShuffleDependency} +import org.apache.spark.{Partition, Partitioner, SparkEnv, TaskContext} +import org.apache.spark.{Dependency, OneToOneDependency, ShuffleDependency} private[spark] sealed trait CoGroupSplitDep extends Serializable @@ -35,13 +52,6 @@ class CoGroupPartition(idx: Int, val deps: Array[CoGroupSplitDep]) override def hashCode(): Int = idx } -private[spark] class CoGroupAggregator - extends Aggregator[Any, Any, ArrayBuffer[Any]]( - { x => ArrayBuffer(x) }, - { (b, x) => b += x }, - { (b1, b2) => b1 ++ b2 }) - with Serializable - /** * A RDD that cogroups its parents. For each key k in parent RDDs, the resulting RDD contains a @@ -49,34 +59,25 @@ private[spark] class CoGroupAggregator * * @param rdds parent RDDs. * @param part partitioner used to partition the shuffle output. - * @param mapSideCombine flag indicating whether to merge values before shuffle step. If the flag - * is on, Spark does an extra pass over the data on the map side to merge - * all values belonging to the same key together. This can reduce the amount - * of data shuffled if and only if the number of distinct keys is very small, - * and the ratio of key size to value size is also very small. */ -class CoGroupedRDD[K]( - @transient var rdds: Seq[RDD[(K, _)]], - part: Partitioner, - val mapSideCombine: Boolean = false, - val serializerClass: String = null) +class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part: Partitioner) extends RDD[(K, Seq[Seq[_]])](rdds.head.context, Nil) { - private val aggr = new CoGroupAggregator + private var serializerClass: String = null + + def setSerializer(cls: String): CoGroupedRDD[K] = { + serializerClass = cls + this + } override def getDependencies: Seq[Dependency[_]] = { - rdds.map { rdd => + rdds.map { rdd: RDD[_ <: Product2[K, _]] => if (rdd.partitioner == Some(part)) { - logInfo("Adding one-to-one dependency with " + rdd) + logDebug("Adding one-to-one dependency with " + rdd) new OneToOneDependency(rdd) } else { - logInfo("Adding shuffle dependency with " + rdd) - if (mapSideCombine) { - val mapSideCombinedRDD = rdd.mapPartitions(aggr.combineValuesByKey(_), true) - new ShuffleDependency[Any, ArrayBuffer[Any]](mapSideCombinedRDD, part, serializerClass) - } else { - new ShuffleDependency[Any, Any](rdd.asInstanceOf[RDD[(Any, Any)]], part, serializerClass) - } + logDebug("Adding shuffle dependency with " + rdd) + new ShuffleDependency[Any, Any](rdd, part, serializerClass) } } } @@ -121,23 +122,15 @@ class CoGroupedRDD[K]( for ((dep, depNum) <- split.deps.zipWithIndex) dep match { case NarrowCoGroupSplitDep(rdd, _, itsSplit) => { // Read them from the parent - for ((k, v) <- rdd.iterator(itsSplit, context)) { - getSeq(k.asInstanceOf[K])(depNum) += v + rdd.iterator(itsSplit, context).asInstanceOf[Iterator[Product2[K, Any]]].foreach { kv => + getSeq(kv._1)(depNum) += kv._2 } } case ShuffleCoGroupSplitDep(shuffleId) => { // Read map outputs of shuffle val fetcher = SparkEnv.get.shuffleFetcher - if (mapSideCombine) { - // With map side combine on, for each key, the shuffle fetcher returns a list of values. - fetcher.fetch[K, Seq[Any]](shuffleId, split.index, context.taskMetrics, ser).foreach { - case (key, values) => getSeq(key)(depNum) ++= values - } - } else { - // With map side combine off, for each key the shuffle fetcher returns a single value. - fetcher.fetch[K, Any](shuffleId, split.index, context.taskMetrics, ser).foreach { - case (key, value) => getSeq(key)(depNum) += value - } + fetcher.fetch[Product2[K, Any]](shuffleId, split.index, context.taskMetrics, ser).foreach { + kv => getSeq(kv._1)(depNum) += kv._2 } } } diff --git a/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala new file mode 100644 index 0000000000..c5de6362a9 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/CoalescedRDD.scala @@ -0,0 +1,342 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark._ +import java.io.{ObjectOutputStream, IOException} +import scala.collection.mutable +import scala.Some +import scala.collection.mutable.ArrayBuffer + +/** + * Class that captures a coalesced RDD by essentially keeping track of parent partitions + * @param index of this coalesced partition + * @param rdd which it belongs to + * @param parentsIndices list of indices in the parent that have been coalesced into this partition + * @param preferredLocation the preferred location for this partition + */ +case class CoalescedRDDPartition( + index: Int, + @transient rdd: RDD[_], + parentsIndices: Array[Int], + @transient preferredLocation: String = "" + ) extends Partition { + var parents: Seq[Partition] = parentsIndices.map(rdd.partitions(_)) + + @throws(classOf[IOException]) + private def writeObject(oos: ObjectOutputStream) { + // Update the reference to parent partition at the time of task serialization + parents = parentsIndices.map(rdd.partitions(_)) + oos.defaultWriteObject() + } + + /** + * Computes how many of the parents partitions have getPreferredLocation + * as one of their preferredLocations + * @return locality of this coalesced partition between 0 and 1 + */ + def localFraction: Double = { + val loc = parents.count(p => + rdd.context.getPreferredLocs(rdd, p.index).map(tl => tl.host).contains(preferredLocation)) + + if (parents.size == 0) 0.0 else (loc.toDouble / parents.size.toDouble) + } +} + +/** + * Represents a coalesced RDD that has fewer partitions than its parent RDD + * This class uses the PartitionCoalescer class to find a good partitioning of the parent RDD + * so that each new partition has roughly the same number of parent partitions and that + * the preferred location of each new partition overlaps with as many preferred locations of its + * parent partitions + * @param prev RDD to be coalesced + * @param maxPartitions number of desired partitions in the coalesced RDD + * @param balanceSlack used to trade-off balance and locality. 1.0 is all locality, 0 is all balance + */ +class CoalescedRDD[T: ClassManifest]( + @transient var prev: RDD[T], + maxPartitions: Int, + balanceSlack: Double = 0.10) + extends RDD[T](prev.context, Nil) { // Nil since we implement getDependencies + + override def getPartitions: Array[Partition] = { + val pc = new PartitionCoalescer(maxPartitions, prev, balanceSlack) + + pc.run().zipWithIndex.map { + case (pg, i) => + val ids = pg.arr.map(_.index).toArray + new CoalescedRDDPartition(i, prev, ids, pg.prefLoc) + } + } + + override def compute(partition: Partition, context: TaskContext): Iterator[T] = { + partition.asInstanceOf[CoalescedRDDPartition].parents.iterator.flatMap { parentPartition => + firstParent[T].iterator(parentPartition, context) + } + } + + override def getDependencies: Seq[Dependency[_]] = { + Seq(new NarrowDependency(prev) { + def getParents(id: Int): Seq[Int] = + partitions(id).asInstanceOf[CoalescedRDDPartition].parentsIndices + }) + } + + override def clearDependencies() { + super.clearDependencies() + prev = null + } + + /** + * Returns the preferred machine for the partition. If split is of type CoalescedRDDPartition, + * then the preferred machine will be one which most parent splits prefer too. + * @param partition + * @return the machine most preferred by split + */ + override def getPreferredLocations(partition: Partition): Seq[String] = { + List(partition.asInstanceOf[CoalescedRDDPartition].preferredLocation) + } +} + +/** + * Coalesce the partitions of a parent RDD (`prev`) into fewer partitions, so that each partition of + * this RDD computes one or more of the parent ones. It will produce exactly `maxPartitions` if the + * parent had more than maxPartitions, or fewer if the parent had fewer. + * + * This transformation is useful when an RDD with many partitions gets filtered into a smaller one, + * or to avoid having a large number of small tasks when processing a directory with many files. + * + * If there is no locality information (no preferredLocations) in the parent, then the coalescing + * is very simple: chunk parents that are close in the Array in chunks. + * If there is locality information, it proceeds to pack them with the following four goals: + * + * (1) Balance the groups so they roughly have the same number of parent partitions + * (2) Achieve locality per partition, i.e. find one machine which most parent partitions prefer + * (3) Be efficient, i.e. O(n) algorithm for n parent partitions (problem is likely NP-hard) + * (4) Balance preferred machines, i.e. avoid as much as possible picking the same preferred machine + * + * Furthermore, it is assumed that the parent RDD may have many partitions, e.g. 100 000. + * We assume the final number of desired partitions is small, e.g. less than 1000. + * + * The algorithm tries to assign unique preferred machines to each partition. If the number of + * desired partitions is greater than the number of preferred machines (can happen), it needs to + * start picking duplicate preferred machines. This is determined using coupon collector estimation + * (2n log(n)). The load balancing is done using power-of-two randomized bins-balls with one twist: + * it tries to also achieve locality. This is done by allowing a slack (balanceSlack) between two + * bins. If two bins are within the slack in terms of balance, the algorithm will assign partitions + * according to locality. (contact alig for questions) + * + */ + +private[spark] class PartitionCoalescer(maxPartitions: Int, prev: RDD[_], balanceSlack: Double) { + + def compare(o1: PartitionGroup, o2: PartitionGroup): Boolean = o1.size < o2.size + def compare(o1: Option[PartitionGroup], o2: Option[PartitionGroup]): Boolean = + if (o1 == None) false else if (o2 == None) true else compare(o1.get, o2.get) + + val rnd = new scala.util.Random(7919) // keep this class deterministic + + // each element of groupArr represents one coalesced partition + val groupArr = ArrayBuffer[PartitionGroup]() + + // hash used to check whether some machine is already in groupArr + val groupHash = mutable.Map[String, ArrayBuffer[PartitionGroup]]() + + // hash used for the first maxPartitions (to avoid duplicates) + val initialHash = mutable.Set[Partition]() + + // determines the tradeoff between load-balancing the partitions sizes and their locality + // e.g. balanceSlack=0.10 means that it allows up to 10% imbalance in favor of locality + val slack = (balanceSlack * prev.partitions.size).toInt + + var noLocality = true // if true if no preferredLocations exists for parent RDD + + // gets the *current* preferred locations from the DAGScheduler (as opposed to the static ones) + def currPrefLocs(part: Partition): Seq[String] = { + prev.context.getPreferredLocs(prev, part.index).map(tl => tl.host) + } + + // this class just keeps iterating and rotating infinitely over the partitions of the RDD + // next() returns the next preferred machine that a partition is replicated on + // the rotator first goes through the first replica copy of each partition, then second, third + // the iterators return type is a tuple: (replicaString, partition) + class LocationIterator(prev: RDD[_]) extends Iterator[(String, Partition)] { + + var it: Iterator[(String, Partition)] = resetIterator() + + override val isEmpty = !it.hasNext + + // initializes/resets to start iterating from the beginning + def resetIterator() = { + val iterators = (0 to 2).map( x => + prev.partitions.iterator.flatMap(p => { + if (currPrefLocs(p).size > x) Some((currPrefLocs(p)(x), p)) else None + } ) + ) + iterators.reduceLeft((x, y) => x ++ y) + } + + // hasNext() is false iff there are no preferredLocations for any of the partitions of the RDD + def hasNext(): Boolean = { !isEmpty } + + // return the next preferredLocation of some partition of the RDD + def next(): (String, Partition) = { + if (it.hasNext) + it.next() + else { + it = resetIterator() // ran out of preferred locations, reset and rotate to the beginning + it.next() + } + } + } + + /** + * Sorts and gets the least element of the list associated with key in groupHash + * The returned PartitionGroup is the least loaded of all groups that represent the machine "key" + * @param key string representing a partitioned group on preferred machine key + * @return Option of PartitionGroup that has least elements for key + */ + def getLeastGroupHash(key: String): Option[PartitionGroup] = { + groupHash.get(key).map(_.sortWith(compare).head) + } + + def addPartToPGroup(part: Partition, pgroup: PartitionGroup): Boolean = { + if (!initialHash.contains(part)) { + pgroup.arr += part // already assign this element + initialHash += part // needed to avoid assigning partitions to multiple buckets + true + } else { false } + } + + /** + * Initializes targetLen partition groups and assigns a preferredLocation + * This uses coupon collector to estimate how many preferredLocations it must rotate through + * until it has seen most of the preferred locations (2 * n log(n)) + * @param targetLen + */ + def setupGroups(targetLen: Int) { + val rotIt = new LocationIterator(prev) + + // deal with empty case, just create targetLen partition groups with no preferred location + if (!rotIt.hasNext()) { + (1 to targetLen).foreach(x => groupArr += PartitionGroup()) + return + } + + noLocality = false + + // number of iterations needed to be certain that we've seen most preferred locations + val expectedCoupons2 = 2 * (math.log(targetLen)*targetLen + targetLen + 0.5).toInt + var numCreated = 0 + var tries = 0 + + // rotate through until either targetLen unique/distinct preferred locations have been created + // OR we've rotated expectedCoupons2, in which case we have likely seen all preferred locations, + // i.e. likely targetLen >> number of preferred locations (more buckets than there are machines) + while (numCreated < targetLen && tries < expectedCoupons2) { + tries += 1 + val (nxt_replica, nxt_part) = rotIt.next() + if (!groupHash.contains(nxt_replica)) { + val pgroup = PartitionGroup(nxt_replica) + groupArr += pgroup + addPartToPGroup(nxt_part, pgroup) + groupHash += (nxt_replica -> (ArrayBuffer(pgroup))) // list in case we have multiple + numCreated += 1 + } + } + + while (numCreated < targetLen) { // if we don't have enough partition groups, create duplicates + var (nxt_replica, nxt_part) = rotIt.next() + val pgroup = PartitionGroup(nxt_replica) + groupArr += pgroup + groupHash.get(nxt_replica).get += pgroup + var tries = 0 + while (!addPartToPGroup(nxt_part, pgroup) && tries < targetLen) { // ensure at least one part + nxt_part = rotIt.next()._2 + tries += 1 + } + numCreated += 1 + } + + } + + /** + * Takes a parent RDD partition and decides which of the partition groups to put it in + * Takes locality into account, but also uses power of 2 choices to load balance + * It strikes a balance between the two use the balanceSlack variable + * @param p partition (ball to be thrown) + * @return partition group (bin to be put in) + */ + def pickBin(p: Partition): PartitionGroup = { + val pref = currPrefLocs(p).map(getLeastGroupHash(_)).sortWith(compare) // least loaded pref locs + val prefPart = if (pref == Nil) None else pref.head + + val r1 = rnd.nextInt(groupArr.size) + val r2 = rnd.nextInt(groupArr.size) + val minPowerOfTwo = if (groupArr(r1).size < groupArr(r2).size) groupArr(r1) else groupArr(r2) + if (prefPart== None) // if no preferred locations, just use basic power of two + return minPowerOfTwo + + val prefPartActual = prefPart.get + + if (minPowerOfTwo.size + slack <= prefPartActual.size) // more imbalance than the slack allows + return minPowerOfTwo // prefer balance over locality + else { + return prefPartActual // prefer locality over balance + } + } + + def throwBalls() { + if (noLocality) { // no preferredLocations in parent RDD, no randomization needed + if (maxPartitions > groupArr.size) { // just return prev.partitions + for ((p,i) <- prev.partitions.zipWithIndex) { + groupArr(i).arr += p + } + } else { // no locality available, then simply split partitions based on positions in array + for(i <- 0 until maxPartitions) { + val rangeStart = ((i.toLong * prev.partitions.length) / maxPartitions).toInt + val rangeEnd = (((i.toLong + 1) * prev.partitions.length) / maxPartitions).toInt + (rangeStart until rangeEnd).foreach{ j => groupArr(i).arr += prev.partitions(j) } + } + } + } else { + for (p <- prev.partitions if (!initialHash.contains(p))) { // throw every partition into group + pickBin(p).arr += p + } + } + } + + def getPartitions: Array[PartitionGroup] = groupArr.filter( pg => pg.size > 0).toArray + + /** + * Runs the packing algorithm and returns an array of PartitionGroups that if possible are + * load balanced and grouped by locality + * @return array of partition groups + */ + def run(): Array[PartitionGroup] = { + setupGroups(math.min(prev.partitions.length, maxPartitions)) // setup the groups (bins) + throwBalls() // assign partitions (balls) to each group (bins) + getPartitions + } +} + +private[spark] case class PartitionGroup(prefLoc: String = "") { + var arr = mutable.ArrayBuffer[Partition]() + + def size = arr.size +} diff --git a/core/src/main/scala/spark/DoubleRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala index 178d31a73b..a4bec41752 100644 --- a/core/src/main/scala/spark/DoubleRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/DoubleRDDFunctions.scala @@ -1,14 +1,32 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd -import spark.partial.BoundedDouble -import spark.partial.MeanEvaluator -import spark.partial.PartialResult -import spark.partial.SumEvaluator -import spark.util.StatCounter +import org.apache.spark.partial.BoundedDouble +import org.apache.spark.partial.MeanEvaluator +import org.apache.spark.partial.PartialResult +import org.apache.spark.partial.SumEvaluator +import org.apache.spark.util.StatCounter +import org.apache.spark.{TaskContext, Logging} /** * Extra functions available on RDDs of Doubles through an implicit conversion. - * Import `spark.SparkContext._` at the top of your program to use these functions. + * Import `org.apache.spark.SparkContext._` at the top of your program to use these functions. */ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable { /** Add up the elements in this RDD. */ @@ -17,7 +35,7 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable { } /** - * Return a [[spark.util.StatCounter]] object that captures the mean, variance and count + * Return a [[org.apache.spark.util.StatCounter]] object that captures the mean, variance and count * of the RDD's elements in one operation. */ def stats(): StatCounter = { @@ -37,7 +55,13 @@ class DoubleRDDFunctions(self: RDD[Double]) extends Logging with Serializable { * Compute the sample standard deviation of this RDD's elements (which corrects for bias in * estimating the standard deviation by dividing by N-1 instead of N). */ - def sampleStdev(): Double = stats().stdev + def sampleStdev(): Double = stats().sampleStdev + + /** + * Compute the sample variance of this RDD's elements (which corrects for bias in + * estimating the variance by dividing by N-1 instead of N). + */ + def sampleVariance(): Double = stats().sampleVariance /** (Experimental) Approximate operation to return the mean within a timeout. */ def meanApprox(timeout: Long, confidence: Double = 0.95): PartialResult[BoundedDouble] = { diff --git a/core/src/main/scala/org/apache/spark/rdd/EmptyRDD.scala b/core/src/main/scala/org/apache/spark/rdd/EmptyRDD.scala new file mode 100644 index 0000000000..c8900d1a93 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/EmptyRDD.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{SparkContext, SparkEnv, Partition, TaskContext} + + +/** + * An RDD that is empty, i.e. has no element in it. + */ +class EmptyRDD[T: ClassManifest](sc: SparkContext) extends RDD[T](sc, Nil) { + + override def getPartitions: Array[Partition] = Array.empty + + override def compute(split: Partition, context: TaskContext): Iterator[T] = { + throw new UnsupportedOperationException("empty RDD") + } +} diff --git a/core/src/main/scala/org/apache/spark/rdd/FilteredRDD.scala b/core/src/main/scala/org/apache/spark/rdd/FilteredRDD.scala new file mode 100644 index 0000000000..5312dc0b59 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/FilteredRDD.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{OneToOneDependency, Partition, TaskContext} + +private[spark] class FilteredRDD[T: ClassManifest]( + prev: RDD[T], + f: T => Boolean) + extends RDD[T](prev) { + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override val partitioner = prev.partitioner // Since filter cannot change a partition's keys + + override def compute(split: Partition, context: TaskContext) = + firstParent[T].iterator(split, context).filter(f) +} diff --git a/core/src/main/scala/org/apache/spark/rdd/FlatMappedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/FlatMappedRDD.scala new file mode 100644 index 0000000000..cbdf6d84c0 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/FlatMappedRDD.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Partition, TaskContext} + + +private[spark] +class FlatMappedRDD[U: ClassManifest, T: ClassManifest]( + prev: RDD[T], + f: T => TraversableOnce[U]) + extends RDD[U](prev) { + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override def compute(split: Partition, context: TaskContext) = + firstParent[T].iterator(split, context).flatMap(f) +} diff --git a/core/src/main/scala/org/apache/spark/rdd/FlatMappedValuesRDD.scala b/core/src/main/scala/org/apache/spark/rdd/FlatMappedValuesRDD.scala new file mode 100644 index 0000000000..82000bac09 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/FlatMappedValuesRDD.scala @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{TaskContext, Partition} + + +private[spark] +class FlatMappedValuesRDD[K, V, U](prev: RDD[_ <: Product2[K, V]], f: V => TraversableOnce[U]) + extends RDD[(K, U)](prev) { + + override def getPartitions = firstParent[Product2[K, V]].partitions + + override val partitioner = firstParent[Product2[K, V]].partitioner + + override def compute(split: Partition, context: TaskContext) = { + firstParent[Product2[K, V]].iterator(split, context).flatMap { case Product2(k, v) => + f(v).map(x => (k, x)) + } + } +} diff --git a/core/src/main/scala/org/apache/spark/rdd/GlommedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/GlommedRDD.scala new file mode 100644 index 0000000000..829545d7b0 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/GlommedRDD.scala @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Partition, TaskContext} + +private[spark] class GlommedRDD[T: ClassManifest](prev: RDD[T]) + extends RDD[Array[T]](prev) { + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override def compute(split: Partition, context: TaskContext) = + Array(firstParent[T].iterator(split, context).toArray).iterator +} diff --git a/core/src/main/scala/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala index 07c103503c..2cb6734e41 100644 --- a/core/src/main/scala/spark/rdd/HadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala @@ -1,24 +1,34 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.io.EOFException -import java.util.NoSuchElementException -import org.apache.hadoop.io.LongWritable -import org.apache.hadoop.io.NullWritable -import org.apache.hadoop.io.Text -import org.apache.hadoop.mapred.FileInputFormat import org.apache.hadoop.mapred.InputFormat import org.apache.hadoop.mapred.InputSplit import org.apache.hadoop.mapred.JobConf -import org.apache.hadoop.mapred.TextInputFormat import org.apache.hadoop.mapred.RecordReader import org.apache.hadoop.mapred.Reporter import org.apache.hadoop.util.ReflectionUtils -import spark.deploy.SparkHadoopUtil -import spark.{Dependency, Logging, Partition, RDD, SerializableWritable, SparkContext, TaskContext} -import spark.util.NextIterator -import org.apache.hadoop.conf.Configurable +import org.apache.spark.{Logging, Partition, SerializableWritable, SparkContext, SparkEnv, TaskContext} +import org.apache.spark.util.NextIterator +import org.apache.hadoop.conf.{Configuration, Configurable} /** @@ -51,7 +61,8 @@ class HadoopRDD[K, V]( private val confBroadcast = sc.broadcast(new SerializableWritable(conf)) override def getPartitions: Array[Partition] = { - SparkHadoopUtil.addCredentials(conf); + val env = SparkEnv.get + env.hadoop.addCredentials(conf) val inputFormat = createInputFormat(conf) if (inputFormat.isInstanceOf[Configurable]) { inputFormat.asInstanceOf[Configurable].setConf(conf) @@ -71,6 +82,7 @@ class HadoopRDD[K, V]( override def compute(theSplit: Partition, context: TaskContext) = new NextIterator[(K, V)] { val split = theSplit.asInstanceOf[HadoopPartition] + logInfo("Input split: " + split.inputSplit) var reader: RecordReader[K, V] = null val conf = confBroadcast.value.value @@ -114,4 +126,6 @@ class HadoopRDD[K, V]( override def checkpoint() { // Do nothing. Hadoop RDD should not be checkpointed. } + + def getConf: Configuration = confBroadcast.value.value } diff --git a/core/src/main/scala/spark/rdd/JdbcRDD.scala b/core/src/main/scala/org/apache/spark/rdd/JdbcRDD.scala index f570dd6d8b..e72f86fb13 100644 --- a/core/src/main/scala/spark/rdd/JdbcRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/JdbcRDD.scala @@ -1,10 +1,27 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.sql.{Connection, ResultSet} -import spark.{Logging, Partition, RDD, SparkContext, TaskContext} -import spark.util.NextIterator import scala.reflect.ClassTag +import org.apache.spark.{Logging, Partition, SparkContext, TaskContext} +import org.apache.spark.util.NextIterator private[spark] class JdbcPartition(idx: Int, val lower: Long, val upper: Long) extends Partition { override def index = idx diff --git a/core/src/main/scala/org/apache/spark/rdd/MapPartitionsRDD.scala b/core/src/main/scala/org/apache/spark/rdd/MapPartitionsRDD.scala new file mode 100644 index 0000000000..203179c4ea --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/MapPartitionsRDD.scala @@ -0,0 +1,37 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Partition, TaskContext} + + +private[spark] +class MapPartitionsRDD[U: ClassManifest, T: ClassManifest]( + prev: RDD[T], + f: Iterator[T] => Iterator[U], + preservesPartitioning: Boolean = false) + extends RDD[U](prev) { + + override val partitioner = + if (preservesPartitioning) firstParent[T].partitioner else None + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override def compute(split: Partition, context: TaskContext) = + f(firstParent[T].iterator(split, context)) +} diff --git a/core/src/main/scala/org/apache/spark/rdd/MapPartitionsWithIndexRDD.scala b/core/src/main/scala/org/apache/spark/rdd/MapPartitionsWithIndexRDD.scala new file mode 100644 index 0000000000..3ed8339010 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/MapPartitionsWithIndexRDD.scala @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Partition, TaskContext} + + +/** + * A variant of the MapPartitionsRDD that passes the partition index into the + * closure. This can be used to generate or collect partition specific + * information such as the number of tuples in a partition. + */ +private[spark] +class MapPartitionsWithIndexRDD[U: ClassManifest, T: ClassManifest]( + prev: RDD[T], + f: (Int, Iterator[T]) => Iterator[U], + preservesPartitioning: Boolean + ) extends RDD[U](prev) { + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override val partitioner = if (preservesPartitioning) prev.partitioner else None + + override def compute(split: Partition, context: TaskContext) = + f(split.index, firstParent[T].iterator(split, context)) +} diff --git a/core/src/main/scala/org/apache/spark/rdd/MappedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/MappedRDD.scala new file mode 100644 index 0000000000..e8be1c4816 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/MappedRDD.scala @@ -0,0 +1,30 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Partition, TaskContext} + +private[spark] +class MappedRDD[U: ClassManifest, T: ClassManifest](prev: RDD[T], f: T => U) + extends RDD[U](prev) { + + override def getPartitions: Array[Partition] = firstParent[T].partitions + + override def compute(split: Partition, context: TaskContext) = + firstParent[T].iterator(split, context).map(f) +} diff --git a/core/src/main/scala/org/apache/spark/rdd/MappedValuesRDD.scala b/core/src/main/scala/org/apache/spark/rdd/MappedValuesRDD.scala new file mode 100644 index 0000000000..d33c1af581 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/MappedValuesRDD.scala @@ -0,0 +1,34 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + + +import org.apache.spark.{TaskContext, Partition} + +private[spark] +class MappedValuesRDD[K, V, U](prev: RDD[_ <: Product2[K, V]], f: V => U) + extends RDD[(K, U)](prev) { + + override def getPartitions = firstParent[Product2[K, U]].partitions + + override val partitioner = firstParent[Product2[K, U]].partitioner + + override def compute(split: Partition, context: TaskContext): Iterator[(K, U)] = { + firstParent[Product2[K, V]].iterator(split, context).map { case Product2(k ,v) => (k, f(v)) } + } +} diff --git a/core/src/main/scala/spark/rdd/NewHadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala index 901d01ef30..7b3a89f7e0 100644 --- a/core/src/main/scala/spark/rdd/NewHadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.text.SimpleDateFormat import java.util.Date @@ -7,7 +24,7 @@ import org.apache.hadoop.conf.{Configurable, Configuration} import org.apache.hadoop.io.Writable import org.apache.hadoop.mapreduce._ -import spark.{Dependency, Logging, Partition, RDD, SerializableWritable, SparkContext, TaskContext} +import org.apache.spark.{Dependency, Logging, Partition, SerializableWritable, SparkContext, TaskContext} private[spark] @@ -26,7 +43,7 @@ class NewHadoopRDD[K, V]( valueClass: Class[V], @transient conf: Configuration) extends RDD[(K, V)](sc, Nil) - with HadoopMapReduceUtil + with SparkHadoopMapReduceUtil with Logging { // A Hadoop Configuration can be about 10 KB, which is pretty big, so broadcast it @@ -56,6 +73,7 @@ class NewHadoopRDD[K, V]( override def compute(theSplit: Partition, context: TaskContext) = new Iterator[(K, V)] { val split = theSplit.asInstanceOf[NewHadoopPartition] + logInfo("Input split: " + split.serializableHadoopSplit) val conf = confBroadcast.value.value val attemptId = newTaskAttemptID(jobtrackerId, id, true, split.index, 0) val hadoopAttemptContext = newTaskAttemptContext(conf, attemptId) @@ -102,4 +120,7 @@ class NewHadoopRDD[K, V]( val theSplit = split.asInstanceOf[NewHadoopPartition] theSplit.serializableHadoopSplit.value.getLocations.filter(_ != "localhost") } + + def getConf: Configuration = confBroadcast.value.value } + diff --git a/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala new file mode 100644 index 0000000000..697be8b997 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala @@ -0,0 +1,52 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{RangePartitioner, Logging} + +/** + * Extra functions available on RDDs of (key, value) pairs where the key is sortable through + * an implicit conversion. Import `org.apache.spark.SparkContext._` at the top of your program to + * use these functions. They will work with any key type that has a `scala.math.Ordered` + * implementation. + */ +class OrderedRDDFunctions[K <% Ordered[K]: ClassManifest, + V: ClassManifest, + P <: Product2[K, V] : ClassManifest]( + self: RDD[P]) + extends Logging with Serializable { + + /** + * Sort the RDD by key, so that each partition contains a sorted range of the elements. Calling + * `collect` or `save` on the resulting RDD will return or output an ordered list of records + * (in the `save` case, they will be written to multiple `part-X` files in the filesystem, in + * order of the keys). + */ + def sortByKey(ascending: Boolean = true, numPartitions: Int = self.partitions.size): RDD[P] = { + val part = new RangePartitioner(numPartitions, self, ascending) + val shuffled = new ShuffledRDD[K, V, P](self, part) + shuffled.mapPartitions(iter => { + val buf = iter.toArray + if (ascending) { + buf.sortWith((x, y) => x._1 < y._1).iterator + } else { + buf.sortWith((x, y) => x._1 > y._1).iterator + } + }, preservesPartitioning = true) + } +} diff --git a/core/src/main/scala/spark/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index ee09c2085b..aed585e6a1 100644 --- a/core/src/main/scala/spark/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -1,43 +1,59 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.nio.ByteBuffer -import java.util.{Date, HashMap => JHashMap} +import java.util.Date import java.text.SimpleDateFormat +import java.util.{HashMap => JHashMap} -import scala.collection.Map +import scala.collection.{mutable, Map} import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap import scala.collection.JavaConversions._ import scala.reflect.{ ClassTag, classTag} +import org.apache.hadoop.mapred._ +import org.apache.hadoop.io.compress.CompressionCodec import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.hadoop.io.compress.CompressionCodec import org.apache.hadoop.io.SequenceFile.CompressionType -import org.apache.hadoop.mapred.FileOutputCommitter import org.apache.hadoop.mapred.FileOutputFormat -import org.apache.hadoop.mapred.HadoopWriter -import org.apache.hadoop.mapred.JobConf import org.apache.hadoop.mapred.OutputFormat - +import org.apache.hadoop.mapreduce.{OutputFormat => NewOutputFormat} import org.apache.hadoop.mapreduce.lib.output.{FileOutputFormat => NewFileOutputFormat} -import org.apache.hadoop.mapreduce.{OutputFormat => NewOutputFormat, RecordWriter => NewRecordWriter, Job => NewAPIHadoopJob, HadoopMapReduceUtil} -import org.apache.hadoop.security.UserGroupInformation +import org.apache.hadoop.mapreduce.SparkHadoopMapReduceUtil +import org.apache.hadoop.mapreduce.{Job => NewAPIHadoopJob} +import org.apache.hadoop.mapreduce.{RecordWriter => NewRecordWriter} -import spark.partial.BoundedDouble -import spark.partial.PartialResult -import spark.rdd._ -import spark.SparkContext._ -import spark.Partitioner._ +import org.apache.spark._ +import org.apache.spark.SparkContext._ +import org.apache.spark.partial.{BoundedDouble, PartialResult} +import org.apache.spark.Aggregator +import org.apache.spark.Partitioner +import org.apache.spark.Partitioner.defaultPartitioner /** * Extra functions available on RDDs of (key, value) pairs through an implicit conversion. - * Import `spark.SparkContext._` at the top of your program to use these functions. + * Import `org.apache.spark.SparkContext._` at the top of your program to use these functions. */ -class PairRDDFunctions[K: ClassTag, V: ClassTag]( - self: RDD[(K, V)]) +class PairRDDFunctions[K: ClassManifest, V: ClassManifest](self: RDD[(K, V)]) extends Logging - with HadoopMapReduceUtil + with SparkHadoopMapReduceUtil with Serializable { /** @@ -69,17 +85,18 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( } val aggregator = new Aggregator[K, V, C](createCombiner, mergeValue, mergeCombiners) if (self.partitioner == Some(partitioner)) { - self.mapPartitions(aggregator.combineValuesByKey(_), true) + self.mapPartitions(aggregator.combineValuesByKey, preservesPartitioning = true) } else if (mapSideCombine) { - val mapSideCombined = self.mapPartitions(aggregator.combineValuesByKey(_), true) - val partitioned = new ShuffledRDD[K, C](mapSideCombined, partitioner, serializerClass) - partitioned.mapPartitions(aggregator.combineCombinersByKey(_), true) + val combined = self.mapPartitions(aggregator.combineValuesByKey, preservesPartitioning = true) + val partitioned = new ShuffledRDD[K, C, (K, C)](combined, partitioner) + .setSerializer(serializerClass) + partitioned.mapPartitions(aggregator.combineCombinersByKey, preservesPartitioning = true) } else { // Don't apply map-side combiner. // A sanity check to make sure mergeCombiners is not defined. assert(mergeCombiners == null) - val values = new ShuffledRDD[K, V](self, partitioner, serializerClass) - values.mapPartitions(aggregator.combineValuesByKey(_), true) + val values = new ShuffledRDD[K, V, (K, V)](self, partitioner).setSerializer(serializerClass) + values.mapPartitions(aggregator.combineValuesByKey, preservesPartitioning = true) } } @@ -151,7 +168,7 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( def reducePartition(iter: Iterator[(K, V)]): Iterator[JHashMap[K, V]] = { val map = new JHashMap[K, V] - for ((k, v) <- iter) { + iter.foreach { case (k, v) => val old = map.get(k) map.put(k, if (old == null) v else func(old, v)) } @@ -159,11 +176,11 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( } def mergeMaps(m1: JHashMap[K, V], m2: JHashMap[K, V]): JHashMap[K, V] = { - for ((k, v) <- m2) { + m2.foreach { case (k, v) => val old = m1.get(k) m1.put(k, if (old == null) v else func(old, v)) } - return m1 + m1 } self.mapPartitions(reducePartition).reduce(mergeMaps) @@ -217,31 +234,13 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( } /** - * Return a copy of the RDD partitioned using the specified partitioner. If `mapSideCombine` - * is true, Spark will group values of the same key together on the map side before the - * repartitioning, to only send each key over the network once. If a large number of - * duplicated keys are expected, and the size of the keys are large, `mapSideCombine` should - * be set to true. + * Return a copy of the RDD partitioned using the specified partitioner. */ - def partitionBy(partitioner: Partitioner, mapSideCombine: Boolean = false): RDD[(K, V)] = { - if (getKeyClass().isArray) { - if (mapSideCombine) { - throw new SparkException("Cannot use map-side combining with array keys.") - } - if (partitioner.isInstanceOf[HashPartitioner]) { - throw new SparkException("Default partitioner cannot partition array keys.") - } - } - if (mapSideCombine) { - def createCombiner(v: V) = ArrayBuffer(v) - def mergeValue(buf: ArrayBuffer[V], v: V) = buf += v - def mergeCombiners(b1: ArrayBuffer[V], b2: ArrayBuffer[V]) = b1 ++= b2 - val bufs = combineByKey[ArrayBuffer[V]]( - createCombiner _, mergeValue _, mergeCombiners _, partitioner) - bufs.flatMapValues(buf => buf) - } else { - new ShuffledRDD[K, V](self, partitioner) + def partitionBy(partitioner: Partitioner): RDD[(K, V)] = { + if (getKeyClass().isArray && partitioner.isInstanceOf[HashPartitioner]) { + throw new SparkException("Default partitioner cannot partition array keys.") } + new ShuffledRDD[K, V, (K, V)](self, partitioner) } /** @@ -250,9 +249,8 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( * (k, v2) is in `other`. Uses the given Partitioner to partition the output RDD. */ def join[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (V, W))] = { - this.cogroup(other, partitioner).flatMapValues { - case (vs, ws) => - for (v <- vs.iterator; w <- ws.iterator) yield (v, w) + this.cogroup(other, partitioner).flatMapValues { case (vs, ws) => + for (v <- vs.iterator; w <- ws.iterator) yield (v, w) } } @@ -263,13 +261,12 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( * partition the output RDD. */ def leftOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (V, Option[W]))] = { - this.cogroup(other, partitioner).flatMapValues { - case (vs, ws) => - if (ws.isEmpty) { - vs.iterator.map(v => (v, None)) - } else { - for (v <- vs.iterator; w <- ws.iterator) yield (v, Some(w)) - } + this.cogroup(other, partitioner).flatMapValues { case (vs, ws) => + if (ws.isEmpty) { + vs.iterator.map(v => (v, None)) + } else { + for (v <- vs.iterator; w <- ws.iterator) yield (v, Some(w)) + } } } @@ -281,13 +278,12 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( */ def rightOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner) : RDD[(K, (Option[V], W))] = { - this.cogroup(other, partitioner).flatMapValues { - case (vs, ws) => - if (vs.isEmpty) { - ws.iterator.map(w => (None, w)) - } else { - for (v <- vs.iterator; w <- ws.iterator) yield (Some(v), w) - } + this.cogroup(other, partitioner).flatMapValues { case (vs, ws) => + if (vs.isEmpty) { + ws.iterator.map(w => (None, w)) + } else { + for (v <- vs.iterator; w <- ws.iterator) yield (Some(v), w) + } } } @@ -379,7 +375,13 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( /** * Return the key-value pairs in this RDD to the master as a Map. */ - def collectAsMap(): Map[K, V] = HashMap(self.collect(): _*) + def collectAsMap(): Map[K, V] = { + val data = self.toArray() + val map = new mutable.HashMap[K, V] + map.sizeHint(data.length) + data.foreach { case (k, v) => map.put(k, v) } + map + } /** * Pass each value in the key-value pair RDD through a map function without changing the keys; @@ -407,13 +409,10 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( if (partitioner.isInstanceOf[HashPartitioner] && getKeyClass().isArray) { throw new SparkException("Default partitioner cannot partition array keys.") } - val cg = new CoGroupedRDD[K]( - Seq(self.asInstanceOf[RDD[(K, _)]], other.asInstanceOf[RDD[(K, _)]]), - partitioner) + val cg = new CoGroupedRDD[K](Seq(self, other), partitioner) val prfs = new PairRDDFunctions[K, Seq[Seq[_]]](cg)(classTag[K], ClassTags.seqSeqClassTag) - prfs.mapValues { - case Seq(vs, ws) => - (vs.asInstanceOf[Seq[V]], ws.asInstanceOf[Seq[W]]) + prfs.mapValues { case Seq(vs, ws) => + (vs.asInstanceOf[Seq[V]], ws.asInstanceOf[Seq[W]]) } } @@ -426,15 +425,10 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( if (partitioner.isInstanceOf[HashPartitioner] && getKeyClass().isArray) { throw new SparkException("Default partitioner cannot partition array keys.") } - val cg = new CoGroupedRDD[K]( - Seq(self.asInstanceOf[RDD[(K, _)]], - other1.asInstanceOf[RDD[(K, _)]], - other2.asInstanceOf[RDD[(K, _)]]), - partitioner) - val prfs = new PairRDDFunctions[K, Seq[Seq[_]]](cg)(classTag[K], ClassTags.seqSeqClassTag) - prfs.mapValues { - case Seq(vs, w1s, w2s) => - (vs.asInstanceOf[Seq[V]], w1s.asInstanceOf[Seq[W1]], w2s.asInstanceOf[Seq[W2]]) + val cg = new CoGroupedRDD[K](Seq(self, other1, other2), partitioner) + val prfs = new PairRDDFunctions[K, Seq[Seq[_]]](cg)(classTag[K], ClassTags.seqSeqClassTag) + prfs.mapValues { case Seq(vs, w1s, w2s) => + (vs.asInstanceOf[Seq[V]], w1s.asInstanceOf[Seq[W1]], w2s.asInstanceOf[Seq[W2]]) } } @@ -566,7 +560,7 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( val formatter = new SimpleDateFormat("yyyyMMddHHmm") val jobtrackerID = formatter.format(new Date()) val stageId = self.id - def writeShard(context: spark.TaskContext, iter: Iterator[(K,V)]): Int = { + def writeShard(context: TaskContext, iter: Iterator[(K,V)]): Int = { // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it // around by taking a mod. We expect that no task will be attempted 2 billion times. val attemptNumber = (context.attemptId % Int.MaxValue).toInt @@ -578,7 +572,7 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( committer.setupTask(hadoopContext) val writer = format.getRecordWriter(hadoopContext).asInstanceOf[NewRecordWriter[K,V]] while (iter.hasNext) { - val (k, v) = iter.next + val (k, v) = iter.next() writer.write(k, v) } writer.close(hadoopContext) @@ -636,7 +630,7 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( conf.set("mapred.output.compression.type", CompressionType.BLOCK.toString) } conf.setOutputCommitter(classOf[FileOutputCommitter]) - FileOutputFormat.setOutputPath(conf, HadoopWriter.createPathFromString(path, conf)) + FileOutputFormat.setOutputPath(conf, SparkHadoopWriter.createPathFromString(path, conf)) saveAsHadoopDataset(conf) } @@ -662,10 +656,10 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( logInfo("Saving as hadoop file of type (" + keyClass.getSimpleName+ ", " + valueClass.getSimpleName+ ")") - val writer = new HadoopWriter(conf) + val writer = new SparkHadoopWriter(conf) writer.preSetup() - def writeToFile(context: TaskContext, iter: Iterator[(K,V)]) { + def writeToFile(context: TaskContext, iter: Iterator[(K, V)]) { // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it // around by taking a mod. We expect that no task will be attempted 2 billion times. val attemptNumber = (context.attemptId % Int.MaxValue).toInt @@ -704,55 +698,6 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag]( private[spark] def getValueClass() = implicitly[ClassTag[V]].runtimeClass } -/** - * Extra functions available on RDDs of (key, value) pairs where the key is sortable through - * an implicit conversion. Import `spark.SparkContext._` at the top of your program to use these - * functions. They will work with any key type that has a `scala.math.Ordered` implementation. - */ -class OrderedRDDFunctions[K <% Ordered[K]: ClassTag, V: ClassTag]( - self: RDD[(K, V)]) - extends Logging - with Serializable { - - /** - * Sort the RDD by key, so that each partition contains a sorted range of the elements. Calling - * `collect` or `save` on the resulting RDD will return or output an ordered list of records - * (in the `save` case, they will be written to multiple `part-X` files in the filesystem, in - * order of the keys). - */ - def sortByKey(ascending: Boolean = true, numPartitions: Int = self.partitions.size): RDD[(K,V)] = { - val shuffled = - new ShuffledRDD[K, V](self, new RangePartitioner(numPartitions, self, ascending)) - shuffled.mapPartitions(iter => { - val buf = iter.toArray - if (ascending) { - buf.sortWith((x, y) => x._1 < y._1).iterator - } else { - buf.sortWith((x, y) => x._1 > y._1).iterator - } - }, true) - } -} - -private[spark] -class MappedValuesRDD[K, V, U](prev: RDD[(K, V)], f: V => U) extends RDD[(K, U)](prev) { - override def getPartitions = firstParent[(K, V)].partitions - override val partitioner = firstParent[(K, V)].partitioner - override def compute(split: Partition, context: TaskContext) = - firstParent[(K, V)].iterator(split, context).map{ case (k, v) => (k, f(v)) } -} - -private[spark] -class FlatMappedValuesRDD[K, V, U](prev: RDD[(K, V)], f: V => TraversableOnce[U]) - extends RDD[(K, U)](prev) { - - override def getPartitions = firstParent[(K, V)].partitions - override val partitioner = firstParent[(K, V)].partitioner - override def compute(split: Partition, context: TaskContext) = { - firstParent[(K, V)].iterator(split, context).flatMap { case (k, v) => f(v).map(x => (k, x)) } - } -} - private[spark] object ClassTags { val seqSeqClassTag = classTag[Seq[Seq[_]]] } diff --git a/core/src/main/scala/spark/rdd/ParallelCollectionRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala index 81dbcde227..78fe0cdcdb 100644 --- a/core/src/main/scala/spark/rdd/ParallelCollectionRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala @@ -1,17 +1,38 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.collection.immutable.NumericRange import scala.collection.mutable.ArrayBuffer import scala.collection.Map import scala.reflect.ClassTag -import spark.{RDD, TaskContext, SparkContext, Partition} +import org.apache.spark._ +import java.io._ +import scala.Serializable +import org.apache.spark.serializer.JavaSerializer +import org.apache.spark.util.Utils private[spark] class ParallelCollectionPartition[T: ClassTag]( - val rddId: Long, - val slice: Int, - values: Seq[T]) - extends Partition with Serializable { + var rddId: Long, + var slice: Int, + var values: Seq[T]) + extends Partition with Serializable { def iterator: Iterator[T] = values.iterator @@ -22,15 +43,49 @@ private[spark] class ParallelCollectionPartition[T: ClassTag]( case _ => false } - override val index: Int = slice + override def index: Int = slice + + @throws(classOf[IOException]) + private def writeObject(out: ObjectOutputStream): Unit = { + + val sfactory = SparkEnv.get.serializer + + // Treat java serializer with default action rather than going thru serialization, to avoid a + // separate serialization header. + + sfactory match { + case js: JavaSerializer => out.defaultWriteObject() + case _ => + out.writeLong(rddId) + out.writeInt(slice) + + val ser = sfactory.newInstance() + Utils.serializeViaNestedStream(out, ser)(_.writeObject(values)) + } + } + + @throws(classOf[IOException]) + private def readObject(in: ObjectInputStream): Unit = { + + val sfactory = SparkEnv.get.serializer + sfactory match { + case js: JavaSerializer => in.defaultReadObject() + case _ => + rddId = in.readLong() + slice = in.readInt() + + val ser = sfactory.newInstance() + Utils.deserializeViaNestedStream(in, ser)(ds => values = ds.readObject()) + } + } } private[spark] class ParallelCollectionRDD[T: ClassTag]( @transient sc: SparkContext, @transient data: Seq[T], numSlices: Int, - locationPrefs: Map[Int,Seq[String]]) - extends RDD[T](sc, Nil) { + locationPrefs: Map[Int, Seq[String]]) + extends RDD[T](sc, Nil) { // TODO: Right now, each split sends along its full data, even if later down the RDD chain it gets // cached. It might be worthwhile to write the data to a file in the DFS and read it in the split // instead. @@ -67,16 +122,17 @@ private object ParallelCollectionRDD { 1 } slice(new Range( - r.start, r.end + sign, r.step).asInstanceOf[Seq[T]], numSlices) + r.start, r.end + sign, r.step).asInstanceOf[Seq[T]], numSlices) } case r: Range => { (0 until numSlices).map(i => { val start = ((i * r.length.toLong) / numSlices).toInt - val end = (((i+1) * r.length.toLong) / numSlices).toInt + val end = (((i + 1) * r.length.toLong) / numSlices).toInt new Range(r.start + start * r.step, r.start + end * r.step, r.step) }).asInstanceOf[Seq[Seq[T]]] } - case nr: NumericRange[_] => { // For ranges of Long, Double, BigInteger, etc + case nr: NumericRange[_] => { + // For ranges of Long, Double, BigInteger, etc val slices = new ArrayBuffer[Seq[T]](numSlices) val sliceSize = (nr.size + numSlices - 1) / numSlices // Round up to catch everything var r = nr @@ -87,10 +143,10 @@ private object ParallelCollectionRDD { slices } case _ => { - val array = seq.toArray // To prevent O(n^2) operations for List etc + val array = seq.toArray // To prevent O(n^2) operations for List etc (0 until numSlices).map(i => { val start = ((i * array.length.toLong) / numSlices).toInt - val end = (((i+1) * array.length.toLong) / numSlices).toInt + val end = (((i + 1) * array.length.toLong) / numSlices).toInt array.slice(start, end).toSeq }) } diff --git a/core/src/main/scala/spark/rdd/PartitionPruningRDD.scala b/core/src/main/scala/org/apache/spark/rdd/PartitionPruningRDD.scala index 0afea33f8e..bb9b309a70 100644 --- a/core/src/main/scala/spark/rdd/PartitionPruningRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PartitionPruningRDD.scala @@ -1,7 +1,25 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.reflect.ClassTag -import spark.{NarrowDependency, RDD, SparkEnv, Partition, TaskContext} + +import org.apache.spark.{NarrowDependency, SparkEnv, Partition, TaskContext} class PartitionPruningRDDPartition(idx: Int, val parentSplit: Partition) extends Partition { @@ -17,8 +35,9 @@ class PruneDependency[T](rdd: RDD[T], @transient partitionFilterFunc: Int => Boo extends NarrowDependency[T](rdd) { @transient - val partitions: Array[Partition] = rdd.partitions.filter(s => partitionFilterFunc(s.index)) - .zipWithIndex.map { case(split, idx) => new PartitionPruningRDDPartition(idx, split) : Partition } + val partitions: Array[Partition] = rdd.partitions.zipWithIndex + .filter(s => partitionFilterFunc(s._2)) + .map { case(split, idx) => new PartitionPruningRDDPartition(idx, split) : Partition } override def getParents(partitionId: Int) = List(partitions(partitionId).index) } diff --git a/core/src/main/scala/spark/rdd/PipedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala index 349e6162c4..1dbbe39898 100644 --- a/core/src/main/scala/spark/rdd/PipedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.io.PrintWriter import java.util.StringTokenizer @@ -9,8 +26,8 @@ import scala.collection.mutable.ArrayBuffer import scala.io.Source import scala.reflect.ClassTag -import spark.{RDD, SparkEnv, Partition, TaskContext} -import spark.broadcast.Broadcast +import org.apache.spark.{SparkEnv, Partition, TaskContext} +import org.apache.spark.broadcast.Broadcast /** diff --git a/core/src/main/scala/spark/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index 2ebfaadc46..70c967f4bf 100644 --- a/core/src/main/scala/spark/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.util.Random @@ -17,43 +34,28 @@ import org.apache.hadoop.mapred.TextOutputFormat import it.unimi.dsi.fastutil.objects.{Object2LongOpenHashMap => OLMap} -import spark.broadcast.Broadcast -import spark.Partitioner._ -import spark.partial.BoundedDouble -import spark.partial.CountEvaluator -import spark.partial.GroupedCountEvaluator -import spark.partial.PartialResult -import spark.rdd.CoalescedRDD -import spark.rdd.CartesianRDD -import spark.rdd.FilteredRDD -import spark.rdd.FlatMappedRDD -import spark.rdd.GlommedRDD -import spark.rdd.MappedRDD -import spark.rdd.MapPartitionsRDD -import spark.rdd.MapPartitionsWithIndexRDD -import spark.rdd.PipedRDD -import spark.rdd.SampledRDD -import spark.rdd.ShuffledRDD -import spark.rdd.UnionRDD -import spark.rdd.ZippedRDD -import spark.rdd.ZippedPartitionsRDD2 -import spark.rdd.ZippedPartitionsRDD3 -import spark.rdd.ZippedPartitionsRDD4 -import spark.storage.StorageLevel -import spark.util.BoundedPriorityQueue - -import SparkContext._ +import org.apache.spark.Partitioner._ +import org.apache.spark.api.java.JavaRDD +import org.apache.spark.partial.BoundedDouble +import org.apache.spark.partial.CountEvaluator +import org.apache.spark.partial.GroupedCountEvaluator +import org.apache.spark.partial.PartialResult +import org.apache.spark.storage.StorageLevel +import org.apache.spark.util.{Utils, BoundedPriorityQueue} + +import org.apache.spark.SparkContext._ +import org.apache.spark._ /** * A Resilient Distributed Dataset (RDD), the basic abstraction in Spark. Represents an immutable, * partitioned collection of elements that can be operated on in parallel. This class contains the * basic operations available on all RDDs, such as `map`, `filter`, and `persist`. In addition, - * [[spark.PairRDDFunctions]] contains operations available only on RDDs of key-value pairs, such - * as `groupByKey` and `join`; [[spark.DoubleRDDFunctions]] contains operations available only on - * RDDs of Doubles; and [[spark.SequenceFileRDDFunctions]] contains operations available on RDDs - * that can be saved as SequenceFiles. These operations are automatically available on any RDD of - * the right type (e.g. RDD[(Int, Int)] through implicit conversions when you - * `import spark.SparkContext._`. + * [[org.apache.spark.rdd.PairRDDFunctions]] contains operations available only on RDDs of key-value + * pairs, such as `groupByKey` and `join`; [[org.apache.spark.rdd.DoubleRDDFunctions]] contains + * operations available only on RDDs of Doubles; and [[org.apache.spark.rdd.SequenceFileRDDFunctions]] + * contains operations available on RDDs that can be saved as SequenceFiles. These operations are + * automatically available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit + * conversions when you `import org.apache.spark.SparkContext._`. * * Internally, each RDD is characterized by five main properties: * @@ -206,8 +208,8 @@ abstract class RDD[T: ClassTag]( } /** - * Get the preferred location of a split, taking into account whether the - * RDD is checkpointed or not. + * Get the preferred locations of a partition (as hostnames), taking into account whether the + * RDD is checkpointed. */ final def preferredLocations(split: Partition): Seq[String] = { checkpointRDD.map(_.getPreferredLocations(split)).getOrElse { @@ -272,7 +274,10 @@ abstract class RDD[T: ClassTag]( def coalesce(numPartitions: Int, shuffle: Boolean = false): RDD[T] = { if (shuffle) { // include a shuffle step so that our upstream tasks are still distributed - new CoalescedRDD(new ShuffledRDD(map(x => (x, null)), new HashPartitioner(numPartitions)), numPartitions).keys + new CoalescedRDD( + new ShuffledRDD[T, Null, (T, Null)](map(x => (x, null)), + new HashPartitioner(numPartitions)), + numPartitions).keys } else { new CoalescedRDD(this, numPartitions) } @@ -287,8 +292,8 @@ abstract class RDD[T: ClassTag]( def takeSample(withReplacement: Boolean, num: Int, seed: Int): Array[T] = { var fraction = 0.0 var total = 0 - var multiplier = 3.0 - var initialCount = this.count() + val multiplier = 3.0 + val initialCount = this.count() var maxSelected = 0 if (num < 0) { @@ -500,22 +505,19 @@ abstract class RDD[T: ClassTag]( * *same number of partitions*, but does *not* require them to have the same number * of elements in each partition. */ - def zipPartitions[B: ClassTag, V: ClassTag]( - f: (Iterator[T], Iterator[B]) => Iterator[V], - rdd2: RDD[B]): RDD[V] = + def zipPartitions[B: ClassTag, V: ClassTag] + (rdd2: RDD[B]) + (f: (Iterator[T], Iterator[B]) => Iterator[V]): RDD[V] = new ZippedPartitionsRDD2(sc, sc.clean(f), this, rdd2) - def zipPartitions[B: ClassTag, C: ClassTag, V: ClassTag]( - f: (Iterator[T], Iterator[B], Iterator[C]) => Iterator[V], - rdd2: RDD[B], - rdd3: RDD[C]): RDD[V] = + def zipPartitions[B: ClassTag, C: ClassTag, V: ClassTag] + (rdd2: RDD[B], rdd3: RDD[C]) + (f: (Iterator[T], Iterator[B], Iterator[C]) => Iterator[V]): RDD[V] = new ZippedPartitionsRDD3(sc, sc.clean(f), this, rdd2, rdd3) - def zipPartitions[B: ClassTag, C: ClassTag, D: ClassTag, V: ClassTag]( - f: (Iterator[T], Iterator[B], Iterator[C], Iterator[D]) => Iterator[V], - rdd2: RDD[B], - rdd3: RDD[C], - rdd4: RDD[D]): RDD[V] = + def zipPartitions[B: ClassTag, C: ClassTag, D: ClassTag, V: ClassTag] + (rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D]) + (f: (Iterator[T], Iterator[B], Iterator[C], Iterator[D]) => Iterator[V]): RDD[V] = new ZippedPartitionsRDD4(sc, sc.clean(f), this, rdd2, rdd3, rdd4) @@ -879,7 +881,7 @@ abstract class RDD[T: ClassTag]( dependencies.head.rdd.asInstanceOf[RDD[U]] } - /** The [[spark.SparkContext]] that this RDD was created on. */ + /** The [[org.apache.spark.SparkContext]] that this RDD was created on. */ def context = sc // Avoid handling doCheckpoint multiple times to prevent excessive recursion @@ -915,7 +917,7 @@ abstract class RDD[T: ClassTag]( * Clears the dependencies of this RDD. This method must ensure that all references * to the original parent RDDs is removed to enable the parent RDDs to be garbage * collected. Subclasses of RDD may override this method for implementing their own cleaning - * logic. See [[spark.rdd.UnionRDD]] for an example. + * logic. See [[org.apache.spark.rdd.UnionRDD]] for an example. */ protected def clearDependencies() { dependencies_ = null @@ -936,4 +938,8 @@ abstract class RDD[T: ClassTag]( id, origin) + def toJavaRDD() : JavaRDD[T] = { + new JavaRDD(this)(elementClassTag) + } + } diff --git a/core/src/main/scala/spark/RDDCheckpointData.scala b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala index 5e7bb029eb..3b56e45aa9 100644 --- a/core/src/main/scala/spark/RDDCheckpointData.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala @@ -1,13 +1,29 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.reflect.ClassTag import org.apache.hadoop.fs.Path import org.apache.hadoop.conf.Configuration -import rdd.{CheckpointRDD, CoalescedRDD} - -import scheduler.{ResultTask, ShuffleMapTask} +import org.apache.spark.{Partition, SparkException, Logging} +import org.apache.spark.scheduler.{ResultTask, ShuffleMapTask} /** * Enumeration to manage state transitions of an RDD through checkpointing diff --git a/core/src/main/scala/spark/rdd/SampledRDD.scala b/core/src/main/scala/org/apache/spark/rdd/SampledRDD.scala index a503088f61..d433670cc2 100644 --- a/core/src/main/scala/spark/rdd/SampledRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/SampledRDD.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.reflect.ClassTag import java.util.Random @@ -6,7 +23,7 @@ import java.util.Random import cern.jet.random.Poisson import cern.jet.random.engine.DRand -import spark.{RDD, Partition, TaskContext} +import org.apache.spark.{Partition, TaskContext} private[spark] class SampledRDDPartition(val prev: Partition, val seed: Int) extends Partition with Serializable { diff --git a/core/src/main/scala/spark/SequenceFileRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/SequenceFileRDDFunctions.scala index edfde37da3..2d1bd5b481 100644 --- a/core/src/main/scala/spark/SequenceFileRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/SequenceFileRDDFunctions.scala @@ -1,38 +1,37 @@ -package spark - -import java.io.EOFException -import java.net.URL -import java.io.ObjectInputStream -import java.util.concurrent.atomic.AtomicLong -import java.util.HashSet -import java.util.Random -import java.util.Date +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.rdd -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.Map -import scala.collection.mutable.HashMap -import scala.reflect.{ classTag, ClassTag} +import scala.reflect.{ ClassTag, classTag} import org.apache.hadoop.mapred.JobConf -import org.apache.hadoop.mapred.OutputFormat -import org.apache.hadoop.mapred.TextOutputFormat import org.apache.hadoop.mapred.SequenceFileOutputFormat -import org.apache.hadoop.mapred.OutputCommitter -import org.apache.hadoop.mapred.FileOutputCommitter import org.apache.hadoop.io.compress.CompressionCodec import org.apache.hadoop.io.Writable -import org.apache.hadoop.io.NullWritable -import org.apache.hadoop.io.BytesWritable -import org.apache.hadoop.io.Text -import spark.SparkContext._ +import org.apache.spark.SparkContext._ +import org.apache.spark.Logging /** * Extra functions available on RDDs of (key, value) pairs to create a Hadoop SequenceFile, * through an implicit conversion. Note that this can't be part of PairRDDFunctions because * we need more implicit parameters to convert our keys and values to Writable. * - * Users should import `spark.SparkContext._` at the top of their program to use these functions. + * Import `org.apache.spark.SparkContext._` at the top of their program to use these functions. */ class SequenceFileRDDFunctions[K <% Writable: ClassTag, V <% Writable : ClassTag]( self: RDD[(K, V)]) diff --git a/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala new file mode 100644 index 0000000000..9537152335 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala @@ -0,0 +1,67 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{Dependency, Partitioner, SparkEnv, ShuffleDependency, Partition, TaskContext} + + +private[spark] class ShuffledRDDPartition(val idx: Int) extends Partition { + override val index = idx + override def hashCode(): Int = idx +} + +/** + * The resulting RDD from a shuffle (e.g. repartitioning of data). + * @param prev the parent RDD. + * @param part the partitioner used to partition the RDD + * @tparam K the key class. + * @tparam V the value class. + */ +class ShuffledRDD[K, V, P <: Product2[K, V] : ClassManifest]( + @transient var prev: RDD[P], + part: Partitioner) + extends RDD[P](prev.context, Nil) { + + private var serializerClass: String = null + + def setSerializer(cls: String): ShuffledRDD[K, V, P] = { + serializerClass = cls + this + } + + override def getDependencies: Seq[Dependency[_]] = { + List(new ShuffleDependency(prev, part, serializerClass)) + } + + override val partitioner = Some(part) + + override def getPartitions: Array[Partition] = { + Array.tabulate[Partition](part.numPartitions)(i => new ShuffledRDDPartition(i)) + } + + override def compute(split: Partition, context: TaskContext): Iterator[P] = { + val shuffledId = dependencies.head.asInstanceOf[ShuffleDependency[K, V]].shuffleId + SparkEnv.get.shuffleFetcher.fetch[P](shuffledId, split.index, context.taskMetrics, + SparkEnv.get.serializerManager.get(serializerClass)) + } + + override def clearDependencies() { + super.clearDependencies() + prev = null + } +} diff --git a/core/src/main/scala/spark/rdd/SubtractedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala index 9274839bca..85c512f3de 100644 --- a/core/src/main/scala/spark/rdd/SubtractedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import java.util.{HashMap => JHashMap} @@ -6,14 +23,13 @@ import scala.collection.JavaConversions._ import scala.collection.mutable.ArrayBuffer import scala.reflect.ClassTag -import spark.RDD -import spark.Partitioner -import spark.Dependency -import spark.TaskContext -import spark.Partition -import spark.SparkEnv -import spark.ShuffleDependency -import spark.OneToOneDependency +import org.apache.spark.Partitioner +import org.apache.spark.Dependency +import org.apache.spark.TaskContext +import org.apache.spark.Partition +import org.apache.spark.SparkEnv +import org.apache.spark.ShuffleDependency +import org.apache.spark.OneToOneDependency /** @@ -33,20 +49,26 @@ import spark.OneToOneDependency * out of memory because of the size of `rdd2`. */ private[spark] class SubtractedRDD[K: ClassTag, V: ClassTag, W: ClassTag]( - @transient var rdd1: RDD[(K, V)], - @transient var rdd2: RDD[(K, W)], - part: Partitioner, - val serializerClass: String = null) + @transient var rdd1: RDD[_ <: Product2[K, V]], + @transient var rdd2: RDD[_ <: Product2[K, W]], + part: Partitioner) extends RDD[(K, V)](rdd1.context, Nil) { + private var serializerClass: String = null + + def setSerializer(cls: String): SubtractedRDD[K, V, W] = { + serializerClass = cls + this + } + override def getDependencies: Seq[Dependency[_]] = { Seq(rdd1, rdd2).map { rdd => if (rdd.partitioner == Some(part)) { - logInfo("Adding one-to-one dependency with " + rdd) + logDebug("Adding one-to-one dependency with " + rdd) new OneToOneDependency(rdd) } else { - logInfo("Adding shuffle dependency with " + rdd) - new ShuffleDependency(rdd.asInstanceOf[RDD[(K, Any)]], part, serializerClass) + logDebug("Adding shuffle dependency with " + rdd) + new ShuffleDependency(rdd, part, serializerClass) } } } @@ -83,16 +105,14 @@ private[spark] class SubtractedRDD[K: ClassTag, V: ClassTag, W: ClassTag]( seq } } - def integrate(dep: CoGroupSplitDep, op: ((K, V)) => Unit) = dep match { + def integrate(dep: CoGroupSplitDep, op: Product2[K, V] => Unit) = dep match { case NarrowCoGroupSplitDep(rdd, _, itsSplit) => { - for (t <- rdd.iterator(itsSplit, context)) - op(t.asInstanceOf[(K, V)]) + rdd.iterator(itsSplit, context).asInstanceOf[Iterator[Product2[K, V]]].foreach(op) } case ShuffleCoGroupSplitDep(shuffleId) => { - val iter = SparkEnv.get.shuffleFetcher.fetch(shuffleId, partition.index, + val iter = SparkEnv.get.shuffleFetcher.fetch[Product2[K, V]](shuffleId, partition.index, context.taskMetrics, serializer) - for (t <- iter) - op(t.asInstanceOf[(K, V)]) + iter.foreach(op) } } // the first dep is rdd1; add all values to the map diff --git a/core/src/main/scala/spark/rdd/UnionRDD.scala b/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala index b4b21c0aac..08a41ac558 100644 --- a/core/src/main/scala/spark/rdd/UnionRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala @@ -1,8 +1,27 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.collection.mutable.ArrayBuffer import scala.reflect.ClassTag -import spark.{Dependency, RangeDependency, RDD, SparkContext, Partition, TaskContext} + +import org.apache.spark.{Dependency, RangeDependency, SparkContext, Partition, TaskContext} + import java.io.{ObjectOutputStream, IOException} private[spark] class UnionPartition[T: ClassTag](idx: Int, rdd: RDD[T], splitIndex: Int) diff --git a/core/src/main/scala/spark/rdd/ZippedPartitionsRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala index d3c2370885..e02c17bf45 100644 --- a/core/src/main/scala/spark/rdd/ZippedPartitionsRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/ZippedPartitionsRDD.scala @@ -1,6 +1,23 @@ -package spark.rdd - -import spark.{Utils, OneToOneDependency, RDD, SparkContext, Partition, TaskContext} +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{OneToOneDependency, SparkContext, Partition, TaskContext} import java.io.{ObjectOutputStream, IOException} import scala.reflect.ClassTag @@ -39,27 +56,15 @@ abstract class ZippedPartitionsBaseRDD[V: ClassTag]( } override def getPreferredLocations(s: Partition): Seq[String] = { - // Note that as number of rdd's increase and/or number of slaves in cluster increase, the computed preferredLocations below - // become diminishingly small : so we might need to look at alternate strategies to alleviate this. - // If there are no (or very small number of preferred locations), we will end up transferred the blocks to 'any' node in the - // cluster - paying with n/w and cache cost. - // Maybe pick a node which figures max amount of time ? - // Choose node which is hosting 'larger' of some subset of blocks ? - // Look at rack locality to ensure chosen host is atleast rack local to both hosting node ?, etc (would be good to defer this if possible) - val splits = s.asInstanceOf[ZippedPartitionsPartition].partitions - val rddSplitZip = rdds.zip(splits) - - // exact match. - val exactMatchPreferredLocations = rddSplitZip.map(x => x._1.preferredLocations(x._2)) - val exactMatchLocations = exactMatchPreferredLocations.reduce((x, y) => x.intersect(y)) - - // Remove exact match and then do host local match. - val exactMatchHosts = exactMatchLocations.map(Utils.parseHostPort(_)._1) - val matchPreferredHosts = exactMatchPreferredLocations.map(locs => locs.map(Utils.parseHostPort(_)._1)) - .reduce((x, y) => x.intersect(y)) - val otherNodeLocalLocations = matchPreferredHosts.filter { s => !exactMatchHosts.contains(s) } - - otherNodeLocalLocations ++ exactMatchLocations + val parts = s.asInstanceOf[ZippedPartitionsPartition].partitions + val prefs = rdds.zip(parts).map { case (rdd, p) => rdd.preferredLocations(p) } + // Check whether there are any hosts that match all RDDs; otherwise return the union + val exactMatchLocations = prefs.reduce((x, y) => x.intersect(y)) + if (!exactMatchLocations.isEmpty) { + exactMatchLocations + } else { + prefs.flatten.distinct + } } override def clearDependencies() { diff --git a/core/src/main/scala/spark/rdd/ZippedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ZippedRDD.scala index be05fb71f9..fb5b070c18 100644 --- a/core/src/main/scala/spark/rdd/ZippedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/ZippedRDD.scala @@ -1,13 +1,28 @@ -package spark.rdd - -import spark.{Utils, OneToOneDependency, RDD, SparkContext, Partition, TaskContext} +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd + +import org.apache.spark.{OneToOneDependency, SparkContext, Partition, TaskContext} import java.io.{ObjectOutputStream, IOException} import scala.reflect.ClassTag -import spark.{OneToOneDependency, RDD, SparkContext, Partition, TaskContext} - private[spark] class ZippedPartition[T: ClassTag, U: ClassTag]( idx: Int, @transient rdd1: RDD[T], @@ -52,27 +67,16 @@ class ZippedRDD[T: ClassTag, U: ClassTag]( } override def getPreferredLocations(s: Partition): Seq[String] = { - // Note that as number of slaves in cluster increase, the computed preferredLocations can become small : so we might need - // to look at alternate strategies to alleviate this. (If there are no (or very small number of preferred locations), we - // will end up transferred the blocks to 'any' node in the cluster - paying with n/w and cache cost. - // Maybe pick one or the other ? (so that atleast one block is local ?). - // Choose node which is hosting 'larger' of the blocks ? - // Look at rack locality to ensure chosen host is atleast rack local to both hosting node ?, etc (would be good to defer this if possible) val (partition1, partition2) = s.asInstanceOf[ZippedPartition[T, U]].partitions val pref1 = rdd1.preferredLocations(partition1) val pref2 = rdd2.preferredLocations(partition2) - - // exact match - instance local and host local. + // Check whether there are any hosts that match both RDDs; otherwise return the union val exactMatchLocations = pref1.intersect(pref2) - - // remove locations which are already handled via exactMatchLocations, and intersect where both partitions are node local. - val otherNodeLocalPref1 = pref1.filter(loc => ! exactMatchLocations.contains(loc)).map(loc => Utils.parseHostPort(loc)._1) - val otherNodeLocalPref2 = pref2.filter(loc => ! exactMatchLocations.contains(loc)).map(loc => Utils.parseHostPort(loc)._1) - val otherNodeLocalLocations = otherNodeLocalPref1.intersect(otherNodeLocalPref2) - - - // Can have mix of instance local (hostPort) and node local (host) locations as preference ! - exactMatchLocations ++ otherNodeLocalLocations + if (!exactMatchLocations.isEmpty) { + exactMatchLocations + } else { + (pref1 ++ pref2).distinct + } } override def clearDependencies() { diff --git a/core/src/main/scala/org/apache/spark/scheduler/ActiveJob.scala b/core/src/main/scala/org/apache/spark/scheduler/ActiveJob.scala new file mode 100644 index 0000000000..0b04607d01 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/ActiveJob.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.apache.spark.TaskContext + +import java.util.Properties + +/** + * Tracks information about an active job in the DAGScheduler. + */ +private[spark] class ActiveJob( + val jobId: Int, + val finalStage: Stage, + val func: (TaskContext, Iterator[_]) => _, + val partitions: Array[Int], + val callSite: String, + val listener: JobListener, + val properties: Properties) { + + val numPartitions = partitions.length + val finished = Array.fill[Boolean](numPartitions)(false) + var numFinished = 0 +} diff --git a/core/src/main/scala/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index d4bda150cb..854dbfee09 100644 --- a/core/src/main/scala/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -1,27 +1,55 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import cluster.TaskInfo -import java.util.concurrent.atomic.AtomicInteger -import java.util.concurrent.LinkedBlockingQueue -import java.util.concurrent.TimeUnit +package org.apache.spark.scheduler + +import java.io.NotSerializableException import java.util.Properties +import java.util.concurrent.{LinkedBlockingQueue, TimeUnit} +import java.util.concurrent.atomic.AtomicInteger import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet, Map} import scala.reflect.ClassTag -import spark._ -import spark.executor.TaskMetrics -import spark.partial.ApproximateActionListener -import spark.partial.ApproximateEvaluator -import spark.partial.PartialResult -import spark.storage.{BlockManager, BlockManagerMaster} -import spark.util.{MetadataCleaner, TimeStampedHashMap} +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.executor.TaskMetrics +import org.apache.spark.partial.{ApproximateActionListener, ApproximateEvaluator, PartialResult} +import org.apache.spark.scheduler.cluster.TaskInfo +import org.apache.spark.storage.{BlockManager, BlockManagerMaster} +import org.apache.spark.util.{MetadataCleaner, TimeStampedHashMap} /** - * A Scheduler subclass that implements stage-oriented scheduling. It computes a DAG of stages for - * each job, keeps track of which RDDs and stage outputs are materialized, and computes a minimal - * schedule to run the job. Subclasses only need to implement the code to send a task to the cluster - * and to report fetch failures (the submitTasks method, and code to add CompletionEvents). + * The high-level scheduling layer that implements stage-oriented scheduling. It computes a DAG of + * stages for each job, keeps track of which RDDs and stage outputs are materialized, and finds a + * minimal schedule to run the job. It then submits stages as TaskSets to an underlying + * TaskScheduler implementation that runs them on the cluster. + * + * In addition to coming up with a DAG of stages, this class also determines the preferred + * locations to run each task on, based on the current cache status, and passes these to the + * low-level TaskScheduler. Furthermore, it handles failures due to shuffle output files being + * lost, in which case old stages may need to be resubmitted. Failures *within* a stage that are + * not caused by shuffie file loss are handled by the TaskScheduler, which will retry each task + * a small number of times before cancelling the whole stage. + * + * THREADING: This class runs all its logic in a single thread executing the run() method, to which + * events are submitted using a synchonized queue (eventQueue). The public API methods, such as + * runJob, taskEnded and executorLost, post events asynchronously to this queue. All other methods + * should be private. */ private[spark] class DAGScheduler( @@ -36,6 +64,11 @@ class DAGScheduler( } taskSched.setListener(this) + // Called by TaskScheduler to report task's starting. + override def taskStarted(task: Task[_], taskInfo: TaskInfo) { + eventQueue.put(BeginEvent(task, taskInfo)) + } + // Called by TaskScheduler to report task completions or failures. override def taskEnded( task: Task[_], @@ -53,8 +86,8 @@ class DAGScheduler( } // Called by TaskScheduler when a host is added - override def executorGained(execId: String, hostPort: String) { - eventQueue.put(ExecutorGained(execId, hostPort)) + override def executorGained(execId: String, host: String) { + eventQueue.put(ExecutorGained(execId, host)) } // Called by TaskScheduler to cancel an entire TaskSet due to repeated failures. @@ -73,27 +106,28 @@ class DAGScheduler( private val eventQueue = new LinkedBlockingQueue[DAGSchedulerEvent] - val nextRunId = new AtomicInteger(0) + val nextJobId = new AtomicInteger(0) val nextStageId = new AtomicInteger(0) - val idToStage = new TimeStampedHashMap[Int, Stage] + val stageIdToStage = new TimeStampedHashMap[Int, Stage] val shuffleToMapStage = new TimeStampedHashMap[Int, Stage] private[spark] val stageToInfos = new TimeStampedHashMap[Stage, StageInfo] - private[spark] val sparkListeners = ArrayBuffer[SparkListener]() + private val listenerBus = new SparkListenerBus() - var cacheLocs = new HashMap[Int, Array[List[String]]] + // Contains the locations that each RDD's partitions are cached on + private val cacheLocs = new HashMap[Int, Array[Seq[TaskLocation]]] - // For tracking failed nodes, we use the MapOutputTracker's generation number, which is - // sent with every task. When we detect a node failing, we note the current generation number - // and failed executor, increment it for new tasks, and use this to ignore stray ShuffleMapTask - // results. - // TODO: Garbage collect information about failure generations when we know there are no more + // For tracking failed nodes, we use the MapOutputTracker's epoch number, which is sent with + // every task. When we detect a node failing, we note the current epoch number and failed + // executor, increment it for new tasks, and use this to ignore stray ShuffleMapTask results. + // + // TODO: Garbage collect information about failure epochs when we know there are no more // stray messages to detect. - val failedGeneration = new HashMap[String, Long] + val failedEpoch = new HashMap[String, Long] val idToActiveJob = new HashMap[Int, ActiveJob] @@ -118,11 +152,17 @@ class DAGScheduler( }.start() } - private def getCacheLocs(rdd: RDD[_]): Array[List[String]] = { + def addSparkListener(listener: SparkListener) { + listenerBus.addListener(listener) + } + + private def getCacheLocs(rdd: RDD[_]): Array[Seq[TaskLocation]] = { if (!cacheLocs.contains(rdd.id)) { val blockIds = rdd.partitions.indices.map(index=> "rdd_%d_%d".format(rdd.id, index)).toArray - val locs = BlockManager.blockIdsToExecutorLocations(blockIds, env, blockManagerMaster) - cacheLocs(rdd.id) = blockIds.map(locs.getOrElse(_, Nil)) + val locs = BlockManager.blockIdsToBlockManagers(blockIds, env, blockManagerMaster) + cacheLocs(rdd.id) = blockIds.map { id => + locs.getOrElse(id, Nil).map(bm => TaskLocation(bm.host, bm.executorId)) + } } cacheLocs(rdd.id) } @@ -133,14 +173,14 @@ class DAGScheduler( /** * Get or create a shuffle map stage for the given shuffle dependency's map side. - * The priority value passed in will be used if the stage doesn't already exist with - * a lower priority (we assume that priorities always increase across jobs for now). + * The jobId value passed in will be used if the stage doesn't already exist with + * a lower jobId (jobId always increases across jobs.) */ - private def getShuffleMapStage(shuffleDep: ShuffleDependency[_,_], priority: Int): Stage = { + private def getShuffleMapStage(shuffleDep: ShuffleDependency[_,_], jobId: Int): Stage = { shuffleToMapStage.get(shuffleDep.shuffleId) match { case Some(stage) => stage case None => - val stage = newStage(shuffleDep.rdd, Some(shuffleDep), priority) + val stage = newStage(shuffleDep.rdd, Some(shuffleDep), jobId) shuffleToMapStage(shuffleDep.shuffleId) = stage stage } @@ -148,10 +188,16 @@ class DAGScheduler( /** * Create a Stage for the given RDD, either as a shuffle map stage (for a ShuffleDependency) or - * as a result stage for the final RDD used directly in an action. The stage will also be given - * the provided priority. + * as a result stage for the final RDD used directly in an action. The stage will also be + * associated with the provided jobId. */ - private def newStage(rdd: RDD[_], shuffleDep: Option[ShuffleDependency[_,_]], priority: Int): Stage = { + private def newStage( + rdd: RDD[_], + shuffleDep: Option[ShuffleDependency[_,_]], + jobId: Int, + callSite: Option[String] = None) + : Stage = + { if (shuffleDep != None) { // Kind of ugly: need to register RDDs with the cache and map output tracker here // since we can't do it in the RDD constructor because # of partitions is unknown @@ -159,17 +205,17 @@ class DAGScheduler( mapOutputTracker.registerShuffle(shuffleDep.get.shuffleId, rdd.partitions.size) } val id = nextStageId.getAndIncrement() - val stage = new Stage(id, rdd, shuffleDep, getParentStages(rdd, priority), priority) - idToStage(id) = stage + val stage = new Stage(id, rdd, shuffleDep, getParentStages(rdd, jobId), jobId, callSite) + stageIdToStage(id) = stage stageToInfos(stage) = StageInfo(stage) stage } /** * Get or create the list of parent stages for a given RDD. The stages will be assigned the - * provided priority if they haven't already been created with a lower priority. + * provided jobId if they haven't already been created with a lower jobId. */ - private def getParentStages(rdd: RDD[_], priority: Int): List[Stage] = { + private def getParentStages(rdd: RDD[_], jobId: Int): List[Stage] = { val parents = new HashSet[Stage] val visited = new HashSet[RDD[_]] def visit(r: RDD[_]) { @@ -180,7 +226,7 @@ class DAGScheduler( for (dep <- r.dependencies) { dep match { case shufDep: ShuffleDependency[_,_] => - parents += getShuffleMapStage(shufDep, priority) + parents += getShuffleMapStage(shufDep, jobId) case _ => visit(dep.rdd) } @@ -201,7 +247,7 @@ class DAGScheduler( for (dep <- rdd.dependencies) { dep match { case shufDep: ShuffleDependency[_,_] => - val mapStage = getShuffleMapStage(shufDep, stage.priority) + val mapStage = getShuffleMapStage(shufDep, stage.jobId) if (!mapStage.isAvailable) { missing += mapStage } @@ -236,8 +282,9 @@ class DAGScheduler( assert(partitions.size > 0) val waiter = new JobWaiter(partitions.size, resultHandler) val func2 = func.asInstanceOf[(TaskContext, Iterator[_]) => _] - val toSubmit = JobSubmitted(finalRdd, func2, partitions.toArray, allowLocal, callSite, waiter, properties) - return (toSubmit, waiter) + val toSubmit = JobSubmitted(finalRdd, func2, partitions.toArray, allowLocal, callSite, waiter, + properties) + (toSubmit, waiter) } def runJob[T, U: ClassTag]( @@ -252,7 +299,16 @@ class DAGScheduler( if (partitions.size == 0) { return } - val (toSubmit, waiter) = prepareJob( + + // Check to make sure we are not launching a task on a partition that does not exist. + val maxPartitions = finalRdd.partitions.length + partitions.find(p => p >= maxPartitions).foreach { p => + throw new IllegalArgumentException( + "Attempting to access a non-existent partition: " + p + ". " + + "Total number of partitions: " + maxPartitions) + } + + val (toSubmit: JobSubmitted, waiter: JobWaiter[_]) = prepareJob( finalRdd, func, partitions, callSite, allowLocal, resultHandler, properties) eventQueue.put(toSubmit) waiter.awaitResult() match { @@ -275,8 +331,8 @@ class DAGScheduler( val listener = new ApproximateActionListener(rdd, func, evaluator, timeout) val func2 = func.asInstanceOf[(TaskContext, Iterator[_]) => _] val partitions = (0 until rdd.partitions.size).toArray - eventQueue.put(JobSubmitted(rdd, func2, partitions, false, callSite, listener, properties)) - return listener.awaitResult() // Will throw an exception if the job fails + eventQueue.put(JobSubmitted(rdd, func2, partitions, allowLocal = false, callSite, listener, properties)) + listener.awaitResult() // Will throw an exception if the job fails } /** @@ -286,50 +342,53 @@ class DAGScheduler( private[scheduler] def processEvent(event: DAGSchedulerEvent): Boolean = { event match { case JobSubmitted(finalRDD, func, partitions, allowLocal, callSite, listener, properties) => - val runId = nextRunId.getAndIncrement() - val finalStage = newStage(finalRDD, None, runId) - val job = new ActiveJob(runId, finalStage, func, partitions, callSite, listener, properties) + val jobId = nextJobId.getAndIncrement() + val finalStage = newStage(finalRDD, None, jobId, Some(callSite)) + val job = new ActiveJob(jobId, finalStage, func, partitions, callSite, listener, properties) clearCacheLocs() - logInfo("Got job " + job.runId + " (" + callSite + ") with " + partitions.length + + logInfo("Got job " + job.jobId + " (" + callSite + ") with " + partitions.length + " output partitions (allowLocal=" + allowLocal + ")") - logInfo("Final stage: " + finalStage + " (" + finalStage.origin + ")") + logInfo("Final stage: " + finalStage + " (" + finalStage.name + ")") logInfo("Parents of final stage: " + finalStage.parents) logInfo("Missing parents: " + getMissingParentStages(finalStage)) if (allowLocal && finalStage.parents.size == 0 && partitions.length == 1) { // Compute very short actions like first() or take() with no parent stages locally. runLocally(job) } else { - sparkListeners.foreach(_.onJobStart(SparkListenerJobStart(job, properties))) - idToActiveJob(runId) = job + listenerBus.post(SparkListenerJobStart(job, properties)) + idToActiveJob(jobId) = job activeJobs += job resultStageToJob(finalStage) = job submitStage(finalStage) } - case ExecutorGained(execId, hostPort) => - handleExecutorGained(execId, hostPort) + case ExecutorGained(execId, host) => + handleExecutorGained(execId, host) case ExecutorLost(execId) => handleExecutorLost(execId) + case begin: BeginEvent => + listenerBus.post(SparkListenerTaskStart(begin.task, begin.taskInfo)) + case completion: CompletionEvent => - sparkListeners.foreach(_.onTaskEnd(SparkListenerTaskEnd(completion.task, - completion.reason, completion.taskInfo, completion.taskMetrics))) + listenerBus.post(SparkListenerTaskEnd( + completion.task, completion.reason, completion.taskInfo, completion.taskMetrics)) handleTaskCompletion(completion) case TaskSetFailed(taskSet, reason) => - abortStage(idToStage(taskSet.stageId), reason) + abortStage(stageIdToStage(taskSet.stageId), reason) case StopDAGScheduler => // Cancel any active jobs for (job <- activeJobs) { val error = new SparkException("Job cancelled because SparkContext was shut down") job.listener.jobFailed(error) - sparkListeners.foreach(_.onJobEnd(SparkListenerJobEnd(job, JobFailed(error, None)))) + listenerBus.post(SparkListenerJobEnd(job, JobFailed(error, None))) } return true } - return false + false } /** @@ -341,7 +400,7 @@ class DAGScheduler( clearCacheLocs() val failed2 = failed.toArray failed.clear() - for (stage <- failed2.sortBy(_.priority)) { + for (stage <- failed2.sortBy(_.jobId)) { submitStage(stage) } } @@ -359,7 +418,7 @@ class DAGScheduler( logTrace("failed: " + failed) val waiting2 = waiting.toArray waiting.clear() - for (stage <- waiting2.sortBy(_.priority)) { + for (stage <- waiting2.sortBy(_.jobId)) { submitStage(stage) } } @@ -378,23 +437,24 @@ class DAGScheduler( if (event != null) { logDebug("Got event of type " + event.getClass.getName) } - - if (event != null) { - if (processEvent(event)) { - return + this.synchronized { // needed in case other threads makes calls into methods of this class + if (event != null) { + if (processEvent(event)) { + return + } } - } - val time = System.currentTimeMillis() // TODO: use a pluggable clock for testability - // Periodically resubmit failed stages if some map output fetches have failed and we have - // waited at least RESUBMIT_TIMEOUT. We wait for this short time because when a node fails, - // tasks on many other nodes are bound to get a fetch failure, and they won't all get it at - // the same time, so we want to make sure we've identified all the reduce tasks that depend - // on the failed node. - if (failed.size > 0 && time > lastFetchFailureTime + RESUBMIT_TIMEOUT) { - resubmitFailedStages() - } else { - submitWaitingStages() + val time = System.currentTimeMillis() // TODO: use a pluggable clock for testability + // Periodically resubmit failed stages if some map output fetches have failed and we have + // waited at least RESUBMIT_TIMEOUT. We wait for this short time because when a node fails, + // tasks on many other nodes are bound to get a fetch failure, and they won't all get it at + // the same time, so we want to make sure we've identified all the reduce tasks that depend + // on the failed node. + if (failed.size > 0 && time > lastFetchFailureTime + RESUBMIT_TIMEOUT) { + resubmitFailedStages() + } else { + submitWaitingStages() + } } } } @@ -406,7 +466,7 @@ class DAGScheduler( */ protected def runLocally(job: ActiveJob) { logInfo("Computing the requested partition locally") - new Thread("Local computation of job " + job.runId) { + new Thread("Local computation of job " + job.jobId) { override def run() { runLocallyWithinThread(job) } @@ -466,20 +526,36 @@ class DAGScheduler( } else { // This is a final stage; figure out its job's missing partitions val job = resultStageToJob(stage) - for (id <- 0 until job.numPartitions if (!job.finished(id))) { + for (id <- 0 until job.numPartitions if !job.finished(id)) { val partition = job.partitions(id) val locs = getPreferredLocs(stage.rdd, partition) tasks += new ResultTask(stage.id, stage.rdd, job.func, partition, locs, id) } } + // must be run listener before possible NotSerializableException + // should be "StageSubmitted" first and then "JobEnded" + val properties = idToActiveJob(stage.jobId).properties + listenerBus.post(SparkListenerStageSubmitted(stage, tasks.size, properties)) + if (tasks.size > 0) { - sparkListeners.foreach(_.onStageSubmitted(SparkListenerStageSubmitted(stage, tasks.size))) + // Preemptively serialize a task to make sure it can be serialized. We are catching this + // exception here because it would be fairly hard to catch the non-serializable exception + // down the road, where we have several different implementations for local scheduler and + // cluster schedulers. + try { + SparkEnv.get.closureSerializer.newInstance().serialize(tasks.head) + } catch { + case e: NotSerializableException => + abortStage(stage, e.toString) + running -= stage + return + } + logInfo("Submitting " + tasks.size + " missing tasks from " + stage + " (" + stage.rdd + ")") myPending ++= tasks logDebug("New pending tasks: " + myPending) - val properties = idToActiveJob(stage.priority).properties taskSched.submitTasks( - new TaskSet(tasks.toArray, stage.id, stage.newAttemptId(), stage.priority, properties)) + new TaskSet(tasks.toArray, stage.id, stage.newAttemptId(), stage.jobId, properties)) if (!stage.submissionTime.isDefined) { stage.submissionTime = Some(System.currentTimeMillis()) } @@ -496,17 +572,16 @@ class DAGScheduler( */ private def handleTaskCompletion(event: CompletionEvent) { val task = event.task - val stage = idToStage(task.stageId) + val stage = stageIdToStage(task.stageId) def markStageAsFinished(stage: Stage) = { val serviceTime = stage.submissionTime match { case Some(t) => "%.03f".format((System.currentTimeMillis() - t) / 1000.0) case _ => "Unkown" } - logInfo("%s (%s) finished in %s s".format(stage, stage.origin, serviceTime)) + logInfo("%s (%s) finished in %s s".format(stage, stage.name, serviceTime)) stage.completionTime = Some(System.currentTimeMillis) - val stageComp = StageCompleted(stageToInfos(stage)) - sparkListeners.foreach{_.onStageCompleted(stageComp)} + listenerBus.post(StageCompleted(stageToInfos(stage))) running -= stage } event.reason match { @@ -526,11 +601,11 @@ class DAGScheduler( job.numFinished += 1 // If the whole job has finished, remove it if (job.numFinished == job.numPartitions) { - idToActiveJob -= stage.priority + idToActiveJob -= stage.jobId activeJobs -= job resultStageToJob -= stage markStageAsFinished(stage) - sparkListeners.foreach(_.onJobEnd(SparkListenerJobEnd(job, JobSucceeded))) + listenerBus.post(SparkListenerJobEnd(job, JobSucceeded)) } job.listener.taskSucceeded(rt.outputId, event.result) } @@ -542,7 +617,7 @@ class DAGScheduler( val status = event.result.asInstanceOf[MapStatus] val execId = status.location.executorId logDebug("ShuffleMapTask finished on " + execId) - if (failedGeneration.contains(execId) && smt.generation <= failedGeneration(execId)) { + if (failedEpoch.contains(execId) && smt.epoch <= failedEpoch(execId)) { logInfo("Ignoring possibly bogus ShuffleMapTask completion from " + execId) } else { stage.addOutputLoc(smt.partition, status) @@ -554,22 +629,22 @@ class DAGScheduler( logInfo("waiting: " + waiting) logInfo("failed: " + failed) if (stage.shuffleDep != None) { - // We supply true to increment the generation number here in case this is a + // We supply true to increment the epoch number here in case this is a // recomputation of the map outputs. In that case, some nodes may have cached // locations with holes (from when we detected the error) and will need the - // generation incremented to refetch them. - // TODO: Only increment the generation number if this is not the first time + // epoch incremented to refetch them. + // TODO: Only increment the epoch number if this is not the first time // we registered these map outputs. mapOutputTracker.registerMapOutputs( stage.shuffleDep.get.shuffleId, stage.outputLocs.map(list => if (list.isEmpty) null else list.head).toArray, - true) + changeEpoch = true) } clearCacheLocs() if (stage.outputLocs.count(_ == Nil) != 0) { // Some tasks had failed; let's resubmit this stage // TODO: Lower-level scheduler should also deal with this - logInfo("Resubmitting " + stage + " (" + stage.origin + + logInfo("Resubmitting " + stage + " (" + stage.name + ") because some of its tasks had failed: " + stage.outputLocs.zipWithIndex.filter(_._1 == Nil).map(_._2).mkString(", ")) submitStage(stage) @@ -597,11 +672,11 @@ class DAGScheduler( case FetchFailed(bmAddress, shuffleId, mapId, reduceId) => // Mark the stage that the reducer was in as unrunnable - val failedStage = idToStage(task.stageId) + val failedStage = stageIdToStage(task.stageId) running -= failedStage failed += failedStage // TODO: Cancel running tasks in the stage - logInfo("Marking " + failedStage + " (" + failedStage.origin + + logInfo("Marking " + failedStage + " (" + failedStage.name + ") for resubmision due to a fetch failure") // Mark the map whose fetch failed as broken in the map stage val mapStage = shuffleToMapStage(shuffleId) @@ -609,7 +684,7 @@ class DAGScheduler( mapStage.removeOutputLoc(mapId, bmAddress) mapOutputTracker.unregisterMapOutput(shuffleId, mapId, bmAddress) } - logInfo("The failed fetch was from " + mapStage + " (" + mapStage.origin + + logInfo("The failed fetch was from " + mapStage + " (" + mapStage.name + "); marking it for resubmission") failed += mapStage // Remember that a fetch failed now; this is used to resubmit the broken @@ -617,7 +692,7 @@ class DAGScheduler( lastFetchFailureTime = System.currentTimeMillis() // TODO: Use pluggable clock // TODO: mark the executor as failed only if there were lots of fetch failures on it if (bmAddress != null) { - handleExecutorLost(bmAddress.executorId, Some(task.generation)) + handleExecutorLost(bmAddress.executorId, Some(task.epoch)) } case ExceptionFailure(className, description, stackTrace, metrics) => @@ -625,7 +700,7 @@ class DAGScheduler( case other => // Unrecognized failure - abort all jobs depending on this stage - abortStage(idToStage(task.stageId), task + " failed: " + other) + abortStage(stageIdToStage(task.stageId), task + " failed: " + other) } } @@ -633,36 +708,36 @@ class DAGScheduler( * Responds to an executor being lost. This is called inside the event loop, so it assumes it can * modify the scheduler's internal state. Use executorLost() to post a loss event from outside. * - * Optionally the generation during which the failure was caught can be passed to avoid allowing + * Optionally the epoch during which the failure was caught can be passed to avoid allowing * stray fetch failures from possibly retriggering the detection of a node as lost. */ - private def handleExecutorLost(execId: String, maybeGeneration: Option[Long] = None) { - val currentGeneration = maybeGeneration.getOrElse(mapOutputTracker.getGeneration) - if (!failedGeneration.contains(execId) || failedGeneration(execId) < currentGeneration) { - failedGeneration(execId) = currentGeneration - logInfo("Executor lost: %s (generation %d)".format(execId, currentGeneration)) + private def handleExecutorLost(execId: String, maybeEpoch: Option[Long] = None) { + val currentEpoch = maybeEpoch.getOrElse(mapOutputTracker.getEpoch) + if (!failedEpoch.contains(execId) || failedEpoch(execId) < currentEpoch) { + failedEpoch(execId) = currentEpoch + logInfo("Executor lost: %s (epoch %d)".format(execId, currentEpoch)) blockManagerMaster.removeExecutor(execId) // TODO: This will be really slow if we keep accumulating shuffle map stages for ((shuffleId, stage) <- shuffleToMapStage) { stage.removeOutputsOnExecutor(execId) val locs = stage.outputLocs.map(list => if (list.isEmpty) null else list.head).toArray - mapOutputTracker.registerMapOutputs(shuffleId, locs, true) + mapOutputTracker.registerMapOutputs(shuffleId, locs, changeEpoch = true) } if (shuffleToMapStage.isEmpty) { - mapOutputTracker.incrementGeneration() + mapOutputTracker.incrementEpoch() } clearCacheLocs() } else { logDebug("Additional executor lost message for " + execId + - "(generation " + currentGeneration + ")") + "(epoch " + currentEpoch + ")") } } - private def handleExecutorGained(execId: String, hostPort: String) { - // remove from failedGeneration(execId) ? - if (failedGeneration.contains(execId)) { - logInfo("Host gained which was in lost list earlier: " + hostPort) - failedGeneration -= execId + private def handleExecutorGained(execId: String, host: String) { + // remove from failedEpoch(execId) ? + if (failedEpoch.contains(execId)) { + logInfo("Host gained which was in lost list earlier: " + host) + failedEpoch -= execId } } @@ -677,8 +752,8 @@ class DAGScheduler( val job = resultStageToJob(resultStage) val error = new SparkException("Job failed: " + reason) job.listener.jobFailed(error) - sparkListeners.foreach(_.onJobEnd(SparkListenerJobEnd(job, JobFailed(error, Some(failedStage))))) - idToActiveJob -= resultStage.priority + listenerBus.post(SparkListenerJobEnd(job, JobFailed(error, Some(failedStage)))) + idToActiveJob -= resultStage.jobId activeJobs -= job resultStageToJob -= resultStage } @@ -702,7 +777,7 @@ class DAGScheduler( for (dep <- rdd.dependencies) { dep match { case shufDep: ShuffleDependency[_,_] => - val mapStage = getShuffleMapStage(shufDep, stage.priority) + val mapStage = getShuffleMapStage(shufDep, stage.jobId) if (!mapStage.isAvailable) { visitedStages += mapStage visit(mapStage.rdd) @@ -717,16 +792,23 @@ class DAGScheduler( visitedRdds.contains(target.rdd) } - private def getPreferredLocs(rdd: RDD[_], partition: Int): List[String] = { + /** + * Synchronized method that might be called from other threads. + * @param rdd whose partitions are to be looked at + * @param partition to lookup locality information for + * @return list of machines that are preferred by the partition + */ + private[spark] + def getPreferredLocs(rdd: RDD[_], partition: Int): Seq[TaskLocation] = synchronized { // If the partition is cached, return the cache locations val cached = getCacheLocs(rdd)(partition) - if (cached != Nil) { + if (!cached.isEmpty) { return cached } // If the RDD has some placement preferences (as is the case for input RDDs), get those val rddPrefs = rdd.preferredLocations(rdd.partitions(partition)).toList - if (rddPrefs != Nil) { - return rddPrefs + if (!rddPrefs.isEmpty) { + return rddPrefs.map(host => TaskLocation(host)) } // If the RDD has narrow dependencies, pick the first partition of the first narrow dep // that has any placement preferences. Ideally we would choose based on transfer sizes, @@ -740,13 +822,13 @@ class DAGScheduler( } case _ => }) - return Nil + Nil } private def cleanup(cleanupTime: Long) { - var sizeBefore = idToStage.size - idToStage.clearOldValues(cleanupTime) - logInfo("idToStage " + sizeBefore + " --> " + idToStage.size) + var sizeBefore = stageIdToStage.size + stageIdToStage.clearOldValues(cleanupTime) + logInfo("stageIdToStage " + sizeBefore + " --> " + stageIdToStage.size) sizeBefore = shuffleToMapStage.size shuffleToMapStage.clearOldValues(cleanupTime) diff --git a/core/src/main/scala/spark/scheduler/DAGSchedulerEvent.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGSchedulerEvent.scala index acad915f13..0d99670648 100644 --- a/core/src/main/scala/spark/scheduler/DAGSchedulerEvent.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGSchedulerEvent.scala @@ -1,12 +1,30 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import java.util.Properties -import spark.scheduler.cluster.TaskInfo +import org.apache.spark.scheduler.cluster.TaskInfo import scala.collection.mutable.Map -import spark._ -import spark.executor.TaskMetrics +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.executor.TaskMetrics /** * Types of events that can be handled by the DAGScheduler. The DAGScheduler uses an event queue @@ -26,6 +44,8 @@ private[spark] case class JobSubmitted( properties: Properties = null) extends DAGSchedulerEvent +private[spark] case class BeginEvent(task: Task[_], taskInfo: TaskInfo) extends DAGSchedulerEvent + private[spark] case class CompletionEvent( task: Task[_], reason: TaskEndReason, @@ -35,9 +55,7 @@ private[spark] case class CompletionEvent( taskMetrics: TaskMetrics) extends DAGSchedulerEvent -private[spark] case class ExecutorGained(execId: String, hostPort: String) extends DAGSchedulerEvent { - Utils.checkHostPort(hostPort, "Required hostport") -} +private[spark] case class ExecutorGained(execId: String, host: String) extends DAGSchedulerEvent private[spark] case class ExecutorLost(execId: String) extends DAGSchedulerEvent diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGSchedulerSource.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGSchedulerSource.scala new file mode 100644 index 0000000000..22e3723ac8 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGSchedulerSource.scala @@ -0,0 +1,47 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import com.codahale.metrics.{Gauge,MetricRegistry} + +import org.apache.spark.metrics.source.Source + +private[spark] class DAGSchedulerSource(val dagScheduler: DAGScheduler) extends Source { + val metricRegistry = new MetricRegistry() + val sourceName = "DAGScheduler" + + metricRegistry.register(MetricRegistry.name("stage", "failedStages", "number"), new Gauge[Int] { + override def getValue: Int = dagScheduler.failed.size + }) + + metricRegistry.register(MetricRegistry.name("stage", "runningStages", "number"), new Gauge[Int] { + override def getValue: Int = dagScheduler.running.size + }) + + metricRegistry.register(MetricRegistry.name("stage", "waitingStages", "number"), new Gauge[Int] { + override def getValue: Int = dagScheduler.waiting.size + }) + + metricRegistry.register(MetricRegistry.name("job", "allJobs", "number"), new Gauge[Int] { + override def getValue: Int = dagScheduler.nextJobId.get() + }) + + metricRegistry.register(MetricRegistry.name("job", "activeJobs", "number"), new Gauge[Int] { + override def getValue: Int = dagScheduler.activeJobs.size + }) +} diff --git a/core/src/main/scala/spark/scheduler/InputFormatInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala index 17d0ea4f80..370ccd183c 100644 --- a/core/src/main/scala/spark/scheduler/InputFormatInfo.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala @@ -1,6 +1,23 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler -import spark.Logging +import org.apache.spark.{Logging, SparkEnv} import scala.collection.immutable.Set import org.apache.hadoop.mapred.{FileInputFormat, JobConf} import org.apache.hadoop.security.UserGroupInformation @@ -9,7 +26,6 @@ import org.apache.hadoop.mapreduce.Job import org.apache.hadoop.conf.Configuration import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} import scala.collection.JavaConversions._ -import spark.deploy.SparkHadoopUtil /** @@ -71,8 +87,9 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl // This method does not expect failures, since validate has already passed ... private def prefLocsFromMapreduceInputFormat(): Set[SplitInfo] = { + val env = SparkEnv.get val conf = new JobConf(configuration) - SparkHadoopUtil.addCredentials(conf); + env.hadoop.addCredentials(conf) FileInputFormat.setInputPaths(conf, path) val instance: org.apache.hadoop.mapreduce.InputFormat[_, _] = @@ -91,8 +108,9 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl // This method does not expect failures, since validate has already passed ... private def prefLocsFromMapredInputFormat(): Set[SplitInfo] = { + val env = SparkEnv.get val jobConf = new JobConf(configuration) - SparkHadoopUtil.addCredentials(jobConf); + env.hadoop.addCredentials(jobConf) FileInputFormat.setInputPaths(jobConf, path) val instance: org.apache.hadoop.mapred.InputFormat[_, _] = diff --git a/core/src/main/scala/org/apache/spark/scheduler/JobListener.scala b/core/src/main/scala/org/apache/spark/scheduler/JobListener.scala new file mode 100644 index 0000000000..50c2b9acd6 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/JobListener.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +/** + * Interface used to listen for job completion or failure events after submitting a job to the + * DAGScheduler. The listener is notified each time a task succeeds, as well as if the whole + * job fails (and no further taskSucceeded events will happen). + */ +private[spark] trait JobListener { + def taskSucceeded(index: Int, result: Any) + def jobFailed(exception: Exception) +} diff --git a/core/src/main/scala/spark/scheduler/JobLogger.scala b/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala index 6a9d52f356..c8b78bf00a 100644 --- a/core/src/main/scala/spark/scheduler/JobLogger.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala @@ -1,4 +1,21 @@ -package spark.scheduler
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler
import java.io.PrintWriter
import java.io.File
@@ -6,11 +23,14 @@ import java.io.FileNotFoundException import java.text.SimpleDateFormat
import java.util.{Date, Properties}
import java.util.concurrent.LinkedBlockingQueue
+
import scala.collection.mutable.{Map, HashMap, ListBuffer}
import scala.io.Source
-import spark._
-import spark.executor.TaskMetrics
-import spark.scheduler.cluster.TaskInfo
+
+import org.apache.spark._
+import org.apache.spark.rdd.RDD
+import org.apache.spark.executor.TaskMetrics
+import org.apache.spark.scheduler.cluster.TaskInfo
// Used to record runtime information for each job, including RDD graph
// tasks' start/stop shuffle information and information from outside
@@ -36,29 +56,6 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging { def getJobIDToStages = jobIDToStages
def getEventQueue = eventQueue
- new Thread("JobLogger") {
- setDaemon(true)
- override def run() {
- while (true) {
- val event = eventQueue.take
- logDebug("Got event of type " + event.getClass.getName)
- event match {
- case SparkListenerJobStart(job, properties) =>
- processJobStartEvent(job, properties)
- case SparkListenerStageSubmitted(stage, taskSize) =>
- processStageSubmittedEvent(stage, taskSize)
- case StageCompleted(stageInfo) =>
- processStageCompletedEvent(stageInfo)
- case SparkListenerJobEnd(job, result) =>
- processJobEndEvent(job, result)
- case SparkListenerTaskEnd(task, reason, taskInfo, taskMetrics) =>
- processTaskEndEvent(task, reason, taskInfo, taskMetrics)
- case _ =>
- }
- }
- }
- }.start()
-
// Create a folder for log files, the folder's name is the creation time of the jobLogger
protected def createLogDir() {
val dir = new File(logDir + "/" + logDirName + "/")
@@ -106,7 +103,7 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging { stageIDToJobID.get(stageID).foreach(jobID => jobLogInfo(jobID, info, withTime))
protected def buildJobDep(jobID: Int, stage: Stage) {
- if (stage.priority == jobID) {
+ if (stage.jobId == jobID) {
jobIDToStages.get(jobID) match {
case Some(stageList) => stageList += stage
case None => val stageList = new ListBuffer[Stage]
@@ -182,12 +179,12 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging { }else{
stageInfo = "STAGE_ID=" + stage.id + " RESULT_STAGE"
}
- if (stage.priority == jobID) {
+ if (stage.jobId == jobID) {
jobLogInfo(jobID, indentString(indent) + stageInfo, false)
recordRddInStageGraph(jobID, stage.rdd, indent)
stage.parents.foreach(recordStageDepGraph(jobID, _, indent + 2))
} else
- jobLogInfo(jobID, indentString(indent) + stageInfo + " JOB_ID=" + stage.priority, false)
+ jobLogInfo(jobID, indentString(indent) + stageInfo + " JOB_ID=" + stage.jobId, false)
}
// Record task metrics into job log files
@@ -219,37 +216,32 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging { }
override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) {
- eventQueue.put(stageSubmitted)
- }
-
- protected def processStageSubmittedEvent(stage: Stage, taskSize: Int) {
- stageLogInfo(stage.id, "STAGE_ID=" + stage.id + " STATUS=SUBMITTED" + " TASK_SIZE=" + taskSize)
+ stageLogInfo(
+ stageSubmitted.stage.id,
+ "STAGE_ID=%d STATUS=SUBMITTED TASK_SIZE=%d".format(
+ stageSubmitted.stage.id, stageSubmitted.taskSize))
}
override def onStageCompleted(stageCompleted: StageCompleted) {
- eventQueue.put(stageCompleted)
- }
-
- protected def processStageCompletedEvent(stageInfo: StageInfo) {
- stageLogInfo(stageInfo.stage.id, "STAGE_ID=" +
- stageInfo.stage.id + " STATUS=COMPLETED")
+ stageLogInfo(
+ stageCompleted.stageInfo.stage.id,
+ "STAGE_ID=%d STATUS=COMPLETED".format(stageCompleted.stageInfo.stage.id))
}
-
- override def onTaskEnd(taskEnd: SparkListenerTaskEnd) {
- eventQueue.put(taskEnd)
- }
- protected def processTaskEndEvent(task: Task[_], reason: TaskEndReason,
- taskInfo: TaskInfo, taskMetrics: TaskMetrics) {
+ override def onTaskStart(taskStart: SparkListenerTaskStart) { }
+
+ override def onTaskEnd(taskEnd: SparkListenerTaskEnd) {
+ val task = taskEnd.task
+ val taskInfo = taskEnd.taskInfo
var taskStatus = ""
task match {
case resultTask: ResultTask[_, _] => taskStatus = "TASK_TYPE=RESULT_TASK"
case shuffleMapTask: ShuffleMapTask => taskStatus = "TASK_TYPE=SHUFFLE_MAP_TASK"
}
- reason match {
+ taskEnd.reason match {
case Success => taskStatus += " STATUS=SUCCESS"
- recordTaskMetrics(task.stageId, taskStatus, taskInfo, taskMetrics)
+ recordTaskMetrics(task.stageId, taskStatus, taskInfo, taskEnd.taskMetrics)
case Resubmitted =>
taskStatus += " STATUS=RESUBMITTED TID=" + taskInfo.taskId +
" STAGE_ID=" + task.stageId
@@ -268,39 +260,34 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging { }
override def onJobEnd(jobEnd: SparkListenerJobEnd) {
- eventQueue.put(jobEnd)
- }
-
- protected def processJobEndEvent(job: ActiveJob, reason: JobResult) {
- var info = "JOB_ID=" + job.runId
- reason match {
+ val job = jobEnd.job
+ var info = "JOB_ID=" + job.jobId
+ jobEnd.jobResult match {
case JobSucceeded => info += " STATUS=SUCCESS"
case JobFailed(exception, _) =>
info += " STATUS=FAILED REASON="
exception.getMessage.split("\\s+").foreach(info += _ + "_")
case _ =>
}
- jobLogInfo(job.runId, info.substring(0, info.length - 1).toUpperCase)
- closeLogWriter(job.runId)
+ jobLogInfo(job.jobId, info.substring(0, info.length - 1).toUpperCase)
+ closeLogWriter(job.jobId)
}
protected def recordJobProperties(jobID: Int, properties: Properties) {
if(properties != null) {
- val annotation = properties.getProperty("spark.job.annotation", "")
- jobLogInfo(jobID, annotation, false)
+ val description = properties.getProperty(SparkContext.SPARK_JOB_DESCRIPTION, "")
+ jobLogInfo(jobID, description, false)
}
}
override def onJobStart(jobStart: SparkListenerJobStart) {
- eventQueue.put(jobStart)
- }
-
- protected def processJobStartEvent(job: ActiveJob, properties: Properties) {
- createLogWriter(job.runId)
- recordJobProperties(job.runId, properties)
- buildJobDep(job.runId, job.finalStage)
- recordStageDep(job.runId)
- recordStageDepGraph(job.runId, job.finalStage)
- jobLogInfo(job.runId, "JOB_ID=" + job.runId + " STATUS=STARTED")
+ val job = jobStart.job
+ val properties = jobStart.properties
+ createLogWriter(job.jobId)
+ recordJobProperties(job.jobId, properties)
+ buildJobDep(job.jobId, job.finalStage)
+ recordStageDep(job.jobId)
+ recordStageDepGraph(job.jobId, job.finalStage)
+ jobLogInfo(job.jobId, "JOB_ID=" + job.jobId + " STATUS=STARTED")
}
}
diff --git a/core/src/main/scala/org/apache/spark/scheduler/JobResult.scala b/core/src/main/scala/org/apache/spark/scheduler/JobResult.scala new file mode 100644 index 0000000000..c381348a8d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/JobResult.scala @@ -0,0 +1,26 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +/** + * A result of a job in the DAGScheduler. + */ +private[spark] sealed trait JobResult + +private[spark] case object JobSucceeded extends JobResult +private[spark] case class JobFailed(exception: Exception, failedStage: Option[Stage]) extends JobResult diff --git a/core/src/main/scala/spark/scheduler/JobWaiter.scala b/core/src/main/scala/org/apache/spark/scheduler/JobWaiter.scala index 6ff2e29434..200d881799 100644 --- a/core/src/main/scala/spark/scheduler/JobWaiter.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/JobWaiter.scala @@ -1,4 +1,21 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import scala.collection.mutable.ArrayBuffer diff --git a/core/src/main/scala/org/apache/spark/scheduler/MapStatus.scala b/core/src/main/scala/org/apache/spark/scheduler/MapStatus.scala new file mode 100644 index 0000000000..1c61687f28 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/MapStatus.scala @@ -0,0 +1,44 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.apache.spark.storage.BlockManagerId +import java.io.{ObjectOutput, ObjectInput, Externalizable} + +/** + * Result returned by a ShuffleMapTask to a scheduler. Includes the block manager address that the + * task ran on as well as the sizes of outputs for each reducer, for passing on to the reduce tasks. + * The map output sizes are compressed using MapOutputTracker.compressSize. + */ +private[spark] class MapStatus(var location: BlockManagerId, var compressedSizes: Array[Byte]) + extends Externalizable { + + def this() = this(null, null) // For deserialization only + + def writeExternal(out: ObjectOutput) { + location.writeExternal(out) + out.writeInt(compressedSizes.length) + out.write(compressedSizes) + } + + def readExternal(in: ObjectInput) { + location = BlockManagerId(in) + compressedSizes = new Array[Byte](in.readInt()) + in.readFully(compressedSizes) + } +} diff --git a/core/src/main/scala/spark/scheduler/ResultTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala index 83166bce22..2b007cbe82 100644 --- a/core/src/main/scala/spark/scheduler/ResultTask.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala @@ -1,10 +1,30 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler -import spark._ import java.io._ -import util.{MetadataCleaner, TimeStampedHashMap} import java.util.zip.{GZIPInputStream, GZIPOutputStream} +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.RDDCheckpointData +import org.apache.spark.util.{MetadataCleaner, TimeStampedHashMap} + private[spark] object ResultTask { // A simple map between the stage id to the serialized byte array of a task. @@ -34,15 +54,13 @@ private[spark] object ResultTask { } def deserializeInfo(stageId: Int, bytes: Array[Byte]): (RDD[_], (TaskContext, Iterator[_]) => _) = { - synchronized { - val loader = Thread.currentThread.getContextClassLoader - val in = new GZIPInputStream(new ByteArrayInputStream(bytes)) - val ser = SparkEnv.get.closureSerializer.newInstance - val objIn = ser.deserializeStream(in) - val rdd = objIn.readObject().asInstanceOf[RDD[_]] - val func = objIn.readObject().asInstanceOf[(TaskContext, Iterator[_]) => _] - return (rdd, func) - } + val loader = Thread.currentThread.getContextClassLoader + val in = new GZIPInputStream(new ByteArrayInputStream(bytes)) + val ser = SparkEnv.get.closureSerializer.newInstance + val objIn = ser.deserializeStream(in) + val rdd = objIn.readObject().asInstanceOf[RDD[_]] + val func = objIn.readObject().asInstanceOf[(TaskContext, Iterator[_]) => _] + return (rdd, func) } def clearCache() { @@ -58,7 +76,7 @@ private[spark] class ResultTask[T, U]( var rdd: RDD[T], var func: (TaskContext, Iterator[T]) => U, var partition: Int, - @transient locs: Seq[String], + @transient locs: Seq[TaskLocation], val outputId: Int) extends Task[U](stageId) with Externalizable { @@ -70,11 +88,8 @@ private[spark] class ResultTask[T, U]( rdd.partitions(partition) } - private val preferredLocs: Seq[String] = if (locs == null) Nil else locs.toSet.toSeq - - { - // DEBUG code - preferredLocs.foreach (hostPort => Utils.checkHost(Utils.parseHostPort(hostPort)._1, "preferredLocs : " + preferredLocs)) + @transient private val preferredLocs: Seq[TaskLocation] = { + if (locs == null) Nil else locs.toSet.toSeq } override def run(attemptId: Long): U = { @@ -87,7 +102,7 @@ private[spark] class ResultTask[T, U]( } } - override def preferredLocations: Seq[String] = preferredLocs + override def preferredLocations: Seq[TaskLocation] = preferredLocs override def toString = "ResultTask(" + stageId + ", " + partition + ")" @@ -101,6 +116,7 @@ private[spark] class ResultTask[T, U]( out.write(bytes) out.writeInt(partition) out.writeInt(outputId) + out.writeLong(epoch) out.writeObject(split) } } @@ -115,6 +131,7 @@ private[spark] class ResultTask[T, U]( func = func_.asInstanceOf[(TaskContext, Iterator[T]) => U] partition = in.readInt() val outputId = in.readInt() + epoch = in.readLong() split = in.readObject().asInstanceOf[Partition] } } diff --git a/core/src/main/scala/spark/scheduler/ShuffleMapTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala index 95647389c3..764775fede 100644 --- a/core/src/main/scala/spark/scheduler/ShuffleMapTask.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala @@ -1,21 +1,33 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import java.io._ -import java.util.{HashMap => JHashMap} import java.util.zip.{GZIPInputStream, GZIPOutputStream} -import scala.collection.mutable.{ArrayBuffer, HashMap} -import scala.collection.JavaConversions._ +import scala.collection.mutable.HashMap -import it.unimi.dsi.fastutil.io.FastBufferedOutputStream - -import com.ning.compress.lzf.LZFInputStream -import com.ning.compress.lzf.LZFOutputStream - -import spark._ -import spark.executor.ShuffleWriteMetrics -import spark.storage._ -import spark.util.{TimeStampedHashMap, MetadataCleaner} +import org.apache.spark._ +import org.apache.spark.executor.ShuffleWriteMetrics +import org.apache.spark.storage._ +import org.apache.spark.util.{TimeStampedHashMap, MetadataCleaner} +import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.RDDCheckpointData private[spark] object ShuffleMapTask { @@ -78,25 +90,18 @@ private[spark] class ShuffleMapTask( var rdd: RDD[_], var dep: ShuffleDependency[_,_], var partition: Int, - @transient private var locs: Seq[String]) + @transient private var locs: Seq[TaskLocation]) extends Task[MapStatus](stageId) with Externalizable with Logging { protected def this() = this(0, null, null, 0, null) - @transient private val preferredLocs: Seq[String] = if (locs == null) Nil else locs.toSet.toSeq - - { - // DEBUG code - preferredLocs.foreach (hostPort => Utils.checkHost(Utils.parseHostPort(hostPort)._1, "preferredLocs : " + preferredLocs)) + @transient private val preferredLocs: Seq[TaskLocation] = { + if (locs == null) Nil else locs.toSet.toSeq } - var split = if (rdd == null) { - null - } else { - rdd.partitions(partition) - } + var split = if (rdd == null) null else rdd.partitions(partition) override def writeExternal(out: ObjectOutput) { RDDCheckpointData.synchronized { @@ -106,7 +111,7 @@ private[spark] class ShuffleMapTask( out.writeInt(bytes.length) out.write(bytes) out.writeInt(partition) - out.writeLong(generation) + out.writeLong(epoch) out.writeObject(split) } } @@ -120,7 +125,7 @@ private[spark] class ShuffleMapTask( rdd = rdd_ dep = dep_ partition = in.readInt() - generation = in.readLong() + epoch = in.readLong() split = in.readObject().asInstanceOf[Partition] } @@ -142,7 +147,7 @@ private[spark] class ShuffleMapTask( // Write the map output to its associated buckets. for (elem <- rdd.iterator(split, taskContext)) { - val pair = elem.asInstanceOf[(Any, Any)] + val pair = elem.asInstanceOf[Product2[Any, Any]] val bucketId = dep.partitioner.getPartition(pair._1) buckets.writers(bucketId).write(pair) } @@ -180,7 +185,7 @@ private[spark] class ShuffleMapTask( } } - override def preferredLocations: Seq[String] = preferredLocs + override def preferredLocations: Seq[TaskLocation] = preferredLocs override def toString = "ShuffleMapTask(%d, %d)".format(stageId, partition) } diff --git a/core/src/main/scala/spark/scheduler/SparkListener.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala index 8de3aa91a4..c3cf4b8907 100644 --- a/core/src/main/scala/spark/scheduler/SparkListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala @@ -1,24 +1,44 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import java.util.Properties -import spark.scheduler.cluster.TaskInfo -import spark.util.Distribution -import spark.{Logging, SparkContext, TaskEndReason, Utils} -import spark.executor.TaskMetrics +import org.apache.spark.scheduler.cluster.TaskInfo +import org.apache.spark.util.{Utils, Distribution} +import org.apache.spark.{Logging, SparkContext, TaskEndReason} +import org.apache.spark.executor.TaskMetrics sealed trait SparkListenerEvents -case class SparkListenerStageSubmitted(stage: Stage, taskSize: Int) extends SparkListenerEvents +case class SparkListenerStageSubmitted(stage: Stage, taskSize: Int, properties: Properties) + extends SparkListenerEvents case class StageCompleted(val stageInfo: StageInfo) extends SparkListenerEvents +case class SparkListenerTaskStart(task: Task[_], taskInfo: TaskInfo) extends SparkListenerEvents + case class SparkListenerTaskEnd(task: Task[_], reason: TaskEndReason, taskInfo: TaskInfo, taskMetrics: TaskMetrics) extends SparkListenerEvents -case class SparkListenerJobStart(job: ActiveJob, properties: Properties = null) +case class SparkListenerJobStart(job: ActiveJob, properties: Properties = null) extends SparkListenerEvents -case class SparkListenerJobEnd(job: ActiveJob, jobResult: JobResult) +case class SparkListenerJobEnd(job: ActiveJob, jobResult: JobResult) extends SparkListenerEvents trait SparkListener { @@ -26,12 +46,17 @@ trait SparkListener { * Called when a stage is completed, with information on the completed stage */ def onStageCompleted(stageCompleted: StageCompleted) { } - + /** * Called when a stage is submitted */ def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) { } - + + /** + * Called when a task starts + */ + def onTaskStart(taskEnd: SparkListenerTaskStart) { } + /** * Called when a task ends */ @@ -41,12 +66,12 @@ trait SparkListener { * Called when a job starts */ def onJobStart(jobStart: SparkListenerJobStart) { } - + /** * Called when a job ends */ def onJobEnd(jobEnd: SparkListenerJobEnd) { } - + } /** @@ -54,7 +79,7 @@ trait SparkListener { */ class StatsReportListener extends SparkListener with Logging { override def onStageCompleted(stageCompleted: StageCompleted) { - import spark.scheduler.StatsReportListener._ + import org.apache.spark.scheduler.StatsReportListener._ implicit val sc = stageCompleted this.logInfo("Finished stage: " + stageCompleted.stageInfo) showMillisDistribution("task runtime:", (info, _) => Some(info.duration)) @@ -128,7 +153,7 @@ object StatsReportListener extends Logging { } def showBytesDistribution(heading: String, dist: Distribution) { - showDistribution(heading, dist, (d => Utils.memoryBytesToString(d.toLong)): Double => String) + showDistribution(heading, dist, (d => Utils.bytesToString(d.toLong)): Double => String) } def showMillisDistribution(heading: String, dOpt: Option[Distribution]) { diff --git a/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala new file mode 100644 index 0000000000..a65e1ecd6d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala @@ -0,0 +1,74 @@ +/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler
+
+import java.util.concurrent.LinkedBlockingQueue
+
+import scala.collection.mutable.{ArrayBuffer, SynchronizedBuffer}
+
+import org.apache.spark.Logging
+
+/** Asynchronously passes SparkListenerEvents to registered SparkListeners. */
+private[spark] class SparkListenerBus() extends Logging {
+ private val sparkListeners = new ArrayBuffer[SparkListener]() with SynchronizedBuffer[SparkListener]
+
+ /* Cap the capacity of the SparkListenerEvent queue so we get an explicit error (rather than
+ * an OOM exception) if it's perpetually being added to more quickly than it's being drained. */
+ private val EVENT_QUEUE_CAPACITY = 10000
+ private val eventQueue = new LinkedBlockingQueue[SparkListenerEvents](EVENT_QUEUE_CAPACITY)
+ private var queueFullErrorMessageLogged = false
+
+ new Thread("SparkListenerBus") {
+ setDaemon(true)
+ override def run() {
+ while (true) {
+ val event = eventQueue.take
+ event match {
+ case stageSubmitted: SparkListenerStageSubmitted =>
+ sparkListeners.foreach(_.onStageSubmitted(stageSubmitted))
+ case stageCompleted: StageCompleted =>
+ sparkListeners.foreach(_.onStageCompleted(stageCompleted))
+ case jobStart: SparkListenerJobStart =>
+ sparkListeners.foreach(_.onJobStart(jobStart))
+ case jobEnd: SparkListenerJobEnd =>
+ sparkListeners.foreach(_.onJobEnd(jobEnd))
+ case taskStart: SparkListenerTaskStart =>
+ sparkListeners.foreach(_.onTaskStart(taskStart))
+ case taskEnd: SparkListenerTaskEnd =>
+ sparkListeners.foreach(_.onTaskEnd(taskEnd))
+ case _ =>
+ }
+ }
+ }
+ }.start()
+
+ def addListener(listener: SparkListener) {
+ sparkListeners += listener
+ }
+
+ def post(event: SparkListenerEvents) {
+ val eventAdded = eventQueue.offer(event)
+ if (!eventAdded && !queueFullErrorMessageLogged) {
+ logError("Dropping SparkListenerEvent because no remaining room in event queue. " +
+ "This likely means one of the SparkListeners is too slow and cannot keep up with the " +
+ "rate at which tasks are being started by the scheduler.")
+ queueFullErrorMessageLogged = true
+ }
+ }
+}
+
diff --git a/core/src/main/scala/spark/scheduler/SplitInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/SplitInfo.scala index 6abfb7a1f7..5b40a3eb29 100644 --- a/core/src/main/scala/spark/scheduler/SplitInfo.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SplitInfo.scala @@ -1,4 +1,21 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import collection.mutable.ArrayBuffer diff --git a/core/src/main/scala/spark/scheduler/Stage.scala b/core/src/main/scala/org/apache/spark/scheduler/Stage.scala index 539cf8233b..aa293dc6b3 100644 --- a/core/src/main/scala/spark/scheduler/Stage.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/Stage.scala @@ -1,9 +1,25 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import java.net.URI +package org.apache.spark.scheduler -import spark._ -import spark.storage.BlockManagerId +import org.apache.spark._ +import org.apache.spark.rdd.RDD +import org.apache.spark.storage.BlockManagerId /** * A stage is a set of independent tasks all computing the same function that need to run as part @@ -16,15 +32,17 @@ import spark.storage.BlockManagerId * initiated a job (e.g. count(), save(), etc). For shuffle map stages, we also track the nodes * that each output partition is on. * - * Each Stage also has a priority, which is (by default) based on the job it was submitted in. - * This allows Stages from earlier jobs to be computed first or recovered faster on failure. + * Each Stage also has a jobId, identifying the job that first submitted the stage. When FIFO + * scheduling is used, this allows Stages from earlier jobs to be computed first or recovered + * faster on failure. */ private[spark] class Stage( val id: Int, val rdd: RDD[_], val shuffleDep: Option[ShuffleDependency[_,_]], // Output shuffle if stage is a map stage val parents: List[Stage], - val priority: Int) + val jobId: Int, + callSite: Option[String]) extends Logging { val isShuffleMap = shuffleDep != None @@ -85,7 +103,7 @@ private[spark] class Stage( return id } - def origin: String = rdd.origin + val name = callSite.getOrElse(rdd.origin) override def toString = "Stage " + id diff --git a/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala new file mode 100644 index 0000000000..72cb1c9ce8 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.apache.spark.scheduler.cluster.TaskInfo +import scala.collection._ +import org.apache.spark.executor.TaskMetrics + +case class StageInfo( + val stage: Stage, + val taskInfos: mutable.Buffer[(TaskInfo, TaskMetrics)] = mutable.Buffer[(TaskInfo, TaskMetrics)]() +) { + override def toString = stage.rdd.toString +} diff --git a/core/src/main/scala/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala index a6462c6968..598d91752a 100644 --- a/core/src/main/scala/spark/scheduler/Task.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala @@ -1,21 +1,38 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler -import spark.serializer.SerializerInstance +import org.apache.spark.serializer.SerializerInstance import java.io.{DataInputStream, DataOutputStream} import java.nio.ByteBuffer import it.unimi.dsi.fastutil.io.FastByteArrayOutputStream -import spark.util.ByteBufferInputStream +import org.apache.spark.util.ByteBufferInputStream import scala.collection.mutable.HashMap -import spark.executor.TaskMetrics +import org.apache.spark.executor.TaskMetrics /** * A task to execute on a worker node. */ private[spark] abstract class Task[T](val stageId: Int) extends Serializable { def run(attemptId: Long): T - def preferredLocations: Seq[String] = Nil + def preferredLocations: Seq[TaskLocation] = Nil - var generation: Long = -1 // Map output tracker generation. Will be set by TaskScheduler. + var epoch: Long = -1 // Map output tracker epoch. Will be set by TaskScheduler. var metrics: Option[TaskMetrics] = None diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskLocation.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskLocation.scala new file mode 100644 index 0000000000..67c9a6760b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskLocation.scala @@ -0,0 +1,34 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +/** + * A location where a task should run. This can either be a host or a (host, executorID) pair. + * In the latter case, we will prefer to launch the task on that executorID, but our next level + * of preference will be executors on the same host if this is not possible. + */ +private[spark] +class TaskLocation private (val host: String, val executorId: Option[String]) extends Serializable { + override def toString: String = "TaskLocation(" + host + ", " + executorId + ")" +} + +private[spark] object TaskLocation { + def apply(host: String, executorId: String) = new TaskLocation(host, Some(executorId)) + + def apply(host: String) = new TaskLocation(host, None) +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskResult.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskResult.scala new file mode 100644 index 0000000000..5c7e5bb977 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskResult.scala @@ -0,0 +1,73 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import java.io._ + +import scala.collection.mutable.Map +import org.apache.spark.executor.TaskMetrics +import org.apache.spark.{SparkEnv} +import java.nio.ByteBuffer +import org.apache.spark.util.Utils + +// Task result. Also contains updates to accumulator variables. +// TODO: Use of distributed cache to return result is a hack to get around +// what seems to be a bug with messages over 60KB in libprocess; fix it +private[spark] +class TaskResult[T](var value: T, var accumUpdates: Map[Long, Any], var metrics: TaskMetrics) + extends Externalizable +{ + def this() = this(null.asInstanceOf[T], null, null) + + override def writeExternal(out: ObjectOutput) { + + val objectSer = SparkEnv.get.serializer.newInstance() + val bb = objectSer.serialize(value) + + out.writeInt(bb.remaining()) + Utils.writeByteBuffer(bb, out) + + out.writeInt(accumUpdates.size) + for ((key, value) <- accumUpdates) { + out.writeLong(key) + out.writeObject(value) + } + out.writeObject(metrics) + } + + override def readExternal(in: ObjectInput) { + + val objectSer = SparkEnv.get.serializer.newInstance() + + val blen = in.readInt() + val byteVal = new Array[Byte](blen) + in.readFully(byteVal) + value = objectSer.deserialize(ByteBuffer.wrap(byteVal)) + + val numUpdates = in.readInt + if (numUpdates == 0) { + accumUpdates = null + } else { + accumUpdates = Map() + for (i <- 0 until numUpdates) { + accumUpdates(in.readLong()) = in.readObject() + } + } + metrics = in.readObject().asInstanceOf[TaskMetrics] + } +} diff --git a/core/src/main/scala/spark/scheduler/TaskScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala index 7787b54762..63be8ba3f5 100644 --- a/core/src/main/scala/spark/scheduler/TaskScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala @@ -1,5 +1,24 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler +import org.apache.spark.scheduler.cluster.Pool +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode /** * Low-level task scheduler interface, implemented by both ClusterScheduler and LocalScheduler. * These schedulers get sets of tasks submitted to them from the DAGScheduler for each stage, @@ -8,6 +27,11 @@ package spark.scheduler * the TaskSchedulerListener interface. */ private[spark] trait TaskScheduler { + + def rootPool: Pool + + def schedulingMode: SchedulingMode + def start(): Unit // Invoked after system has successfully initialized (typically in spark context). diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerListener.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerListener.scala new file mode 100644 index 0000000000..83be051c1a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerListener.scala @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.apache.spark.scheduler.cluster.TaskInfo +import scala.collection.mutable.Map + +import org.apache.spark.TaskEndReason +import org.apache.spark.executor.TaskMetrics + +/** + * Interface for getting events back from the TaskScheduler. + */ +private[spark] trait TaskSchedulerListener { + // A task has started. + def taskStarted(task: Task[_], taskInfo: TaskInfo) + + // A task has finished or failed. + def taskEnded(task: Task[_], reason: TaskEndReason, result: Any, accumUpdates: Map[Long, Any], + taskInfo: TaskInfo, taskMetrics: TaskMetrics): Unit + + // A node was added to the cluster. + def executorGained(execId: String, host: String): Unit + + // A node was lost from the cluster. + def executorLost(execId: String): Unit + + // The TaskScheduler wants to abort an entire task set. + def taskSetFailed(taskSet: TaskSet, reason: String): Unit +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSet.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSet.scala new file mode 100644 index 0000000000..c3ad325156 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSet.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import java.util.Properties + +/** + * A set of tasks submitted together to the low-level TaskScheduler, usually representing + * missing partitions of a particular stage. + */ +private[spark] class TaskSet( + val tasks: Array[Task[_]], + val stageId: Int, + val attempt: Int, + val priority: Int, + val properties: Properties) { + val id: String = stageId + "." + attempt + + override def toString: String = "TaskSet " + id +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterScheduler.scala new file mode 100644 index 0000000000..3196ab5022 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterScheduler.scala @@ -0,0 +1,440 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.lang.{Boolean => JBoolean} + +import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable.HashMap +import scala.collection.mutable.HashSet + +import org.apache.spark._ +import org.apache.spark.TaskState.TaskState +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode +import java.nio.ByteBuffer +import java.util.concurrent.atomic.AtomicLong +import java.util.{TimerTask, Timer} + +/** + * The main TaskScheduler implementation, for running tasks on a cluster. Clients should first call + * initialize() and start(), then submit task sets through the runTasks method. + * + * This class can work with multiple types of clusters by acting through a SchedulerBackend. + * It handles common logic, like determining a scheduling order across jobs, waking up to launch + * speculative tasks, etc. + * + * THREADING: SchedulerBackends and task-submitting clients can call this class from multiple + * threads, so it needs locks in public API methods to maintain its state. In addition, some + * SchedulerBackends sycnchronize on themselves when they want to send events here, and then + * acquire a lock on us, so we need to make sure that we don't try to lock the backend while + * we are holding a lock on ourselves. + */ +private[spark] class ClusterScheduler(val sc: SparkContext) + extends TaskScheduler + with Logging +{ + // How often to check for speculative tasks + val SPECULATION_INTERVAL = System.getProperty("spark.speculation.interval", "100").toLong + + // Threshold above which we warn user initial TaskSet may be starved + val STARVATION_TIMEOUT = System.getProperty("spark.starvation.timeout", "15000").toLong + + val activeTaskSets = new HashMap[String, TaskSetManager] + + val taskIdToTaskSetId = new HashMap[Long, String] + val taskIdToExecutorId = new HashMap[Long, String] + val taskSetTaskIds = new HashMap[String, HashSet[Long]] + + @volatile private var hasReceivedTask = false + @volatile private var hasLaunchedTask = false + private val starvationTimer = new Timer(true) + + // Incrementing Mesos task IDs + val nextTaskId = new AtomicLong(0) + + // Which executor IDs we have executors on + val activeExecutorIds = new HashSet[String] + + // The set of executors we have on each host; this is used to compute hostsAlive, which + // in turn is used to decide when we can attain data locality on a given host + private val executorsByHost = new HashMap[String, HashSet[String]] + + private val executorIdToHost = new HashMap[String, String] + + // JAR server, if any JARs were added by the user to the SparkContext + var jarServer: HttpServer = null + + // URIs of JARs to pass to executor + var jarUris: String = "" + + // Listener object to pass upcalls into + var listener: TaskSchedulerListener = null + + var backend: SchedulerBackend = null + + val mapOutputTracker = SparkEnv.get.mapOutputTracker + + var schedulableBuilder: SchedulableBuilder = null + var rootPool: Pool = null + // default scheduler is FIFO + val schedulingMode: SchedulingMode = SchedulingMode.withName( + System.getProperty("spark.cluster.schedulingmode", "FIFO")) + + override def setListener(listener: TaskSchedulerListener) { + this.listener = listener + } + + def initialize(context: SchedulerBackend) { + backend = context + // temporarily set rootPool name to empty + rootPool = new Pool("", schedulingMode, 0, 0) + schedulableBuilder = { + schedulingMode match { + case SchedulingMode.FIFO => + new FIFOSchedulableBuilder(rootPool) + case SchedulingMode.FAIR => + new FairSchedulableBuilder(rootPool) + } + } + schedulableBuilder.buildPools() + } + + def newTaskId(): Long = nextTaskId.getAndIncrement() + + override def start() { + backend.start() + + if (System.getProperty("spark.speculation", "false").toBoolean) { + new Thread("ClusterScheduler speculation check") { + setDaemon(true) + + override def run() { + logInfo("Starting speculative execution thread") + while (true) { + try { + Thread.sleep(SPECULATION_INTERVAL) + } catch { + case e: InterruptedException => {} + } + checkSpeculatableTasks() + } + } + }.start() + } + } + + override def submitTasks(taskSet: TaskSet) { + val tasks = taskSet.tasks + logInfo("Adding task set " + taskSet.id + " with " + tasks.length + " tasks") + this.synchronized { + val manager = new ClusterTaskSetManager(this, taskSet) + activeTaskSets(taskSet.id) = manager + schedulableBuilder.addTaskSetManager(manager, manager.taskSet.properties) + taskSetTaskIds(taskSet.id) = new HashSet[Long]() + + if (!hasReceivedTask) { + starvationTimer.scheduleAtFixedRate(new TimerTask() { + override def run() { + if (!hasLaunchedTask) { + logWarning("Initial job has not accepted any resources; " + + "check your cluster UI to ensure that workers are registered " + + "and have sufficient memory") + } else { + this.cancel() + } + } + }, STARVATION_TIMEOUT, STARVATION_TIMEOUT) + } + hasReceivedTask = true + } + backend.reviveOffers() + } + + def taskSetFinished(manager: TaskSetManager) { + this.synchronized { + activeTaskSets -= manager.taskSet.id + manager.parent.removeSchedulable(manager) + logInfo("Remove TaskSet %s from pool %s".format(manager.taskSet.id, manager.parent.name)) + taskIdToTaskSetId --= taskSetTaskIds(manager.taskSet.id) + taskIdToExecutorId --= taskSetTaskIds(manager.taskSet.id) + taskSetTaskIds.remove(manager.taskSet.id) + } + } + + /** + * Called by cluster manager to offer resources on slaves. We respond by asking our active task + * sets for tasks in order of priority. We fill each node with tasks in a round-robin manner so + * that tasks are balanced across the cluster. + */ + def resourceOffers(offers: Seq[WorkerOffer]): Seq[Seq[TaskDescription]] = synchronized { + SparkEnv.set(sc.env) + + // Mark each slave as alive and remember its hostname + for (o <- offers) { + executorIdToHost(o.executorId) = o.host + if (!executorsByHost.contains(o.host)) { + executorsByHost(o.host) = new HashSet[String]() + executorGained(o.executorId, o.host) + } + } + + // Build a list of tasks to assign to each worker + val tasks = offers.map(o => new ArrayBuffer[TaskDescription](o.cores)) + val availableCpus = offers.map(o => o.cores).toArray + val sortedTaskSets = rootPool.getSortedTaskSetQueue() + for (taskSet <- sortedTaskSets) { + logDebug("parentName: %s, name: %s, runningTasks: %s".format( + taskSet.parent.name, taskSet.name, taskSet.runningTasks)) + } + + // Take each TaskSet in our scheduling order, and then offer it each node in increasing order + // of locality levels so that it gets a chance to launch local tasks on all of them. + var launchedTask = false + for (taskSet <- sortedTaskSets; maxLocality <- TaskLocality.values) { + do { + launchedTask = false + for (i <- 0 until offers.size) { + val execId = offers(i).executorId + val host = offers(i).host + for (task <- taskSet.resourceOffer(execId, host, availableCpus(i), maxLocality)) { + tasks(i) += task + val tid = task.taskId + taskIdToTaskSetId(tid) = taskSet.taskSet.id + taskSetTaskIds(taskSet.taskSet.id) += tid + taskIdToExecutorId(tid) = execId + activeExecutorIds += execId + executorsByHost(host) += execId + availableCpus(i) -= 1 + launchedTask = true + } + } + } while (launchedTask) + } + + if (tasks.size > 0) { + hasLaunchedTask = true + } + return tasks + } + + def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { + var taskSetToUpdate: Option[TaskSetManager] = None + var failedExecutor: Option[String] = None + var taskFailed = false + synchronized { + try { + if (state == TaskState.LOST && taskIdToExecutorId.contains(tid)) { + // We lost this entire executor, so remember that it's gone + val execId = taskIdToExecutorId(tid) + if (activeExecutorIds.contains(execId)) { + removeExecutor(execId) + failedExecutor = Some(execId) + } + } + taskIdToTaskSetId.get(tid) match { + case Some(taskSetId) => + if (activeTaskSets.contains(taskSetId)) { + taskSetToUpdate = Some(activeTaskSets(taskSetId)) + } + if (TaskState.isFinished(state)) { + taskIdToTaskSetId.remove(tid) + if (taskSetTaskIds.contains(taskSetId)) { + taskSetTaskIds(taskSetId) -= tid + } + taskIdToExecutorId.remove(tid) + } + if (state == TaskState.FAILED) { + taskFailed = true + } + case None => + logInfo("Ignoring update from TID " + tid + " because its task set is gone") + } + } catch { + case e: Exception => logError("Exception in statusUpdate", e) + } + } + // Update the task set and DAGScheduler without holding a lock on this, since that can deadlock + if (taskSetToUpdate != None) { + taskSetToUpdate.get.statusUpdate(tid, state, serializedData) + } + if (failedExecutor != None) { + listener.executorLost(failedExecutor.get) + backend.reviveOffers() + } + if (taskFailed) { + // Also revive offers if a task had failed for some reason other than host lost + backend.reviveOffers() + } + } + + def error(message: String) { + synchronized { + if (activeTaskSets.size > 0) { + // Have each task set throw a SparkException with the error + for ((taskSetId, manager) <- activeTaskSets) { + try { + manager.error(message) + } catch { + case e: Exception => logError("Exception in error callback", e) + } + } + } else { + // No task sets are active but we still got an error. Just exit since this + // must mean the error is during registration. + // It might be good to do something smarter here in the future. + logError("Exiting due to error from cluster scheduler: " + message) + System.exit(1) + } + } + } + + override def stop() { + if (backend != null) { + backend.stop() + } + if (jarServer != null) { + jarServer.stop() + } + + // sleeping for an arbitrary 5 seconds : to ensure that messages are sent out. + // TODO: Do something better ! + Thread.sleep(5000L) + } + + override def defaultParallelism() = backend.defaultParallelism() + + + // Check for speculatable tasks in all our active jobs. + def checkSpeculatableTasks() { + var shouldRevive = false + synchronized { + shouldRevive = rootPool.checkSpeculatableTasks() + } + if (shouldRevive) { + backend.reviveOffers() + } + } + + // Check for pending tasks in all our active jobs. + def hasPendingTasks: Boolean = { + synchronized { + rootPool.hasPendingTasks() + } + } + + def executorLost(executorId: String, reason: ExecutorLossReason) { + var failedExecutor: Option[String] = None + + synchronized { + if (activeExecutorIds.contains(executorId)) { + val hostPort = executorIdToHost(executorId) + logError("Lost executor %s on %s: %s".format(executorId, hostPort, reason)) + removeExecutor(executorId) + failedExecutor = Some(executorId) + } else { + // We may get multiple executorLost() calls with different loss reasons. For example, one + // may be triggered by a dropped connection from the slave while another may be a report + // of executor termination from Mesos. We produce log messages for both so we eventually + // report the termination reason. + logError("Lost an executor " + executorId + " (already removed): " + reason) + } + } + // Call listener.executorLost without holding the lock on this to prevent deadlock + if (failedExecutor != None) { + listener.executorLost(failedExecutor.get) + backend.reviveOffers() + } + } + + /** Remove an executor from all our data structures and mark it as lost */ + private def removeExecutor(executorId: String) { + activeExecutorIds -= executorId + val host = executorIdToHost(executorId) + val execs = executorsByHost.getOrElse(host, new HashSet) + execs -= executorId + if (execs.isEmpty) { + executorsByHost -= host + } + executorIdToHost -= executorId + rootPool.executorLost(executorId, host) + } + + def executorGained(execId: String, host: String) { + listener.executorGained(execId, host) + } + + def getExecutorsAliveOnHost(host: String): Option[Set[String]] = synchronized { + executorsByHost.get(host).map(_.toSet) + } + + def hasExecutorsAliveOnHost(host: String): Boolean = synchronized { + executorsByHost.contains(host) + } + + def isExecutorAlive(execId: String): Boolean = synchronized { + activeExecutorIds.contains(execId) + } + + // By default, rack is unknown + def getRackForHost(value: String): Option[String] = None +} + + +object ClusterScheduler { + /** + * Used to balance containers across hosts. + * + * Accepts a map of hosts to resource offers for that host, and returns a prioritized list of + * resource offers representing the order in which the offers should be used. The resource + * offers are ordered such that we'll allocate one container on each host before allocating a + * second container on any host, and so on, in order to reduce the damage if a host fails. + * + * For example, given <h1, [o1, o2, o3]>, <h2, [o4]>, <h1, [o5, o6]>, returns + * [o1, o5, o4, 02, o6, o3] + */ + def prioritizeContainers[K, T] (map: HashMap[K, ArrayBuffer[T]]): List[T] = { + val _keyList = new ArrayBuffer[K](map.size) + _keyList ++= map.keys + + // order keyList based on population of value in map + val keyList = _keyList.sortWith( + (left, right) => map(left).size > map(right).size + ) + + val retval = new ArrayBuffer[T](keyList.size * 2) + var index = 0 + var found = true + + while (found) { + found = false + for (key <- keyList) { + val containerList: ArrayBuffer[T] = map.get(key).getOrElse(null) + assert(containerList != null) + // Get the index'th entry for this host - if present + if (index < containerList.size){ + retval += containerList.apply(index) + found = true + } + } + index += 1 + } + + retval.toList + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManager.scala new file mode 100644 index 0000000000..1b31c8c57e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManager.scala @@ -0,0 +1,712 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.nio.ByteBuffer +import java.util.{Arrays, NoSuchElementException} + +import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable.HashMap +import scala.collection.mutable.HashSet +import scala.math.max +import scala.math.min + +import org.apache.spark.{FetchFailed, Logging, Resubmitted, SparkEnv, Success, TaskEndReason, TaskState} +import org.apache.spark.{ExceptionFailure, SparkException, TaskResultTooBigFailure} +import org.apache.spark.TaskState.TaskState +import org.apache.spark.scheduler._ +import scala.Some +import org.apache.spark.FetchFailed +import org.apache.spark.ExceptionFailure +import org.apache.spark.TaskResultTooBigFailure +import org.apache.spark.util.{SystemClock, Clock} + + +/** + * Schedules the tasks within a single TaskSet in the ClusterScheduler. This class keeps track of + * the status of each task, retries tasks if they fail (up to a limited number of times), and + * handles locality-aware scheduling for this TaskSet via delay scheduling. The main interfaces + * to it are resourceOffer, which asks the TaskSet whether it wants to run a task on one node, + * and statusUpdate, which tells it that one of its tasks changed state (e.g. finished). + * + * THREADING: This class is designed to only be called from code with a lock on the + * ClusterScheduler (e.g. its event handlers). It should not be called from other threads. + */ +private[spark] class ClusterTaskSetManager( + sched: ClusterScheduler, + val taskSet: TaskSet, + clock: Clock = SystemClock) + extends TaskSetManager + with Logging +{ + // CPUs to request per task + val CPUS_PER_TASK = System.getProperty("spark.task.cpus", "1").toInt + + // Maximum times a task is allowed to fail before failing the job + val MAX_TASK_FAILURES = System.getProperty("spark.task.maxFailures", "4").toInt + + // Quantile of tasks at which to start speculation + val SPECULATION_QUANTILE = System.getProperty("spark.speculation.quantile", "0.75").toDouble + val SPECULATION_MULTIPLIER = System.getProperty("spark.speculation.multiplier", "1.5").toDouble + + // Serializer for closures and tasks. + val env = SparkEnv.get + val ser = env.closureSerializer.newInstance() + + val tasks = taskSet.tasks + val numTasks = tasks.length + val copiesRunning = new Array[Int](numTasks) + val finished = new Array[Boolean](numTasks) + val numFailures = new Array[Int](numTasks) + val taskAttempts = Array.fill[List[TaskInfo]](numTasks)(Nil) + var tasksFinished = 0 + + var weight = 1 + var minShare = 0 + var runningTasks = 0 + var priority = taskSet.priority + var stageId = taskSet.stageId + var name = "TaskSet_"+taskSet.stageId.toString + var parent: Schedulable = null + + // Set of pending tasks for each executor. These collections are actually + // treated as stacks, in which new tasks are added to the end of the + // ArrayBuffer and removed from the end. This makes it faster to detect + // tasks that repeatedly fail because whenever a task failed, it is put + // back at the head of the stack. They are also only cleaned up lazily; + // when a task is launched, it remains in all the pending lists except + // the one that it was launched from, but gets removed from them later. + private val pendingTasksForExecutor = new HashMap[String, ArrayBuffer[Int]] + + // Set of pending tasks for each host. Similar to pendingTasksForExecutor, + // but at host level. + private val pendingTasksForHost = new HashMap[String, ArrayBuffer[Int]] + + // Set of pending tasks for each rack -- similar to the above. + private val pendingTasksForRack = new HashMap[String, ArrayBuffer[Int]] + + // Set containing pending tasks with no locality preferences. + val pendingTasksWithNoPrefs = new ArrayBuffer[Int] + + // Set containing all pending tasks (also used as a stack, as above). + val allPendingTasks = new ArrayBuffer[Int] + + // Tasks that can be speculated. Since these will be a small fraction of total + // tasks, we'll just hold them in a HashSet. + val speculatableTasks = new HashSet[Int] + + // Task index, start and finish time for each task attempt (indexed by task ID) + val taskInfos = new HashMap[Long, TaskInfo] + + // Did the TaskSet fail? + var failed = false + var causeOfFailure = "" + + // How frequently to reprint duplicate exceptions in full, in milliseconds + val EXCEPTION_PRINT_INTERVAL = + System.getProperty("spark.logging.exceptionPrintInterval", "10000").toLong + + // Map of recent exceptions (identified by string representation and top stack frame) to + // duplicate count (how many times the same exception has appeared) and time the full exception + // was printed. This should ideally be an LRU map that can drop old exceptions automatically. + val recentExceptions = HashMap[String, (Int, Long)]() + + // Figure out the current map output tracker epoch and set it on all tasks + val epoch = sched.mapOutputTracker.getEpoch + logDebug("Epoch for " + taskSet + ": " + epoch) + for (t <- tasks) { + t.epoch = epoch + } + + // Add all our tasks to the pending lists. We do this in reverse order + // of task index so that tasks with low indices get launched first. + for (i <- (0 until numTasks).reverse) { + addPendingTask(i) + } + + // Figure out which locality levels we have in our TaskSet, so we can do delay scheduling + val myLocalityLevels = computeValidLocalityLevels() + val localityWaits = myLocalityLevels.map(getLocalityWait) // Time to wait at each level + + // Delay scheduling variables: we keep track of our current locality level and the time we + // last launched a task at that level, and move up a level when localityWaits[curLevel] expires. + // We then move down if we manage to launch a "more local" task. + var currentLocalityIndex = 0 // Index of our current locality level in validLocalityLevels + var lastLaunchTime = clock.getTime() // Time we last launched a task at this level + + /** + * Add a task to all the pending-task lists that it should be on. If readding is set, we are + * re-adding the task so only include it in each list if it's not already there. + */ + private def addPendingTask(index: Int, readding: Boolean = false) { + // Utility method that adds `index` to a list only if readding=false or it's not already there + def addTo(list: ArrayBuffer[Int]) { + if (!readding || !list.contains(index)) { + list += index + } + } + + var hadAliveLocations = false + for (loc <- tasks(index).preferredLocations) { + for (execId <- loc.executorId) { + if (sched.isExecutorAlive(execId)) { + addTo(pendingTasksForExecutor.getOrElseUpdate(execId, new ArrayBuffer)) + hadAliveLocations = true + } + } + if (sched.hasExecutorsAliveOnHost(loc.host)) { + addTo(pendingTasksForHost.getOrElseUpdate(loc.host, new ArrayBuffer)) + for (rack <- sched.getRackForHost(loc.host)) { + addTo(pendingTasksForRack.getOrElseUpdate(rack, new ArrayBuffer)) + } + hadAliveLocations = true + } + } + + if (!hadAliveLocations) { + // Even though the task might've had preferred locations, all of those hosts or executors + // are dead; put it in the no-prefs list so we can schedule it elsewhere right away. + addTo(pendingTasksWithNoPrefs) + } + + if (!readding) { + allPendingTasks += index // No point scanning this whole list to find the old task there + } + } + + /** + * Return the pending tasks list for a given executor ID, or an empty list if + * there is no map entry for that host + */ + private def getPendingTasksForExecutor(executorId: String): ArrayBuffer[Int] = { + pendingTasksForExecutor.getOrElse(executorId, ArrayBuffer()) + } + + /** + * Return the pending tasks list for a given host, or an empty list if + * there is no map entry for that host + */ + private def getPendingTasksForHost(host: String): ArrayBuffer[Int] = { + pendingTasksForHost.getOrElse(host, ArrayBuffer()) + } + + /** + * Return the pending rack-local task list for a given rack, or an empty list if + * there is no map entry for that rack + */ + private def getPendingTasksForRack(rack: String): ArrayBuffer[Int] = { + pendingTasksForRack.getOrElse(rack, ArrayBuffer()) + } + + /** + * Dequeue a pending task from the given list and return its index. + * Return None if the list is empty. + * This method also cleans up any tasks in the list that have already + * been launched, since we want that to happen lazily. + */ + private def findTaskFromList(list: ArrayBuffer[Int]): Option[Int] = { + while (!list.isEmpty) { + val index = list.last + list.trimEnd(1) + if (copiesRunning(index) == 0 && !finished(index)) { + return Some(index) + } + } + return None + } + + /** Check whether a task is currently running an attempt on a given host */ + private def hasAttemptOnHost(taskIndex: Int, host: String): Boolean = { + !taskAttempts(taskIndex).exists(_.host == host) + } + + /** + * Return a speculative task for a given executor if any are available. The task should not have + * an attempt running on this host, in case the host is slow. In addition, the task should meet + * the given locality constraint. + */ + private def findSpeculativeTask(execId: String, host: String, locality: TaskLocality.Value) + : Option[(Int, TaskLocality.Value)] = + { + speculatableTasks.retain(index => !finished(index)) // Remove finished tasks from set + + if (!speculatableTasks.isEmpty) { + // Check for process-local or preference-less tasks; note that tasks can be process-local + // on multiple nodes when we replicate cached blocks, as in Spark Streaming + for (index <- speculatableTasks if !hasAttemptOnHost(index, host)) { + val prefs = tasks(index).preferredLocations + val executors = prefs.flatMap(_.executorId) + if (prefs.size == 0 || executors.contains(execId)) { + speculatableTasks -= index + return Some((index, TaskLocality.PROCESS_LOCAL)) + } + } + + // Check for node-local tasks + if (TaskLocality.isAllowed(locality, TaskLocality.NODE_LOCAL)) { + for (index <- speculatableTasks if !hasAttemptOnHost(index, host)) { + val locations = tasks(index).preferredLocations.map(_.host) + if (locations.contains(host)) { + speculatableTasks -= index + return Some((index, TaskLocality.NODE_LOCAL)) + } + } + } + + // Check for rack-local tasks + if (TaskLocality.isAllowed(locality, TaskLocality.RACK_LOCAL)) { + for (rack <- sched.getRackForHost(host)) { + for (index <- speculatableTasks if !hasAttemptOnHost(index, host)) { + val racks = tasks(index).preferredLocations.map(_.host).map(sched.getRackForHost) + if (racks.contains(rack)) { + speculatableTasks -= index + return Some((index, TaskLocality.RACK_LOCAL)) + } + } + } + } + + // Check for non-local tasks + if (TaskLocality.isAllowed(locality, TaskLocality.ANY)) { + for (index <- speculatableTasks if !hasAttemptOnHost(index, host)) { + speculatableTasks -= index + return Some((index, TaskLocality.ANY)) + } + } + } + + return None + } + + /** + * Dequeue a pending task for a given node and return its index and locality level. + * Only search for tasks matching the given locality constraint. + */ + private def findTask(execId: String, host: String, locality: TaskLocality.Value) + : Option[(Int, TaskLocality.Value)] = + { + for (index <- findTaskFromList(getPendingTasksForExecutor(execId))) { + return Some((index, TaskLocality.PROCESS_LOCAL)) + } + + if (TaskLocality.isAllowed(locality, TaskLocality.NODE_LOCAL)) { + for (index <- findTaskFromList(getPendingTasksForHost(host))) { + return Some((index, TaskLocality.NODE_LOCAL)) + } + } + + if (TaskLocality.isAllowed(locality, TaskLocality.RACK_LOCAL)) { + for { + rack <- sched.getRackForHost(host) + index <- findTaskFromList(getPendingTasksForRack(rack)) + } { + return Some((index, TaskLocality.RACK_LOCAL)) + } + } + + // Look for no-pref tasks after rack-local tasks since they can run anywhere. + for (index <- findTaskFromList(pendingTasksWithNoPrefs)) { + return Some((index, TaskLocality.PROCESS_LOCAL)) + } + + if (TaskLocality.isAllowed(locality, TaskLocality.ANY)) { + for (index <- findTaskFromList(allPendingTasks)) { + return Some((index, TaskLocality.ANY)) + } + } + + // Finally, if all else has failed, find a speculative task + return findSpeculativeTask(execId, host, locality) + } + + /** + * Respond to an offer of a single slave from the scheduler by finding a task + */ + override def resourceOffer( + execId: String, + host: String, + availableCpus: Int, + maxLocality: TaskLocality.TaskLocality) + : Option[TaskDescription] = + { + if (tasksFinished < numTasks && availableCpus >= CPUS_PER_TASK) { + val curTime = clock.getTime() + + var allowedLocality = getAllowedLocalityLevel(curTime) + if (allowedLocality > maxLocality) { + allowedLocality = maxLocality // We're not allowed to search for farther-away tasks + } + + findTask(execId, host, allowedLocality) match { + case Some((index, taskLocality)) => { + // Found a task; do some bookkeeping and return a task description + val task = tasks(index) + val taskId = sched.newTaskId() + // Figure out whether this should count as a preferred launch + logInfo("Starting task %s:%d as TID %s on slave %s: %s (%s)".format( + taskSet.id, index, taskId, execId, host, taskLocality)) + // Do various bookkeeping + copiesRunning(index) += 1 + val info = new TaskInfo(taskId, index, curTime, execId, host, taskLocality) + taskInfos(taskId) = info + taskAttempts(index) = info :: taskAttempts(index) + // Update our locality level for delay scheduling + currentLocalityIndex = getLocalityIndex(taskLocality) + lastLaunchTime = curTime + // Serialize and return the task + val startTime = clock.getTime() + // We rely on the DAGScheduler to catch non-serializable closures and RDDs, so in here + // we assume the task can be serialized without exceptions. + val serializedTask = Task.serializeWithDependencies( + task, sched.sc.addedFiles, sched.sc.addedJars, ser) + val timeTaken = clock.getTime() - startTime + increaseRunningTasks(1) + logInfo("Serialized task %s:%d as %d bytes in %d ms".format( + taskSet.id, index, serializedTask.limit, timeTaken)) + val taskName = "task %s:%d".format(taskSet.id, index) + if (taskAttempts(index).size == 1) + taskStarted(task,info) + return Some(new TaskDescription(taskId, execId, taskName, index, serializedTask)) + } + case _ => + } + } + return None + } + + /** + * Get the level we can launch tasks according to delay scheduling, based on current wait time. + */ + private def getAllowedLocalityLevel(curTime: Long): TaskLocality.TaskLocality = { + while (curTime - lastLaunchTime >= localityWaits(currentLocalityIndex) && + currentLocalityIndex < myLocalityLevels.length - 1) + { + // Jump to the next locality level, and remove our waiting time for the current one since + // we don't want to count it again on the next one + lastLaunchTime += localityWaits(currentLocalityIndex) + currentLocalityIndex += 1 + } + myLocalityLevels(currentLocalityIndex) + } + + /** + * Find the index in myLocalityLevels for a given locality. This is also designed to work with + * localities that are not in myLocalityLevels (in case we somehow get those) by returning the + * next-biggest level we have. Uses the fact that the last value in myLocalityLevels is ANY. + */ + def getLocalityIndex(locality: TaskLocality.TaskLocality): Int = { + var index = 0 + while (locality > myLocalityLevels(index)) { + index += 1 + } + index + } + + /** Called by cluster scheduler when one of our tasks changes state */ + override def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { + SparkEnv.set(env) + state match { + case TaskState.FINISHED => + taskFinished(tid, state, serializedData) + case TaskState.LOST => + taskLost(tid, state, serializedData) + case TaskState.FAILED => + taskLost(tid, state, serializedData) + case TaskState.KILLED => + taskLost(tid, state, serializedData) + case _ => + } + } + + def taskStarted(task: Task[_], info: TaskInfo) { + sched.listener.taskStarted(task, info) + } + + def taskFinished(tid: Long, state: TaskState, serializedData: ByteBuffer) { + val info = taskInfos(tid) + if (info.failed) { + // We might get two task-lost messages for the same task in coarse-grained Mesos mode, + // or even from Mesos itself when acks get delayed. + return + } + val index = info.index + info.markSuccessful() + decreaseRunningTasks(1) + if (!finished(index)) { + tasksFinished += 1 + logInfo("Finished TID %s in %d ms on %s (progress: %d/%d)".format( + tid, info.duration, info.host, tasksFinished, numTasks)) + // Deserialize task result and pass it to the scheduler + try { + val result = ser.deserialize[TaskResult[_]](serializedData) + result.metrics.resultSize = serializedData.limit() + sched.listener.taskEnded( + tasks(index), Success, result.value, result.accumUpdates, info, result.metrics) + } catch { + case cnf: ClassNotFoundException => + val loader = Thread.currentThread().getContextClassLoader + throw new SparkException("ClassNotFound with classloader: " + loader, cnf) + case ex => throw ex + } + // Mark finished and stop if we've finished all the tasks + finished(index) = true + if (tasksFinished == numTasks) { + sched.taskSetFinished(this) + } + } else { + logInfo("Ignoring task-finished event for TID " + tid + + " because task " + index + " is already finished") + } + } + + def taskLost(tid: Long, state: TaskState, serializedData: ByteBuffer) { + val info = taskInfos(tid) + if (info.failed) { + // We might get two task-lost messages for the same task in coarse-grained Mesos mode, + // or even from Mesos itself when acks get delayed. + return + } + val index = info.index + info.markFailed() + decreaseRunningTasks(1) + if (!finished(index)) { + logInfo("Lost TID %s (task %s:%d)".format(tid, taskSet.id, index)) + copiesRunning(index) -= 1 + // Check if the problem is a map output fetch failure. In that case, this + // task will never succeed on any node, so tell the scheduler about it. + if (serializedData != null && serializedData.limit() > 0) { + val reason = ser.deserialize[TaskEndReason](serializedData, getClass.getClassLoader) + reason match { + case fetchFailed: FetchFailed => + logInfo("Loss was due to fetch failure from " + fetchFailed.bmAddress) + sched.listener.taskEnded(tasks(index), fetchFailed, null, null, info, null) + finished(index) = true + tasksFinished += 1 + sched.taskSetFinished(this) + decreaseRunningTasks(runningTasks) + return + + case taskResultTooBig: TaskResultTooBigFailure => + logInfo("Loss was due to task %s result exceeding Akka frame size; aborting job".format( + tid)) + abort("Task %s result exceeded Akka frame size".format(tid)) + return + + case ef: ExceptionFailure => + sched.listener.taskEnded(tasks(index), ef, null, null, info, ef.metrics.getOrElse(null)) + val key = ef.description + val now = clock.getTime() + val (printFull, dupCount) = { + if (recentExceptions.contains(key)) { + val (dupCount, printTime) = recentExceptions(key) + if (now - printTime > EXCEPTION_PRINT_INTERVAL) { + recentExceptions(key) = (0, now) + (true, 0) + } else { + recentExceptions(key) = (dupCount + 1, printTime) + (false, dupCount + 1) + } + } else { + recentExceptions(key) = (0, now) + (true, 0) + } + } + if (printFull) { + val locs = ef.stackTrace.map(loc => "\tat %s".format(loc.toString)) + logInfo("Loss was due to %s\n%s\n%s".format( + ef.className, ef.description, locs.mkString("\n"))) + } else { + logInfo("Loss was due to %s [duplicate %d]".format(ef.description, dupCount)) + } + + case _ => {} + } + } + // On non-fetch failures, re-enqueue the task as pending for a max number of retries + addPendingTask(index) + // Count failed attempts only on FAILED and LOST state (not on KILLED) + if (state == TaskState.FAILED || state == TaskState.LOST) { + numFailures(index) += 1 + if (numFailures(index) > MAX_TASK_FAILURES) { + logError("Task %s:%d failed more than %d times; aborting job".format( + taskSet.id, index, MAX_TASK_FAILURES)) + abort("Task %s:%d failed more than %d times".format(taskSet.id, index, MAX_TASK_FAILURES)) + } + } + } else { + logInfo("Ignoring task-lost event for TID " + tid + + " because task " + index + " is already finished") + } + } + + override def error(message: String) { + // Save the error message + abort("Error: " + message) + } + + def abort(message: String) { + failed = true + causeOfFailure = message + // TODO: Kill running tasks if we were not terminated due to a Mesos error + sched.listener.taskSetFailed(taskSet, message) + decreaseRunningTasks(runningTasks) + sched.taskSetFinished(this) + } + + override def increaseRunningTasks(taskNum: Int) { + runningTasks += taskNum + if (parent != null) { + parent.increaseRunningTasks(taskNum) + } + } + + override def decreaseRunningTasks(taskNum: Int) { + runningTasks -= taskNum + if (parent != null) { + parent.decreaseRunningTasks(taskNum) + } + } + + override def getSchedulableByName(name: String): Schedulable = { + return null + } + + override def addSchedulable(schedulable: Schedulable) {} + + override def removeSchedulable(schedulable: Schedulable) {} + + override def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] = { + var sortedTaskSetQueue = ArrayBuffer[TaskSetManager](this) + sortedTaskSetQueue += this + return sortedTaskSetQueue + } + + /** Called by cluster scheduler when an executor is lost so we can re-enqueue our tasks */ + override def executorLost(execId: String, host: String) { + logInfo("Re-queueing tasks for " + execId + " from TaskSet " + taskSet.id) + + // Re-enqueue pending tasks for this host based on the status of the cluster -- for example, a + // task that used to have locations on only this host might now go to the no-prefs list. Note + // that it's okay if we add a task to the same queue twice (if it had multiple preferred + // locations), because findTaskFromList will skip already-running tasks. + for (index <- getPendingTasksForExecutor(execId)) { + addPendingTask(index, readding=true) + } + for (index <- getPendingTasksForHost(host)) { + addPendingTask(index, readding=true) + } + + // Re-enqueue any tasks that ran on the failed executor if this is a shuffle map stage + if (tasks(0).isInstanceOf[ShuffleMapTask]) { + for ((tid, info) <- taskInfos if info.executorId == execId) { + val index = taskInfos(tid).index + if (finished(index)) { + finished(index) = false + copiesRunning(index) -= 1 + tasksFinished -= 1 + addPendingTask(index) + // Tell the DAGScheduler that this task was resubmitted so that it doesn't think our + // stage finishes when a total of tasks.size tasks finish. + sched.listener.taskEnded(tasks(index), Resubmitted, null, null, info, null) + } + } + } + // Also re-enqueue any tasks that were running on the node + for ((tid, info) <- taskInfos if info.running && info.executorId == execId) { + taskLost(tid, TaskState.KILLED, null) + } + } + + /** + * Check for tasks to be speculated and return true if there are any. This is called periodically + * by the ClusterScheduler. + * + * TODO: To make this scale to large jobs, we need to maintain a list of running tasks, so that + * we don't scan the whole task set. It might also help to make this sorted by launch time. + */ + override def checkSpeculatableTasks(): Boolean = { + // Can't speculate if we only have one task, or if all tasks have finished. + if (numTasks == 1 || tasksFinished == numTasks) { + return false + } + var foundTasks = false + val minFinishedForSpeculation = (SPECULATION_QUANTILE * numTasks).floor.toInt + logDebug("Checking for speculative tasks: minFinished = " + minFinishedForSpeculation) + if (tasksFinished >= minFinishedForSpeculation) { + val time = clock.getTime() + val durations = taskInfos.values.filter(_.successful).map(_.duration).toArray + Arrays.sort(durations) + val medianDuration = durations(min((0.5 * numTasks).round.toInt, durations.size - 1)) + val threshold = max(SPECULATION_MULTIPLIER * medianDuration, 100) + // TODO: Threshold should also look at standard deviation of task durations and have a lower + // bound based on that. + logDebug("Task length threshold for speculation: " + threshold) + for ((tid, info) <- taskInfos) { + val index = info.index + if (!finished(index) && copiesRunning(index) == 1 && info.timeRunning(time) > threshold && + !speculatableTasks.contains(index)) { + logInfo( + "Marking task %s:%d (on %s) as speculatable because it ran more than %.0f ms".format( + taskSet.id, index, info.host, threshold)) + speculatableTasks += index + foundTasks = true + } + } + } + return foundTasks + } + + override def hasPendingTasks(): Boolean = { + numTasks > 0 && tasksFinished < numTasks + } + + private def getLocalityWait(level: TaskLocality.TaskLocality): Long = { + val defaultWait = System.getProperty("spark.locality.wait", "3000") + level match { + case TaskLocality.PROCESS_LOCAL => + System.getProperty("spark.locality.wait.process", defaultWait).toLong + case TaskLocality.NODE_LOCAL => + System.getProperty("spark.locality.wait.node", defaultWait).toLong + case TaskLocality.RACK_LOCAL => + System.getProperty("spark.locality.wait.rack", defaultWait).toLong + case TaskLocality.ANY => + 0L + } + } + + /** + * Compute the locality levels used in this TaskSet. Assumes that all tasks have already been + * added to queues using addPendingTask. + */ + private def computeValidLocalityLevels(): Array[TaskLocality.TaskLocality] = { + import TaskLocality.{PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL, ANY} + val levels = new ArrayBuffer[TaskLocality.TaskLocality] + if (!pendingTasksForExecutor.isEmpty && getLocalityWait(PROCESS_LOCAL) != 0) { + levels += PROCESS_LOCAL + } + if (!pendingTasksForHost.isEmpty && getLocalityWait(NODE_LOCAL) != 0) { + levels += NODE_LOCAL + } + if (!pendingTasksForRack.isEmpty && getLocalityWait(RACK_LOCAL) != 0) { + levels += RACK_LOCAL + } + levels += ANY + logDebug("Valid locality levels for " + taskSet + ": " + levels.mkString(", ")) + levels.toArray + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorLossReason.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorLossReason.scala new file mode 100644 index 0000000000..5077b2b48b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorLossReason.scala @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import org.apache.spark.executor.ExecutorExitCode + +/** + * Represents an explanation for a executor or whole slave failing or exiting. + */ +private[spark] +class ExecutorLossReason(val message: String) { + override def toString: String = message +} + +private[spark] +case class ExecutorExited(val exitCode: Int) + extends ExecutorLossReason(ExecutorExitCode.explainExitCode(exitCode)) { +} + +private[spark] +case class SlaveLost(_message: String = "Slave lost") + extends ExecutorLossReason(_message) { +} diff --git a/core/src/main/scala/spark/scheduler/cluster/Pool.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/Pool.scala index 941ba7a3f1..35b32600da 100644 --- a/core/src/main/scala/spark/scheduler/cluster/Pool.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/Pool.scala @@ -1,10 +1,27 @@ -package spark.scheduler.cluster +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashMap -import spark.Logging -import spark.scheduler.cluster.SchedulingMode.SchedulingMode +import org.apache.spark.Logging +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode /** * An Schedulable entity that represent collection of Pools or TaskSetManagers diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/Schedulable.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/Schedulable.scala new file mode 100644 index 0000000000..f4726450ec --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/Schedulable.scala @@ -0,0 +1,48 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode + +import scala.collection.mutable.ArrayBuffer +/** + * An interface for schedulable entities. + * there are two type of Schedulable entities(Pools and TaskSetManagers) + */ +private[spark] trait Schedulable { + var parent: Schedulable + // child queues + def schedulableQueue: ArrayBuffer[Schedulable] + def schedulingMode: SchedulingMode + def weight: Int + def minShare: Int + def runningTasks: Int + def priority: Int + def stageId: Int + def name: String + + def increaseRunningTasks(taskNum: Int): Unit + def decreaseRunningTasks(taskNum: Int): Unit + def addSchedulable(schedulable: Schedulable): Unit + def removeSchedulable(schedulable: Schedulable): Unit + def getSchedulableByName(name: String): Schedulable + def executorLost(executorId: String, host: String): Unit + def checkSpeculatableTasks(): Boolean + def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] + def hasPendingTasks(): Boolean +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulableBuilder.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulableBuilder.scala new file mode 100644 index 0000000000..d04eeb6b98 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulableBuilder.scala @@ -0,0 +1,137 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.io.{File, FileInputStream, FileOutputStream, FileNotFoundException} +import java.util.Properties + +import scala.xml.XML + +import org.apache.spark.Logging +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode + + +/** + * An interface to build Schedulable tree + * buildPools: build the tree nodes(pools) + * addTaskSetManager: build the leaf nodes(TaskSetManagers) + */ +private[spark] trait SchedulableBuilder { + def buildPools() + def addTaskSetManager(manager: Schedulable, properties: Properties) +} + +private[spark] class FIFOSchedulableBuilder(val rootPool: Pool) + extends SchedulableBuilder with Logging { + + override def buildPools() { + // nothing + } + + override def addTaskSetManager(manager: Schedulable, properties: Properties) { + rootPool.addSchedulable(manager) + } +} + +private[spark] class FairSchedulableBuilder(val rootPool: Pool) + extends SchedulableBuilder with Logging { + + val schedulerAllocFile = System.getProperty("spark.fairscheduler.allocation.file") + val FAIR_SCHEDULER_PROPERTIES = "spark.scheduler.cluster.fair.pool" + val DEFAULT_POOL_NAME = "default" + val MINIMUM_SHARES_PROPERTY = "minShare" + val SCHEDULING_MODE_PROPERTY = "schedulingMode" + val WEIGHT_PROPERTY = "weight" + val POOL_NAME_PROPERTY = "@name" + val POOLS_PROPERTY = "pool" + val DEFAULT_SCHEDULING_MODE = SchedulingMode.FIFO + val DEFAULT_MINIMUM_SHARE = 2 + val DEFAULT_WEIGHT = 1 + + override def buildPools() { + if (schedulerAllocFile != null) { + val file = new File(schedulerAllocFile) + if (file.exists()) { + val xml = XML.loadFile(file) + for (poolNode <- (xml \\ POOLS_PROPERTY)) { + + val poolName = (poolNode \ POOL_NAME_PROPERTY).text + var schedulingMode = DEFAULT_SCHEDULING_MODE + var minShare = DEFAULT_MINIMUM_SHARE + var weight = DEFAULT_WEIGHT + + val xmlSchedulingMode = (poolNode \ SCHEDULING_MODE_PROPERTY).text + if (xmlSchedulingMode != "") { + try { + schedulingMode = SchedulingMode.withName(xmlSchedulingMode) + } catch { + case e: Exception => logInfo("Error xml schedulingMode, using default schedulingMode") + } + } + + val xmlMinShare = (poolNode \ MINIMUM_SHARES_PROPERTY).text + if (xmlMinShare != "") { + minShare = xmlMinShare.toInt + } + + val xmlWeight = (poolNode \ WEIGHT_PROPERTY).text + if (xmlWeight != "") { + weight = xmlWeight.toInt + } + + val pool = new Pool(poolName, schedulingMode, minShare, weight) + rootPool.addSchedulable(pool) + logInfo("Created pool %s, schedulingMode: %s, minShare: %d, weight: %d".format( + poolName, schedulingMode, minShare, weight)) + } + } else { + throw new java.io.FileNotFoundException( + "Fair scheduler allocation file not found: " + schedulerAllocFile) + } + } + + // finally create "default" pool + if (rootPool.getSchedulableByName(DEFAULT_POOL_NAME) == null) { + val pool = new Pool(DEFAULT_POOL_NAME, DEFAULT_SCHEDULING_MODE, + DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT) + rootPool.addSchedulable(pool) + logInfo("Created default pool %s, schedulingMode: %s, minShare: %d, weight: %d".format( + DEFAULT_POOL_NAME, DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT)) + } + } + + override def addTaskSetManager(manager: Schedulable, properties: Properties) { + var poolName = DEFAULT_POOL_NAME + var parentPool = rootPool.getSchedulableByName(poolName) + if (properties != null) { + poolName = properties.getProperty(FAIR_SCHEDULER_PROPERTIES, DEFAULT_POOL_NAME) + parentPool = rootPool.getSchedulableByName(poolName) + if (parentPool == null) { + // we will create a new pool that user has configured in app + // instead of being defined in xml file + parentPool = new Pool(poolName, DEFAULT_SCHEDULING_MODE, + DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT) + rootPool.addSchedulable(parentPool) + logInfo("Created pool %s, schedulingMode: %s, minShare: %d, weight: %d".format( + poolName, DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT)) + } + } + parentPool.addSchedulable(manager) + logInfo("Added task set " + manager.name + " tasks to pool "+poolName) + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulerBackend.scala new file mode 100644 index 0000000000..d57eb3276f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulerBackend.scala @@ -0,0 +1,37 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import org.apache.spark.{SparkContext} + +/** + * A backend interface for cluster scheduling systems that allows plugging in different ones under + * ClusterScheduler. We assume a Mesos-like model where the application gets resource offers as + * machines become available and can launch tasks on them. + */ +private[spark] trait SchedulerBackend { + def start(): Unit + def stop(): Unit + def reviveOffers(): Unit + def defaultParallelism(): Int + + // Memory used by each executor (in megabytes) + protected val executorMemory: Int = SparkContext.executorMemoryRequested + + // TODO: Probably want to add a killTask too +} diff --git a/core/src/main/scala/spark/scheduler/cluster/SchedulingAlgorithm.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulingAlgorithm.scala index f33310a34a..cbeed4731a 100644 --- a/core/src/main/scala/spark/scheduler/cluster/SchedulingAlgorithm.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulingAlgorithm.scala @@ -1,4 +1,21 @@ -package spark.scheduler.cluster +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster /** * An interface for sort algorithm diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulingMode.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulingMode.scala new file mode 100644 index 0000000000..34811389a0 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SchedulingMode.scala @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +/** + * "FAIR" and "FIFO" determines which policy is used + * to order tasks amongst a Schedulable's sub-queues + * "NONE" is used when the a Schedulable has no sub-queues. + */ +object SchedulingMode extends Enumeration("FAIR", "FIFO", "NONE") { + + type SchedulingMode = Value + val FAIR,FIFO,NONE = Value +} diff --git a/core/src/main/scala/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala index 170ede0f44..9a2cf20de7 100644 --- a/core/src/main/scala/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala @@ -1,9 +1,27 @@ -package spark.scheduler.cluster +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import spark.{Utils, Logging, SparkContext} -import spark.deploy.client.{Client, ClientListener} -import spark.deploy.{Command, ApplicationDescription} +package org.apache.spark.scheduler.cluster + +import org.apache.spark.{Logging, SparkContext} +import org.apache.spark.deploy.client.{Client, ClientListener} +import org.apache.spark.deploy.{Command, ApplicationDescription} import scala.collection.mutable.HashMap +import org.apache.spark.util.Utils private[spark] class SparkDeploySchedulerBackend( scheduler: ClusterScheduler, @@ -28,11 +46,11 @@ private[spark] class SparkDeploySchedulerBackend( System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"), StandaloneSchedulerBackend.ACTOR_NAME) val args = Seq(driverUrl, "{{EXECUTOR_ID}}", "{{HOSTNAME}}", "{{CORES}}") - val command = Command("spark.executor.StandaloneExecutorBackend", args, sc.executorEnvs) - val sparkHome = sc.getSparkHome().getOrElse( - throw new IllegalArgumentException("must supply spark home for spark standalone")) + val command = Command( + "org.apache.spark.executor.StandaloneExecutorBackend", args, sc.executorEnvs) + val sparkHome = sc.getSparkHome().getOrElse(null) val appDesc = new ApplicationDescription(appName, maxCores, executorMemory, command, sparkHome, - sc.ui.appUIAddress) + "http://" + sc.ui.appUIAddress) client = new Client(sc.env.actorSystem, master, appDesc, this) client.start() @@ -60,7 +78,7 @@ private[spark] class SparkDeploySchedulerBackend( override def executorAdded(executorId: String, workerId: String, hostPort: String, cores: Int, memory: Int) { logInfo("Granted executor ID %s on hostPort %s with %d cores, %s RAM".format( - executorId, hostPort, cores, Utils.memoryMegabytesToString(memory))) + executorId, hostPort, cores, Utils.megabytesToString(memory))) } override def executorRemoved(executorId: String, message: String, exitStatus: Option[Int]) { diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneClusterMessage.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneClusterMessage.scala new file mode 100644 index 0000000000..9c36d221f6 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneClusterMessage.scala @@ -0,0 +1,62 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.nio.ByteBuffer + +import org.apache.spark.TaskState.TaskState +import org.apache.spark.util.{Utils, SerializableBuffer} + + +private[spark] sealed trait StandaloneClusterMessage extends Serializable + +private[spark] object StandaloneClusterMessages { + + // Driver to executors + case class LaunchTask(task: TaskDescription) extends StandaloneClusterMessage + + case class RegisteredExecutor(sparkProperties: Seq[(String, String)]) + extends StandaloneClusterMessage + + case class RegisterExecutorFailed(message: String) extends StandaloneClusterMessage + + // Executors to driver + case class RegisterExecutor(executorId: String, hostPort: String, cores: Int) + extends StandaloneClusterMessage { + Utils.checkHostPort(hostPort, "Expected host port") + } + + case class StatusUpdate(executorId: String, taskId: Long, state: TaskState, + data: SerializableBuffer) extends StandaloneClusterMessage + + object StatusUpdate { + /** Alternate factory method that takes a ByteBuffer directly for the data field */ + def apply(executorId: String, taskId: Long, state: TaskState, data: ByteBuffer) + : StatusUpdate = { + StatusUpdate(executorId, taskId, state, new SerializableBuffer(data)) + } + } + + // Internal messages in driver + case object ReviveOffers extends StandaloneClusterMessage + + case object StopDriver extends StandaloneClusterMessage + + case class RemoveExecutor(executorId: String, reason: String) extends StandaloneClusterMessage + +} diff --git a/core/src/main/scala/spark/scheduler/cluster/StandaloneSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala index 16131215c8..addfa077c1 100644 --- a/core/src/main/scala/spark/scheduler/cluster/StandaloneSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala @@ -1,17 +1,36 @@ -package spark.scheduler.cluster +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} +package org.apache.spark.scheduler.cluster -import akka.actor._ -import scala.concurrent.duration._ -import akka.pattern.ask +import java.util.concurrent.atomic.AtomicInteger -import spark.{Utils, SparkException, Logging, TaskState} +import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} import scala.concurrent.Await +import scala.concurrent.duration._ -import java.util.concurrent.atomic.AtomicInteger +import akka.actor._ +import akka.pattern.ask import akka.remote.{RemoteClientShutdown, RemoteClientDisconnected, RemoteClientLifeCycleEvent} +import org.apache.spark.{SparkException, Logging, TaskState} +import org.apache.spark.scheduler.cluster.StandaloneClusterMessages._ +import org.apache.spark.util.Utils + /** * A standalone scheduler backend, which waits for standalone executors to connect to it through * Akka. These may be executed in a variety of ways, such as Mesos tasks for the coarse-grained @@ -19,15 +38,15 @@ import akka.remote.{RemoteClientShutdown, RemoteClientDisconnected, RemoteClient */ private[spark] class StandaloneSchedulerBackend(scheduler: ClusterScheduler, actorSystem: ActorSystem) - extends SchedulerBackend with Logging { - + extends SchedulerBackend with Logging +{ // Use an atomic variable to track total number of cores in the cluster for simplicity and speed var totalCoreCount = new AtomicInteger(0) class DriverActor(sparkProperties: Seq[(String, String)]) extends Actor { private val executorActor = new HashMap[String, ActorRef] private val executorAddress = new HashMap[String, Address] - private val executorHostPort = new HashMap[String, String] + private val executorHost = new HashMap[String, String] private val freeCores = new HashMap[String, Int] private val actorToExecutorId = new HashMap[ActorRef, String] private val addressToExecutorId = new HashMap[Address, String] @@ -35,6 +54,11 @@ class StandaloneSchedulerBackend(scheduler: ClusterScheduler, actorSystem: Actor override def preStart() { // Listen for remote client disconnection events, since they don't go through Akka's watch() context.system.eventStream.subscribe(self, classOf[RemoteClientLifeCycleEvent]) + + // Periodically revive offers to allow delay scheduling to work + val reviveInterval = System.getProperty("spark.scheduler.revive.interval", "1000").toLong + import context.dispatcher + context.system.scheduler.schedule(0.millis, reviveInterval.millis, self, ReviveOffers) } def receive = { @@ -47,7 +71,7 @@ class StandaloneSchedulerBackend(scheduler: ClusterScheduler, actorSystem: Actor sender ! RegisteredExecutor(sparkProperties) context.watch(sender) executorActor(executorId) = sender - executorHostPort(executorId) = hostPort + executorHost(executorId) = Utils.parseHostPort(hostPort)._1 freeCores(executorId) = cores executorAddress(executorId) = sender.path.address actorToExecutorId(sender) = executorId @@ -87,13 +111,13 @@ class StandaloneSchedulerBackend(scheduler: ClusterScheduler, actorSystem: Actor // Make fake resource offers on all executors def makeOffers() { launchTasks(scheduler.resourceOffers( - executorHostPort.toArray.map {case (id, hostPort) => new WorkerOffer(id, hostPort, freeCores(id))})) + executorHost.toArray.map {case (id, host) => new WorkerOffer(id, host, freeCores(id))})) } // Make fake resource offers on just one executor def makeOffers(executorId: String) { launchTasks(scheduler.resourceOffers( - Seq(new WorkerOffer(executorId, executorHostPort(executorId), freeCores(executorId))))) + Seq(new WorkerOffer(executorId, executorHost(executorId), freeCores(executorId))))) } // Launch tasks returned by a set of resource offers @@ -112,9 +136,8 @@ class StandaloneSchedulerBackend(scheduler: ClusterScheduler, actorSystem: Actor actorToExecutorId -= executorActor(executorId) addressToExecutorId -= executorAddress(executorId) executorActor -= executorId - executorHostPort -= executorId + executorHost -= executorId freeCores -= executorId - executorHostPort -= executorId totalCoreCount.addAndGet(-numCores) scheduler.executorLost(executorId, SlaveLost(reason)) } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskDescription.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskDescription.scala new file mode 100644 index 0000000000..309ac2f6c9 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskDescription.scala @@ -0,0 +1,37 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.nio.ByteBuffer +import org.apache.spark.util.SerializableBuffer + +private[spark] class TaskDescription( + val taskId: Long, + val executorId: String, + val name: String, + val index: Int, // Index within this task's TaskSet + _serializedTask: ByteBuffer) + extends Serializable { + + // Because ByteBuffers are not serializable, wrap the task in a SerializableBuffer + private val buffer = new SerializableBuffer(_serializedTask) + + def serializedTask: ByteBuffer = buffer.value + + override def toString: String = "TaskDescription(TID=%d, index=%d)".format(taskId, index) +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskInfo.scala new file mode 100644 index 0000000000..9685fb1a67 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskInfo.scala @@ -0,0 +1,72 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import org.apache.spark.util.Utils + +/** + * Information about a running task attempt inside a TaskSet. + */ +private[spark] +class TaskInfo( + val taskId: Long, + val index: Int, + val launchTime: Long, + val executorId: String, + val host: String, + val taskLocality: TaskLocality.TaskLocality) { + + var finishTime: Long = 0 + var failed = false + + def markSuccessful(time: Long = System.currentTimeMillis) { + finishTime = time + } + + def markFailed(time: Long = System.currentTimeMillis) { + finishTime = time + failed = true + } + + def finished: Boolean = finishTime != 0 + + def successful: Boolean = finished && !failed + + def running: Boolean = !finished + + def status: String = { + if (running) + "RUNNING" + else if (failed) + "FAILED" + else if (successful) + "SUCCESS" + else + "UNKNOWN" + } + + def duration: Long = { + if (!finished) { + throw new UnsupportedOperationException("duration() called on unfinished tasks") + } else { + finishTime - launchTime + } + } + + def timeRunning(currentTime: Long): Long = currentTime - launchTime +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskLocality.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskLocality.scala new file mode 100644 index 0000000000..5d4130e14a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskLocality.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + + +private[spark] object TaskLocality + extends Enumeration("PROCESS_LOCAL", "NODE_LOCAL", "RACK_LOCAL", "ANY") +{ + // process local is expected to be used ONLY within tasksetmanager for now. + val PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL, ANY = Value + + type TaskLocality = Value + + def isAllowed(constraint: TaskLocality, condition: TaskLocality): Boolean = { + condition <= constraint + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskSetManager.scala new file mode 100644 index 0000000000..648a3ef922 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/TaskSetManager.scala @@ -0,0 +1,51 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import java.nio.ByteBuffer + +import org.apache.spark.TaskState.TaskState +import org.apache.spark.scheduler.TaskSet + +/** + * Tracks and schedules the tasks within a single TaskSet. This class keeps track of the status of + * each task and is responsible for retries on failure and locality. The main interfaces to it + * are resourceOffer, which asks the TaskSet whether it wants to run a task on one node, and + * statusUpdate, which tells it that one of its tasks changed state (e.g. finished). + * + * THREADING: This class is designed to only be called from code with a lock on the TaskScheduler + * (e.g. its event handlers). It should not be called from other threads. + */ +private[spark] trait TaskSetManager extends Schedulable { + def schedulableQueue = null + + def schedulingMode = SchedulingMode.NONE + + def taskSet: TaskSet + + def resourceOffer( + execId: String, + host: String, + availableCpus: Int, + maxLocality: TaskLocality.TaskLocality) + : Option[TaskDescription] + + def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) + + def error(message: String) +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/WorkerOffer.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/WorkerOffer.scala new file mode 100644 index 0000000000..938f62883a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/WorkerOffer.scala @@ -0,0 +1,24 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +/** + * Represents free resources available on an executor. + */ +private[spark] +class WorkerOffer(val executorId: String, val host: String, val cores: Int) diff --git a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalScheduler.scala index b000e328e6..e8fa5e2f17 100644 --- a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalScheduler.scala @@ -1,18 +1,40 @@ -package spark.scheduler.local +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.local import java.io.File +import java.lang.management.ManagementFactory import java.util.concurrent.atomic.AtomicInteger import java.nio.ByteBuffer + +import scala.collection.JavaConversions._ import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashMap import scala.collection.mutable.HashSet -import spark._ -import spark.TaskState.TaskState -import spark.executor.ExecutorURLClassLoader -import spark.scheduler._ -import spark.scheduler.cluster._ +import org.apache.spark._ +import org.apache.spark.TaskState.TaskState +import org.apache.spark.executor.ExecutorURLClassLoader +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster._ +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode import akka.actor._ +import org.apache.spark.util.Utils /** * A FIFO or Fair TaskScheduler implementation that runs tasks locally in a thread pool. Optionally @@ -20,10 +42,15 @@ import akka.actor._ * testing fault recovery. */ -private[spark] case class LocalReviveOffers() -private[spark] case class LocalStatusUpdate(taskId: Long, state: TaskState, serializedData: ByteBuffer) +private[spark] +case class LocalReviveOffers() + +private[spark] +case class LocalStatusUpdate(taskId: Long, state: TaskState, serializedData: ByteBuffer) + +private[spark] +class LocalActor(localScheduler: LocalScheduler, var freeCores: Int) extends Actor with Logging { -private[spark] class LocalActor(localScheduler: LocalScheduler, var freeCores: Int) extends Actor with Logging { def receive = { case LocalReviveOffers => launchTask(localScheduler.resourceOffer(freeCores)) @@ -38,7 +65,7 @@ private[spark] class LocalActor(localScheduler: LocalScheduler, var freeCores: I freeCores -= 1 localScheduler.threadPool.submit(new Runnable { def run() { - localScheduler.runTask(task.taskId,task.serializedTask) + localScheduler.runTask(task.taskId, task.serializedTask) } }) } @@ -63,6 +90,8 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: var schedulableBuilder: SchedulableBuilder = null var rootPool: Pool = null + val schedulingMode: SchedulingMode = SchedulingMode.withName( + System.getProperty("spark.cluster.schedulingmode", "FIFO")) val activeTaskSets = new HashMap[String, TaskSetManager] val taskIdToTaskSetId = new HashMap[Long, String] val taskSetTaskIds = new HashMap[String, HashSet[Long]] @@ -70,15 +99,13 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: var localActor: ActorRef = null override def start() { - //default scheduler is FIFO - val schedulingMode = System.getProperty("spark.cluster.schedulingmode", "FIFO") - //temporarily set rootPool name to empty - rootPool = new Pool("", SchedulingMode.withName(schedulingMode), 0, 0) + // temporarily set rootPool name to empty + rootPool = new Pool("", schedulingMode, 0, 0) schedulableBuilder = { schedulingMode match { - case "FIFO" => + case SchedulingMode.FIFO => new FIFOSchedulableBuilder(rootPool) - case "FAIR" => + case SchedulingMode.FAIR => new FairSchedulableBuilder(rootPool) } } @@ -93,7 +120,7 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: override def submitTasks(taskSet: TaskSet) { synchronized { - var manager = new LocalTaskSetManager(this, taskSet) + val manager = new LocalTaskSetManager(this, taskSet) schedulableBuilder.addTaskSetManager(manager, manager.taskSet.properties) activeTaskSets(taskSet.id) = manager taskSetTaskIds(taskSet.id) = new HashSet[Long]() @@ -107,14 +134,15 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: val tasks = new ArrayBuffer[TaskDescription](freeCores) val sortedTaskSetQueue = rootPool.getSortedTaskSetQueue() for (manager <- sortedTaskSetQueue) { - logDebug("parentName:%s,name:%s,runningTasks:%s".format(manager.parent.name, manager.name, manager.runningTasks)) + logDebug("parentName:%s,name:%s,runningTasks:%s".format( + manager.parent.name, manager.name, manager.runningTasks)) } var launchTask = false for (manager <- sortedTaskSetQueue) { do { launchTask = false - manager.slaveOffer(null,null,freeCpuCores) match { + manager.resourceOffer(null, null, freeCpuCores, null) match { case Some(task) => tasks += task taskIdToTaskSetId(task.taskId) = manager.taskSet.id @@ -122,7 +150,7 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: freeCpuCores -= 1 launchTask = true case None => {} - } + } } while(launchTask) } return tasks @@ -145,9 +173,13 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: // Set the Spark execution environment for the worker thread SparkEnv.set(env) val ser = SparkEnv.get.closureSerializer.newInstance() - var attemptedTask: Option[Task[_]] = None + val objectSer = SparkEnv.get.serializer.newInstance() + var attemptedTask: Option[Task[_]] = None val start = System.currentTimeMillis() var taskStart: Long = 0 + def getTotalGCTime = ManagementFactory.getGarbageCollectorMXBeans.map(g => g.getCollectionTime).sum + val startGCTime = getTotalGCTime + try { Accumulators.clear() Thread.currentThread().setContextClassLoader(classLoader) @@ -169,14 +201,15 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: // executor does. This is useful to catch serialization errors early // on in development (so when users move their local Spark programs // to the cluster, they don't get surprised by serialization errors). - val serResult = ser.serialize(result) + val serResult = objectSer.serialize(result) deserializedTask.metrics.get.resultSize = serResult.limit() - val resultToReturn = ser.deserialize[Any](serResult) + val resultToReturn = objectSer.deserialize[Any](serResult) val accumUpdates = ser.deserialize[collection.mutable.Map[Long, Any]]( ser.serialize(Accumulators.values)) val serviceTime = System.currentTimeMillis() - taskStart logInfo("Finished " + taskId) deserializedTask.metrics.get.executorRunTime = serviceTime.toInt + deserializedTask.metrics.get.jvmGCTime = getTotalGCTime - startGCTime deserializedTask.metrics.get.executorDeserializeTime = deserTime.toInt val taskResult = new TaskResult(result, accumUpdates, deserializedTask.metrics.getOrElse(null)) val serializedResult = ser.serialize(taskResult) @@ -185,7 +218,10 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc: case t: Throwable => { val serviceTime = System.currentTimeMillis() - taskStart val metrics = attemptedTask.flatMap(t => t.metrics) - metrics.foreach{m => m.executorRunTime = serviceTime.toInt} + for (m <- metrics) { + m.executorRunTime = serviceTime.toInt + m.jvmGCTime = getTotalGCTime - startGCTime + } val failure = new ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace, metrics) localActor ! LocalStatusUpdate(taskId, TaskState.FAILED, ser.serialize(failure)) } diff --git a/core/src/main/scala/spark/scheduler/local/LocalTaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalTaskSetManager.scala index f12fec41d5..e52cb998bd 100644 --- a/core/src/main/scala/spark/scheduler/local/LocalTaskSetManager.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalTaskSetManager.scala @@ -1,80 +1,93 @@ -package spark.scheduler.local +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.local -import java.io.File -import java.util.concurrent.atomic.AtomicInteger import java.nio.ByteBuffer import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashMap -import scala.collection.mutable.HashSet -import spark._ -import spark.TaskState.TaskState -import spark.scheduler._ -import spark.scheduler.cluster._ +import org.apache.spark.{ExceptionFailure, Logging, SparkEnv, Success, TaskState} +import org.apache.spark.TaskState.TaskState +import org.apache.spark.scheduler.{Task, TaskResult, TaskSet} +import org.apache.spark.scheduler.cluster.{Schedulable, TaskDescription, TaskInfo, TaskLocality, TaskSetManager} + + +private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: TaskSet) + extends TaskSetManager with Logging { -private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: TaskSet) extends TaskSetManager with Logging { var parent: Schedulable = null var weight: Int = 1 var minShare: Int = 0 var runningTasks: Int = 0 var priority: Int = taskSet.priority var stageId: Int = taskSet.stageId - var name: String = "TaskSet_"+taskSet.stageId.toString - + var name: String = "TaskSet_" + taskSet.stageId.toString var failCount = new Array[Int](taskSet.tasks.size) val taskInfos = new HashMap[Long, TaskInfo] val numTasks = taskSet.tasks.size var numFinished = 0 - val ser = SparkEnv.get.closureSerializer.newInstance() + val env = SparkEnv.get + val ser = env.closureSerializer.newInstance() val copiesRunning = new Array[Int](numTasks) val finished = new Array[Boolean](numTasks) val numFailures = new Array[Int](numTasks) val MAX_TASK_FAILURES = sched.maxFailures - def increaseRunningTasks(taskNum: Int): Unit = { - runningTasks += taskNum - if (parent != null) { - parent.increaseRunningTasks(taskNum) - } + override def increaseRunningTasks(taskNum: Int): Unit = { + runningTasks += taskNum + if (parent != null) { + parent.increaseRunningTasks(taskNum) + } } - def decreaseRunningTasks(taskNum: Int): Unit = { + override def decreaseRunningTasks(taskNum: Int): Unit = { runningTasks -= taskNum if (parent != null) { parent.decreaseRunningTasks(taskNum) } } - def addSchedulable(schedulable: Schedulable): Unit = { - //nothing + override def addSchedulable(schedulable: Schedulable): Unit = { + // nothing } - def removeSchedulable(schedulable: Schedulable): Unit = { - //nothing + override def removeSchedulable(schedulable: Schedulable): Unit = { + // nothing } - def getSchedulableByName(name: String): Schedulable = { + override def getSchedulableByName(name: String): Schedulable = { return null } - def executorLost(executorId: String, host: String): Unit = { - //nothing + override def executorLost(executorId: String, host: String): Unit = { + // nothing } - def checkSpeculatableTasks(): Boolean = { - return true - } + override def checkSpeculatableTasks() = true - def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] = { + override def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] = { var sortedTaskSetQueue = new ArrayBuffer[TaskSetManager] sortedTaskSetQueue += this return sortedTaskSetQueue } - def hasPendingTasks(): Boolean = { - return true - } + override def hasPendingTasks() = true def findTask(): Option[Int] = { for (i <- 0 to numTasks-1) { @@ -85,41 +98,42 @@ private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: Tas return None } - def slaveOffer(execId: String, hostPort: String, availableCpus: Double, overrideLocality: TaskLocality.TaskLocality = null): Option[TaskDescription] = { + override def resourceOffer( + execId: String, + host: String, + availableCpus: Int, + maxLocality: TaskLocality.TaskLocality) + : Option[TaskDescription] = + { SparkEnv.set(sched.env) - logDebug("availableCpus:%d,numFinished:%d,numTasks:%d".format(availableCpus.toInt, numFinished, numTasks)) + logDebug("availableCpus:%d, numFinished:%d, numTasks:%d".format( + availableCpus.toInt, numFinished, numTasks)) if (availableCpus > 0 && numFinished < numTasks) { findTask() match { case Some(index) => val taskId = sched.attemptId.getAndIncrement() val task = taskSet.tasks(index) - val info = new TaskInfo(taskId, index, System.currentTimeMillis(), "local", "local:1", TaskLocality.NODE_LOCAL) + val info = new TaskInfo(taskId, index, System.currentTimeMillis(), "local", "local:1", + TaskLocality.NODE_LOCAL) taskInfos(taskId) = info - val bytes = Task.serializeWithDependencies(task, sched.sc.addedFiles, sched.sc.addedJars, ser) + // We rely on the DAGScheduler to catch non-serializable closures and RDDs, so in here + // we assume the task can be serialized without exceptions. + val bytes = Task.serializeWithDependencies( + task, sched.sc.addedFiles, sched.sc.addedJars, ser) logInfo("Size of task " + taskId + " is " + bytes.limit + " bytes") val taskName = "task %s:%d".format(taskSet.id, index) copiesRunning(index) += 1 increaseRunningTasks(1) - return Some(new TaskDescription(taskId, null, taskName, bytes)) + taskStarted(task, info) + return Some(new TaskDescription(taskId, null, taskName, index, bytes)) case None => {} } } return None } - def numPendingTasksForHostPort(hostPort: String): Int = { - return 0 - } - - def numRackLocalPendingTasksForHost(hostPort :String): Int = { - return 0 - } - - def numPendingTasksForHost(hostPort: String): Int = { - return 0 - } - - def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { + override def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { + SparkEnv.set(env) state match { case TaskState.FINISHED => taskEnded(tid, state, serializedData) @@ -129,6 +143,10 @@ private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: Tas } } + def taskStarted(task: Task[_], info: TaskInfo) { + sched.listener.taskStarted(task, info) + } + def taskEnded(tid: Long, state: TaskState, serializedData: ByteBuffer) { val info = taskInfos(tid) val index = info.index @@ -151,15 +169,18 @@ private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: Tas val task = taskSet.tasks(index) info.markFailed() decreaseRunningTasks(1) - val reason: ExceptionFailure = ser.deserialize[ExceptionFailure](serializedData, getClass.getClassLoader) + val reason: ExceptionFailure = ser.deserialize[ExceptionFailure]( + serializedData, getClass.getClassLoader) sched.listener.taskEnded(task, reason, null, null, info, reason.metrics.getOrElse(null)) if (!finished(index)) { copiesRunning(index) -= 1 numFailures(index) += 1 val locs = reason.stackTrace.map(loc => "\tat %s".format(loc.toString)) - logInfo("Loss was due to %s\n%s\n%s".format(reason.className, reason.description, locs.mkString("\n"))) + logInfo("Loss was due to %s\n%s\n%s".format( + reason.className, reason.description, locs.mkString("\n"))) if (numFailures(index) > MAX_TASK_FAILURES) { - val errorMessage = "Task %s:%d failed more than %d times; aborting job %s".format(taskSet.id, index, 4, reason.description) + val errorMessage = "Task %s:%d failed more than %d times; aborting job %s".format( + taskSet.id, index, 4, reason.description) decreaseRunningTasks(runningTasks) sched.listener.taskSetFailed(taskSet, errorMessage) // need to delete failed Taskset from schedule queue @@ -168,6 +189,6 @@ private[spark] class LocalTaskSetManager(sched: LocalScheduler, val taskSet: Tas } } - def error(message: String) { + override def error(message: String) { } } diff --git a/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala index f4a2994b6d..3dbe61d706 100644 --- a/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala @@ -1,4 +1,21 @@ -package spark.scheduler.mesos +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.mesos import com.google.protobuf.ByteString @@ -6,14 +23,14 @@ import org.apache.mesos.{Scheduler => MScheduler} import org.apache.mesos._ import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, TaskState => MesosTaskState, _} -import spark.{SparkException, Utils, Logging, SparkContext} +import org.apache.spark.{SparkException, Logging, SparkContext} import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} import scala.collection.JavaConversions._ import java.io.File -import spark.scheduler.cluster._ +import org.apache.spark.scheduler.cluster._ import java.util.{ArrayList => JArrayList, List => JList} import java.util.Collections -import spark.TaskState +import org.apache.spark.TaskState /** * A SchedulerBackend that runs tasks on Mesos, but uses "coarse-grained" tasks, where it holds @@ -93,12 +110,6 @@ private[spark] class CoarseMesosSchedulerBackend( } def createCommand(offer: Offer, numCores: Int): CommandInfo = { - val runScript = new File(sparkHome, "run").getCanonicalPath - val driverUrl = "akka://spark@%s:%s/user/%s".format( - System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"), - StandaloneSchedulerBackend.ACTOR_NAME) - val command = "\"%s\" spark.executor.StandaloneExecutorBackend %s %s %s %d".format( - runScript, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores) val environment = Environment.newBuilder() sc.executorEnvs.foreach { case (key, value) => environment.addVariables(Environment.Variable.newBuilder() @@ -106,7 +117,28 @@ private[spark] class CoarseMesosSchedulerBackend( .setValue(value) .build()) } - return CommandInfo.newBuilder().setValue(command).setEnvironment(environment).build() + val command = CommandInfo.newBuilder() + .setEnvironment(environment) + val driverUrl = "akka://spark@%s:%s/user/%s".format( + System.getProperty("spark.driver.host"), + System.getProperty("spark.driver.port"), + StandaloneSchedulerBackend.ACTOR_NAME) + val uri = System.getProperty("spark.executor.uri") + if (uri == null) { + val runScript = new File(sparkHome, "spark-class").getCanonicalPath + command.setValue( + "\"%s\" org.apache.spark.executor.StandaloneExecutorBackend %s %s %s %d".format( + runScript, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores)) + } else { + // Grab everything to the first '.'. We'll use that and '*' to + // glob the directory "correctly". + val basename = uri.split('/').last.split('.').head + command.setValue( + "cd %s*; ./spark-class org.apache.spark.executor.StandaloneExecutorBackend %s %s %s %d".format( + basename, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores)) + command.addUris(CommandInfo.URI.newBuilder().setValue(uri)) + } + return command.build() } override def offerRescinded(d: SchedulerDriver, o: OfferID) {} diff --git a/core/src/main/scala/spark/scheduler/mesos/MesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackend.scala index e83368b98d..541f86e338 100644 --- a/core/src/main/scala/spark/scheduler/mesos/MesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackend.scala @@ -1,4 +1,21 @@ -package spark.scheduler.mesos +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.mesos import com.google.protobuf.ByteString @@ -6,14 +23,15 @@ import org.apache.mesos.{Scheduler => MScheduler} import org.apache.mesos._ import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, TaskState => MesosTaskState, _} -import spark.{SparkException, Utils, Logging, SparkContext} +import org.apache.spark.{SparkException, Logging, SparkContext} import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} import scala.collection.JavaConversions._ import java.io.File -import spark.scheduler.cluster._ +import org.apache.spark.scheduler.cluster._ import java.util.{ArrayList => JArrayList, List => JList} import java.util.Collections -import spark.TaskState +import org.apache.spark.TaskState +import org.apache.spark.util.Utils /** * A SchedulerBackend for running fine-grained tasks on Mesos. Each Spark task is mapped to a @@ -72,7 +90,6 @@ private[spark] class MesosSchedulerBackend( val sparkHome = sc.getSparkHome().getOrElse(throw new SparkException( "Spark home is not set; set it through the spark.home system " + "property, the SPARK_HOME environment variable or the SparkContext constructor")) - val execScript = new File(sparkHome, "spark-executor").getCanonicalPath val environment = Environment.newBuilder() sc.executorEnvs.foreach { case (key, value) => environment.addVariables(Environment.Variable.newBuilder() @@ -80,15 +97,23 @@ private[spark] class MesosSchedulerBackend( .setValue(value) .build()) } + val command = CommandInfo.newBuilder() + .setEnvironment(environment) + val uri = System.getProperty("spark.executor.uri") + if (uri == null) { + command.setValue(new File(sparkHome, "spark-executor").getCanonicalPath) + } else { + // Grab everything to the first '.'. We'll use that and '*' to + // glob the directory "correctly". + val basename = uri.split('/').last.split('.').head + command.setValue("cd %s*; ./spark-executor".format(basename)) + command.addUris(CommandInfo.URI.newBuilder().setValue(uri)) + } val memory = Resource.newBuilder() .setName("mem") .setType(Value.Type.SCALAR) .setScalar(Value.Scalar.newBuilder().setValue(executorMemory).build()) .build() - val command = CommandInfo.newBuilder() - .setValue(execScript) - .setEnvironment(environment) - .build() ExecutorInfo.newBuilder() .setExecutorId(ExecutorID.newBuilder().setValue(execId).build()) .setCommand(command) diff --git a/core/src/main/scala/spark/JavaSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala index b04a27d073..4de81617b1 100644 --- a/core/src/main/scala/spark/JavaSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala @@ -1,10 +1,26 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.serializer import java.io._ import java.nio.ByteBuffer -import serializer.{Serializer, SerializerInstance, DeserializationStream, SerializationStream} -import spark.util.ByteBufferInputStream +import org.apache.spark.util.ByteBufferInputStream private[spark] class JavaSerializationStream(out: OutputStream) extends SerializationStream { val objOut = new ObjectOutputStream(out) diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala new file mode 100644 index 0000000000..24ef204aa1 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala @@ -0,0 +1,159 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.serializer + +import java.nio.ByteBuffer +import java.io.{EOFException, InputStream, OutputStream} + +import com.esotericsoftware.kryo.serializers.{JavaSerializer => KryoJavaSerializer} +import com.esotericsoftware.kryo.{KryoException, Kryo} +import com.esotericsoftware.kryo.io.{Input => KryoInput, Output => KryoOutput} +import com.twitter.chill.ScalaKryoInstantiator + +import org.apache.spark.{SerializableWritable, Logging} +import org.apache.spark.storage.{GetBlock, GotBlock, PutBlock, StorageLevel} + +import org.apache.spark.broadcast.HttpBroadcast + +/** + * A Spark serializer that uses the [[http://code.google.com/p/kryo/wiki/V1Documentation Kryo 1.x library]]. + */ +class KryoSerializer extends org.apache.spark.serializer.Serializer with Logging { + private val bufferSize = System.getProperty("spark.kryoserializer.buffer.mb", "2").toInt * 1024 * 1024 + + def newKryoOutput() = new KryoOutput(bufferSize) + + def newKryoInput() = new KryoInput(bufferSize) + + def newKryo(): Kryo = { + val instantiator = new ScalaKryoInstantiator + val kryo = instantiator.newKryo() + val classLoader = Thread.currentThread.getContextClassLoader + + // Register some commonly used classes + val toRegister: Seq[AnyRef] = Seq( + ByteBuffer.allocate(1), + StorageLevel.MEMORY_ONLY, + PutBlock("1", ByteBuffer.allocate(1), StorageLevel.MEMORY_ONLY), + GotBlock("1", ByteBuffer.allocate(1)), + GetBlock("1") + ) + + for (obj <- toRegister) kryo.register(obj.getClass) + + // Allow sending SerializableWritable + kryo.register(classOf[SerializableWritable[_]], new KryoJavaSerializer()) + kryo.register(classOf[HttpBroadcast[_]], new KryoJavaSerializer()) + + // Allow the user to register their own classes by setting spark.kryo.registrator + try { + Option(System.getProperty("spark.kryo.registrator")).foreach { regCls => + logDebug("Running user registrator: " + regCls) + val reg = Class.forName(regCls, true, classLoader).newInstance().asInstanceOf[KryoRegistrator] + reg.registerClasses(kryo) + } + } catch { + case _: Exception => println("Failed to register spark.kryo.registrator") + } + + kryo.setClassLoader(classLoader) + + // Allow disabling Kryo reference tracking if user knows their object graphs don't have loops + kryo.setReferences(System.getProperty("spark.kryo.referenceTracking", "true").toBoolean) + + kryo + } + + def newInstance(): SerializerInstance = { + new KryoSerializerInstance(this) + } +} + +private[spark] +class KryoSerializationStream(kryo: Kryo, outStream: OutputStream) extends SerializationStream { + val output = new KryoOutput(outStream) + + def writeObject[T](t: T): SerializationStream = { + kryo.writeClassAndObject(output, t) + this + } + + def flush() { output.flush() } + def close() { output.close() } +} + +private[spark] +class KryoDeserializationStream(kryo: Kryo, inStream: InputStream) extends DeserializationStream { + val input = new KryoInput(inStream) + + def readObject[T](): T = { + try { + kryo.readClassAndObject(input).asInstanceOf[T] + } catch { + // DeserializationStream uses the EOF exception to indicate stopping condition. + case _: KryoException => throw new EOFException + } + } + + def close() { + // Kryo's Input automatically closes the input stream it is using. + input.close() + } +} + +private[spark] class KryoSerializerInstance(ks: KryoSerializer) extends SerializerInstance { + val kryo = ks.newKryo() + val output = ks.newKryoOutput() + val input = ks.newKryoInput() + + def serialize[T](t: T): ByteBuffer = { + output.clear() + kryo.writeClassAndObject(output, t) + ByteBuffer.wrap(output.toBytes) + } + + def deserialize[T](bytes: ByteBuffer): T = { + input.setBuffer(bytes.array) + kryo.readClassAndObject(input).asInstanceOf[T] + } + + def deserialize[T](bytes: ByteBuffer, loader: ClassLoader): T = { + val oldClassLoader = kryo.getClassLoader + kryo.setClassLoader(loader) + input.setBuffer(bytes.array) + val obj = kryo.readClassAndObject(input).asInstanceOf[T] + kryo.setClassLoader(oldClassLoader) + obj + } + + def serializeStream(s: OutputStream): SerializationStream = { + new KryoSerializationStream(kryo, s) + } + + def deserializeStream(s: InputStream): DeserializationStream = { + new KryoDeserializationStream(kryo, s) + } +} + +/** + * Interface implemented by clients to register their classes with Kryo when using Kryo + * serialization. + */ +trait KryoRegistrator { + def registerClasses(kryo: Kryo) +} diff --git a/core/src/main/scala/spark/serializer/Serializer.scala b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala index 2ad73b711d..160cca4d6c 100644 --- a/core/src/main/scala/spark/serializer/Serializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala @@ -1,16 +1,33 @@ -package spark.serializer +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.serializer import java.io.{EOFException, InputStream, OutputStream} import java.nio.ByteBuffer import it.unimi.dsi.fastutil.io.FastByteArrayOutputStream -import spark.util.ByteBufferInputStream +import org.apache.spark.util.{NextIterator, ByteBufferInputStream} /** * A serializer. Because some serialization libraries are not thread safe, this class is used to - * create [[spark.serializer.SerializerInstance]] objects that do the actual serialization and are + * create [[org.apache.spark.serializer.SerializerInstance]] objects that do the actual serialization and are * guaranteed to only be called from one thread at a time. */ trait Serializer { @@ -78,7 +95,7 @@ trait DeserializationStream { * Read the elements of this stream through an iterator. This can only be called once, as * reading each element will consume data from the input source. */ - def asIterator: Iterator[Any] = new spark.util.NextIterator[Any] { + def asIterator: Iterator[Any] = new NextIterator[Any] { override protected def getNext() = { try { readObject[Any]() diff --git a/core/src/main/scala/spark/serializer/SerializerManager.scala b/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala index 60b2aac797..2955986fec 100644 --- a/core/src/main/scala/spark/serializer/SerializerManager.scala +++ b/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala @@ -1,4 +1,21 @@ -package spark.serializer +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.serializer import java.util.concurrent.ConcurrentHashMap diff --git a/core/src/main/scala/org/apache/spark/storage/BlockException.scala b/core/src/main/scala/org/apache/spark/storage/BlockException.scala new file mode 100644 index 0000000000..290dbce4f5 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/BlockException.scala @@ -0,0 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +private[spark] +case class BlockException(blockId: String, message: String) extends Exception(message) + diff --git a/core/src/main/scala/org/apache/spark/storage/BlockFetchTracker.scala b/core/src/main/scala/org/apache/spark/storage/BlockFetchTracker.scala new file mode 100644 index 0000000000..2e0b0e6eda --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/BlockFetchTracker.scala @@ -0,0 +1,27 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +private[spark] trait BlockFetchTracker { + def totalBlocks : Int + def numLocalBlocks: Int + def numRemoteBlocks: Int + def remoteFetchTime : Long + def fetchWaitTime: Long + def remoteBytesRead : Long +} diff --git a/core/src/main/scala/spark/storage/BlockFetcherIterator.scala b/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala index bec876213e..3aeda3879d 100644 --- a/core/src/main/scala/spark/storage/BlockFetcherIterator.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer import java.util.concurrent.LinkedBlockingQueue @@ -9,13 +26,13 @@ import scala.collection.mutable.Queue import io.netty.buffer.ByteBuf -import spark.Logging -import spark.Utils -import spark.SparkException -import spark.network.BufferMessage -import spark.network.ConnectionManagerId -import spark.network.netty.ShuffleCopier -import spark.serializer.Serializer +import org.apache.spark.Logging +import org.apache.spark.SparkException +import org.apache.spark.network.BufferMessage +import org.apache.spark.network.ConnectionManagerId +import org.apache.spark.network.netty.ShuffleCopier +import org.apache.spark.serializer.Serializer +import org.apache.spark.util.Utils /** @@ -94,7 +111,7 @@ object BlockFetcherIterator { protected def sendRequest(req: FetchRequest) { logDebug("Sending request for %d blocks (%s) from %s".format( - req.blocks.size, Utils.memoryBytesToString(req.size), req.address.hostPort)) + req.blocks.size, Utils.bytesToString(req.size), req.address.hostPort)) val cmId = new ConnectionManagerId(req.address.host, req.address.port) val blockMessageArray = new BlockMessageArray(req.blocks.map { case (blockId, size) => BlockMessage.fromGetBlock(GetBlock(blockId)) @@ -115,9 +132,10 @@ object BlockFetcherIterator { "Unexpected message " + blockMessage.getType + " received from " + cmId) } val blockId = blockMessage.getId + val networkSize = blockMessage.getData.limit() results.put(new FetchResult(blockId, sizeMap(blockId), () => dataDeserialize(blockId, blockMessage.getData, serializer))) - _remoteBytesRead += req.size + _remoteBytesRead += networkSize logDebug("Got remote block " + blockId + " after " + Utils.getUsedTimeMs(startTime)) } } @@ -292,7 +310,7 @@ object BlockFetcherIterator { } logDebug("Sending request for %d blocks (%s) from %s".format( - req.blocks.size, Utils.memoryBytesToString(req.size), req.address.host)) + req.blocks.size, Utils.bytesToString(req.size), req.address.host)) val cmId = new ConnectionManagerId(req.address.host, req.address.nettyPort) val cpier = new ShuffleCopier cpier.getBlocks(cmId, req.blocks, putResult) diff --git a/core/src/main/scala/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index 4bb4927b4a..13b98a51a1 100644 --- a/core/src/main/scala/spark/storage/BlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.io.{InputStream, OutputStream} import java.nio.{ByteBuffer, MappedByteBuffer} @@ -10,14 +27,13 @@ import scala.concurrent.{Await, Future} import scala.concurrent.duration.Duration import scala.concurrent.duration._ -import com.ning.compress.lzf.{LZFInputStream, LZFOutputStream} - import it.unimi.dsi.fastutil.io.FastByteArrayOutputStream -import spark.{Logging, SparkEnv, SparkException, Utils} -import spark.network._ -import spark.serializer.Serializer -import spark.util.{ByteBufferInputStream, IdGenerator, MetadataCleaner, TimeStampedHashMap} +import org.apache.spark.{Logging, SparkEnv, SparkException} +import org.apache.spark.io.CompressionCodec +import org.apache.spark.network._ +import org.apache.spark.serializer.Serializer +import org.apache.spark.util._ import sun.nio.ch.DirectBuffer @@ -141,6 +157,13 @@ private[spark] class BlockManager( val metadataCleaner = new MetadataCleaner("BlockManager", this.dropOldBlocks) initialize() + // The compression codec to use. Note that the "lazy" val is necessary because we want to delay + // the initialization of the compression codec until it is first used. The reason is that a Spark + // program could be using a user-defined codec in a third party jar, which is loaded in + // Executor.updateDependencies. When the BlockManager is initialized, user level jars hasn't been + // loaded yet. + private lazy val compressionCodec: CompressionCodec = CompressionCodec.createCodec() + /** * Construct a BlockManager with a memory limit set based on system properties. */ @@ -902,18 +925,14 @@ private[spark] class BlockManager( * Wrap an output stream for compression if block compression is enabled for its block type */ def wrapForCompression(blockId: String, s: OutputStream): OutputStream = { - if (shouldCompress(blockId)) { - (new LZFOutputStream(s)).setFinishBlockOnFlush(true) - } else { - s - } + if (shouldCompress(blockId)) compressionCodec.compressedOutputStream(s) else s } /** * Wrap an input stream for compression if block compression is enabled for its block type */ def wrapForCompression(blockId: String, s: InputStream): InputStream = { - if (shouldCompress(blockId)) new LZFInputStream(s) else s + if (shouldCompress(blockId)) compressionCodec.compressedInputStream(s) else s } def dataSerialize( @@ -986,42 +1005,42 @@ private[spark] object BlockManager extends Logging { } } - def blockIdsToExecutorLocations(blockIds: Array[String], env: SparkEnv, blockManagerMaster: BlockManagerMaster = null): HashMap[String, List[String]] = { + def blockIdsToBlockManagers( + blockIds: Array[String], + env: SparkEnv, + blockManagerMaster: BlockManagerMaster = null) + : Map[String, Seq[BlockManagerId]] = + { // env == null and blockManagerMaster != null is used in tests assert (env != null || blockManagerMaster != null) - val locationBlockIds: Seq[Seq[BlockManagerId]] = - if (env != null) { - env.blockManager.getLocationBlockIds(blockIds) - } else { - blockManagerMaster.getLocations(blockIds) - } + val blockLocations: Seq[Seq[BlockManagerId]] = if (env != null) { + env.blockManager.getLocationBlockIds(blockIds) + } else { + blockManagerMaster.getLocations(blockIds) + } - // Convert from block master locations to executor locations (we need that for task scheduling) - val executorLocations = new HashMap[String, List[String]]() + val blockManagers = new HashMap[String, Seq[BlockManagerId]] for (i <- 0 until blockIds.length) { - val blockId = blockIds(i) - val blockLocations = locationBlockIds(i) - - val executors = new HashSet[String]() - - if (env != null) { - for (bkLocation <- blockLocations) { - val executorHostPort = env.resolveExecutorIdToHostPort(bkLocation.executorId, bkLocation.host) - executors += executorHostPort - // logInfo("bkLocation = " + bkLocation + ", executorHostPort = " + executorHostPort) - } - } else { - // Typically while testing, etc - revert to simply using host. - for (bkLocation <- blockLocations) { - executors += bkLocation.host - // logInfo("bkLocation = " + bkLocation + ", executorHostPort = " + executorHostPort) - } - } - - executorLocations.put(blockId, executors.toSeq.toList) + blockManagers(blockIds(i)) = blockLocations(i) } + blockManagers.toMap + } - executorLocations + def blockIdsToExecutorIds( + blockIds: Array[String], + env: SparkEnv, + blockManagerMaster: BlockManagerMaster = null) + : Map[String, Seq[String]] = + { + blockIdsToBlockManagers(blockIds, env, blockManagerMaster).mapValues(s => s.map(_.executorId)) } + def blockIdsToHosts( + blockIds: Array[String], + env: SparkEnv, + blockManagerMaster: BlockManagerMaster = null) + : Map[String, Seq[String]] = + { + blockIdsToBlockManagers(blockIds, env, blockManagerMaster).mapValues(s => s.map(_.host)) + } } diff --git a/core/src/main/scala/spark/storage/BlockManagerId.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerId.scala index 1e557d6148..74207f59af 100644 --- a/core/src/main/scala/spark/storage/BlockManagerId.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerId.scala @@ -1,8 +1,25 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.io.{Externalizable, IOException, ObjectInput, ObjectOutput} import java.util.concurrent.ConcurrentHashMap -import spark.Utils +import org.apache.spark.util.Utils /** * This class represent an unique identifier for a BlockManager. @@ -75,13 +92,13 @@ private[spark] class BlockManagerId private ( private[spark] object BlockManagerId { /** - * Returns a [[spark.storage.BlockManagerId]] for the given configuraiton. + * Returns a [[org.apache.spark.storage.BlockManagerId]] for the given configuraiton. * * @param execId ID of the executor. * @param host Host name of the block manager. * @param port Port of the block manager. * @param nettyPort Optional port for the Netty-based shuffle sender. - * @return A new [[spark.storage.BlockManagerId]]. + * @return A new [[org.apache.spark.storage.BlockManagerId]]. */ def apply(execId: String, host: String, port: Int, nettyPort: Int) = getCachedBlockManagerId(new BlockManagerId(execId, host, port, nettyPort)) diff --git a/core/src/main/scala/spark/storage/BlockManagerMaster.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala index 6a9278292e..0c977f05d1 100644 --- a/core/src/main/scala/spark/storage/BlockManagerMaster.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.io._ import java.util.{HashMap => JHashMap} @@ -15,7 +32,8 @@ import scala.concurrent.ExecutionContext.Implicits.global import akka.pattern.ask import scala.concurrent.duration._ -import spark.{Logging, SparkException} +import org.apache.spark.{Logging, SparkException} +import org.apache.spark.storage.BlockManagerMessages._ private[spark] class BlockManagerMaster(var driverActor: ActorRef) extends Logging { diff --git a/core/src/main/scala/spark/storage/BlockManagerMasterActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala index 6b5e38124b..3776951782 100644 --- a/core/src/main/scala/spark/storage/BlockManagerMasterActor.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.util.{HashMap => JHashMap} @@ -11,7 +28,10 @@ import akka.pattern.ask import scala.concurrent.duration._ import scala.concurrent.Future -import spark.{Logging, Utils, SparkException} +import org.apache.spark.{Logging, SparkException} +import org.apache.spark.storage.BlockManagerMessages._ +import org.apache.spark.util.Utils + /** * BlockManagerMasterActor is an actor on the master node to track statuses of @@ -314,7 +334,7 @@ object BlockManagerMasterActor { private val _blocks = new JHashMap[String, BlockStatus] logInfo("Registering block manager %s with %s RAM".format( - blockManagerId.hostPort, Utils.memoryBytesToString(maxMem))) + blockManagerId.hostPort, Utils.bytesToString(maxMem))) def updateLastSeenMs() { _lastSeenMs = System.currentTimeMillis() @@ -340,12 +360,12 @@ object BlockManagerMasterActor { if (storageLevel.useMemory) { _remainingMem -= memSize logInfo("Added %s in memory on %s (size: %s, free: %s)".format( - blockId, blockManagerId.hostPort, Utils.memoryBytesToString(memSize), - Utils.memoryBytesToString(_remainingMem))) + blockId, blockManagerId.hostPort, Utils.bytesToString(memSize), + Utils.bytesToString(_remainingMem))) } if (storageLevel.useDisk) { logInfo("Added %s on disk on %s (size: %s)".format( - blockId, blockManagerId.hostPort, Utils.memoryBytesToString(diskSize))) + blockId, blockManagerId.hostPort, Utils.bytesToString(diskSize))) } } else if (_blocks.containsKey(blockId)) { // If isValid is not true, drop the block. @@ -354,12 +374,12 @@ object BlockManagerMasterActor { if (blockStatus.storageLevel.useMemory) { _remainingMem += blockStatus.memSize logInfo("Removed %s on %s in memory (size: %s, free: %s)".format( - blockId, blockManagerId.hostPort, Utils.memoryBytesToString(memSize), - Utils.memoryBytesToString(_remainingMem))) + blockId, blockManagerId.hostPort, Utils.bytesToString(blockStatus.memSize), + Utils.bytesToString(_remainingMem))) } if (blockStatus.storageLevel.useDisk) { logInfo("Removed %s on %s on disk (size: %s)".format( - blockId, blockManagerId.hostPort, Utils.memoryBytesToString(diskSize))) + blockId, blockManagerId.hostPort, Utils.bytesToString(blockStatus.diskSize))) } } } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala new file mode 100644 index 0000000000..24333a179c --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala @@ -0,0 +1,110 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import java.io.{Externalizable, ObjectInput, ObjectOutput} + +import akka.actor.ActorRef + + +private[storage] object BlockManagerMessages { + ////////////////////////////////////////////////////////////////////////////////// + // Messages from the master to slaves. + ////////////////////////////////////////////////////////////////////////////////// + sealed trait ToBlockManagerSlave + + // Remove a block from the slaves that have it. This can only be used to remove + // blocks that the master knows about. + case class RemoveBlock(blockId: String) extends ToBlockManagerSlave + + // Remove all blocks belonging to a specific RDD. + case class RemoveRdd(rddId: Int) extends ToBlockManagerSlave + + + ////////////////////////////////////////////////////////////////////////////////// + // Messages from slaves to the master. + ////////////////////////////////////////////////////////////////////////////////// + sealed trait ToBlockManagerMaster + + case class RegisterBlockManager( + blockManagerId: BlockManagerId, + maxMemSize: Long, + sender: ActorRef) + extends ToBlockManagerMaster + + case class HeartBeat(blockManagerId: BlockManagerId) extends ToBlockManagerMaster + + class UpdateBlockInfo( + var blockManagerId: BlockManagerId, + var blockId: String, + var storageLevel: StorageLevel, + var memSize: Long, + var diskSize: Long) + extends ToBlockManagerMaster + with Externalizable { + + def this() = this(null, null, null, 0, 0) // For deserialization only + + override def writeExternal(out: ObjectOutput) { + blockManagerId.writeExternal(out) + out.writeUTF(blockId) + storageLevel.writeExternal(out) + out.writeLong(memSize) + out.writeLong(diskSize) + } + + override def readExternal(in: ObjectInput) { + blockManagerId = BlockManagerId(in) + blockId = in.readUTF() + storageLevel = StorageLevel(in) + memSize = in.readLong() + diskSize = in.readLong() + } + } + + object UpdateBlockInfo { + def apply(blockManagerId: BlockManagerId, + blockId: String, + storageLevel: StorageLevel, + memSize: Long, + diskSize: Long): UpdateBlockInfo = { + new UpdateBlockInfo(blockManagerId, blockId, storageLevel, memSize, diskSize) + } + + // For pattern-matching + def unapply(h: UpdateBlockInfo): Option[(BlockManagerId, String, StorageLevel, Long, Long)] = { + Some((h.blockManagerId, h.blockId, h.storageLevel, h.memSize, h.diskSize)) + } + } + + case class GetLocations(blockId: String) extends ToBlockManagerMaster + + case class GetLocationsMultipleBlockIds(blockIds: Array[String]) extends ToBlockManagerMaster + + case class GetPeers(blockManagerId: BlockManagerId, size: Int) extends ToBlockManagerMaster + + case class RemoveExecutor(execId: String) extends ToBlockManagerMaster + + case object StopBlockManagerMaster extends ToBlockManagerMaster + + case object GetMemoryStatus extends ToBlockManagerMaster + + case object ExpireDeadHosts extends ToBlockManagerMaster + + case object GetStorageStatus extends ToBlockManagerMaster +} diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala new file mode 100644 index 0000000000..951503019f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import akka.actor.Actor + +import org.apache.spark.storage.BlockManagerMessages._ + + +/** + * An actor to take commands from the master to execute options. For example, + * this is used to remove blocks from the slave's BlockManager. + */ +class BlockManagerSlaveActor(blockManager: BlockManager) extends Actor { + override def receive = { + + case RemoveBlock(blockId) => + blockManager.removeBlock(blockId) + + case RemoveRdd(rddId) => + val numBlocksRemoved = blockManager.removeRdd(rddId) + sender ! numBlocksRemoved + } +} diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerSource.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerSource.scala new file mode 100644 index 0000000000..3d709cfde4 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerSource.scala @@ -0,0 +1,65 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import com.codahale.metrics.{Gauge,MetricRegistry} + +import org.apache.spark.metrics.source.Source + + +private[spark] class BlockManagerSource(val blockManager: BlockManager) extends Source { + val metricRegistry = new MetricRegistry() + val sourceName = "BlockManager" + + metricRegistry.register(MetricRegistry.name("memory", "maxMem", "MBytes"), new Gauge[Long] { + override def getValue: Long = { + val storageStatusList = blockManager.master.getStorageStatus + val maxMem = storageStatusList.map(_.maxMem).reduce(_ + _) + maxMem / 1024 / 1024 + } + }) + + metricRegistry.register(MetricRegistry.name("memory", "remainingMem", "MBytes"), new Gauge[Long] { + override def getValue: Long = { + val storageStatusList = blockManager.master.getStorageStatus + val remainingMem = storageStatusList.map(_.memRemaining).reduce(_ + _) + remainingMem / 1024 / 1024 + } + }) + + metricRegistry.register(MetricRegistry.name("memory", "memUsed", "MBytes"), new Gauge[Long] { + override def getValue: Long = { + val storageStatusList = blockManager.master.getStorageStatus + val maxMem = storageStatusList.map(_.maxMem).reduce(_ + _) + val remainingMem = storageStatusList.map(_.memRemaining).reduce(_ + _) + (maxMem - remainingMem) / 1024 / 1024 + } + }) + + metricRegistry.register(MetricRegistry.name("disk", "diskSpaceUsed", "MBytes"), new Gauge[Long] { + override def getValue: Long = { + val storageStatusList = blockManager.master.getStorageStatus + val diskSpaceUsed = storageStatusList + .flatMap(_.blocks.values.map(_.diskSize)) + .reduceOption(_ + _) + .getOrElse(0L) + + diskSpaceUsed / 1024 / 1024 + } + }) +} diff --git a/core/src/main/scala/spark/storage/BlockManagerWorker.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala index 3057ade233..678c38203c 100644 --- a/core/src/main/scala/spark/storage/BlockManagerWorker.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala @@ -1,9 +1,27 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer -import spark.{Logging, Utils} -import spark.network._ +import org.apache.spark.{Logging} +import org.apache.spark.network._ +import org.apache.spark.util.Utils /** * A network interface for BlockManager. Each slave should have one diff --git a/core/src/main/scala/spark/storage/BlockMessage.scala b/core/src/main/scala/org/apache/spark/storage/BlockMessage.scala index 30d7500e01..d8fa6a91d1 100644 --- a/core/src/main/scala/spark/storage/BlockMessage.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockMessage.scala @@ -1,12 +1,28 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer import scala.collection.mutable.StringBuilder import scala.collection.mutable.ArrayBuffer -import spark._ -import spark.network._ +import org.apache.spark.network._ private[spark] case class GetBlock(id: String) private[spark] case class GotBlock(id: String, data: ByteBuffer) diff --git a/core/src/main/scala/spark/storage/BlockMessageArray.scala b/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala index ee0c5ff9a2..0aaf846b5b 100644 --- a/core/src/main/scala/spark/storage/BlockMessageArray.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala @@ -1,12 +1,28 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer -import scala.collection.mutable.StringBuilder import scala.collection.mutable.ArrayBuffer -import spark._ -import spark.network._ +import org.apache.spark._ +import org.apache.spark.network._ private[spark] class BlockMessageArray(var blockMessages: Seq[BlockMessage]) extends Seq[BlockMessage] with Logging { @@ -96,7 +112,7 @@ private[spark] object BlockMessageArray { def main(args: Array[String]) { val blockMessages = - (0 until 10).map(i => { + (0 until 10).map { i => if (i % 2 == 0) { val buffer = ByteBuffer.allocate(100) buffer.clear @@ -104,7 +120,7 @@ private[spark] object BlockMessageArray { } else { BlockMessage.fromGetBlock(GetBlock(i.toString)) } - }) + } val blockMessageArray = new BlockMessageArray(blockMessages) println("Block message array created") diff --git a/core/src/main/scala/spark/storage/BlockObjectWriter.scala b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala index 42e2b07d5c..39f103297f 100644 --- a/core/src/main/scala/spark/storage/BlockObjectWriter.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala @@ -1,6 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import java.nio.ByteBuffer +package org.apache.spark.storage /** diff --git a/core/src/main/scala/spark/storage/BlockStore.scala b/core/src/main/scala/org/apache/spark/storage/BlockStore.scala index 8188d3595e..fa834371f4 100644 --- a/core/src/main/scala/spark/storage/BlockStore.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockStore.scala @@ -1,9 +1,26 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer import scala.collection.mutable.ArrayBuffer -import spark.Logging +import org.apache.spark.Logging /** * Abstract class to store blocks diff --git a/core/src/main/scala/spark/storage/DiskStore.scala b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala index da859eebcb..fc25ef0fae 100644 --- a/core/src/main/scala/spark/storage/DiskStore.scala +++ b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.io.{File, FileOutputStream, OutputStream, RandomAccessFile} import java.nio.ByteBuffer @@ -11,12 +28,12 @@ import scala.collection.mutable.ArrayBuffer import it.unimi.dsi.fastutil.io.FastBufferedOutputStream -import spark.Utils -import spark.executor.ExecutorExitCode -import spark.serializer.{Serializer, SerializationStream} -import spark.Logging -import spark.network.netty.ShuffleSender -import spark.network.netty.PathResolver +import org.apache.spark.executor.ExecutorExitCode +import org.apache.spark.serializer.{Serializer, SerializationStream} +import org.apache.spark.Logging +import org.apache.spark.network.netty.ShuffleSender +import org.apache.spark.network.netty.PathResolver +import org.apache.spark.util.Utils /** @@ -49,7 +66,6 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String) override def close() { if (initialized) { objOut.close() - bs.close() channel = null bs = null objOut = null @@ -131,7 +147,7 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String) channel.close() val finishTime = System.currentTimeMillis logDebug("Block %s stored as %s file on disk in %d ms".format( - blockId, Utils.memoryBytesToString(bytes.limit), (finishTime - startTime))) + blockId, Utils.bytesToString(bytes.limit), (finishTime - startTime))) } private def getFileBytes(file: File): ByteBuffer = { @@ -165,7 +181,7 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String) val timeTaken = System.currentTimeMillis - startTime logDebug("Block %s stored as %s file on disk in %d ms".format( - blockId, Utils.memoryBytesToString(length), timeTaken)) + blockId, Utils.bytesToString(length), timeTaken)) if (returnValues) { // Return a byte buffer for the contents of the file diff --git a/core/src/main/scala/spark/storage/MemoryStore.scala b/core/src/main/scala/org/apache/spark/storage/MemoryStore.scala index eba5ee507f..3b3b2342fa 100644 --- a/core/src/main/scala/spark/storage/MemoryStore.scala +++ b/core/src/main/scala/org/apache/spark/storage/MemoryStore.scala @@ -1,10 +1,27 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.util.LinkedHashMap import java.util.concurrent.ArrayBlockingQueue -import spark.{SizeEstimator, Utils} import java.nio.ByteBuffer import collection.mutable.ArrayBuffer +import org.apache.spark.util.{SizeEstimator, Utils} /** * Stores blocks in memory, either as ArrayBuffers of deserialized Java objects or as @@ -21,7 +38,7 @@ private class MemoryStore(blockManager: BlockManager, maxMemory: Long) // blocks from the memory store. private val putLock = new Object() - logInfo("MemoryStore started with capacity %s.".format(Utils.memoryBytesToString(maxMemory))) + logInfo("MemoryStore started with capacity %s.".format(Utils.bytesToString(maxMemory))) def freeMemory: Long = maxMemory - currentMemory @@ -147,10 +164,10 @@ private class MemoryStore(blockManager: BlockManager, maxMemory: Long) currentMemory += size if (deserialized) { logInfo("Block %s stored as values to memory (estimated size %s, free %s)".format( - blockId, Utils.memoryBytesToString(size), Utils.memoryBytesToString(freeMemory))) + blockId, Utils.bytesToString(size), Utils.bytesToString(freeMemory))) } else { logInfo("Block %s stored as bytes to memory (size %s, free %s)".format( - blockId, Utils.memoryBytesToString(size), Utils.memoryBytesToString(freeMemory))) + blockId, Utils.bytesToString(size), Utils.bytesToString(freeMemory))) } true } else { diff --git a/core/src/main/scala/org/apache/spark/storage/PutResult.scala b/core/src/main/scala/org/apache/spark/storage/PutResult.scala new file mode 100644 index 0000000000..2eba2f06b5 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/PutResult.scala @@ -0,0 +1,26 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import java.nio.ByteBuffer + +/** + * Result of adding a block into a BlockStore. Contains its estimated size, and possibly the + * values put if the caller asked for them to be returned (e.g. for chaining replication) + */ +private[spark] case class PutResult(size: Long, data: Either[Iterator[_], ByteBuffer]) diff --git a/core/src/main/scala/spark/storage/ShuffleBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala index 44638e0c2d..9da11efb57 100644 --- a/core/src/main/scala/spark/storage/ShuffleBlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala @@ -1,6 +1,23 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import spark.serializer.Serializer +package org.apache.spark.storage + +import org.apache.spark.serializer.Serializer private[spark] diff --git a/core/src/main/scala/spark/storage/StorageLevel.scala b/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala index cc0c354e7e..755f1a760e 100644 --- a/core/src/main/scala/spark/storage/StorageLevel.scala +++ b/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.io.{Externalizable, IOException, ObjectInput, ObjectOutput} @@ -6,7 +23,7 @@ import java.io.{Externalizable, IOException, ObjectInput, ObjectOutput} * Flags for controlling the storage of an RDD. Each StorageLevel records whether to use memory, * whether to drop the RDD to disk if it falls out of memory, whether to keep the data in memory * in a serialized format, and whether to replicate the RDD partitions on multiple nodes. - * The [[spark.storage.StorageLevel$]] singleton object contains some static constants for + * The [[org.apache.spark.storage.StorageLevel$]] singleton object contains some static constants for * commonly useful storage levels. To create your own storage level object, use the factor method * of the singleton object (`StorageLevel(...)`). */ diff --git a/core/src/main/scala/spark/storage/StorageUtils.scala b/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala index aca16f533a..2bb7715696 100644 --- a/core/src/main/scala/spark/storage/StorageUtils.scala +++ b/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala @@ -1,7 +1,25 @@ -package spark.storage - -import spark.{Utils, SparkContext} +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import org.apache.spark.{SparkContext} import BlockManagerMasterActor.BlockStatus +import org.apache.spark.util.Utils private[spark] case class StorageStatus(blockManagerId: BlockManagerId, maxMem: Long, @@ -25,9 +43,9 @@ case class RDDInfo(id: Int, name: String, storageLevel: StorageLevel, numCachedPartitions: Int, numPartitions: Int, memSize: Long, diskSize: Long) extends Ordered[RDDInfo] { override def toString = { - import Utils.memoryBytesToString + import Utils.bytesToString "RDD \"%s\" (%d) Storage: %s; CachedPartitions: %d; TotalPartitions: %d; MemorySize: %s; DiskSize: %s".format(name, id, - storageLevel.toString, numCachedPartitions, numPartitions, memoryBytesToString(memSize), memoryBytesToString(diskSize)) + storageLevel.toString, numCachedPartitions, numPartitions, bytesToString(memSize), bytesToString(diskSize)) } override def compare(that: RDDInfo) = { diff --git a/core/src/main/scala/spark/storage/ThreadingTest.scala b/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala index 5c406e68cb..f2ae8dd97d 100644 --- a/core/src/main/scala/spark/storage/ThreadingTest.scala +++ b/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala @@ -1,10 +1,27 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import akka.actor._ -import spark.KryoSerializer import java.util.concurrent.ArrayBlockingQueue import util.Random +import org.apache.spark.serializer.KryoSerializer /** * This class tests the BlockManager and MemoryStore for thread safety and diff --git a/core/src/main/scala/spark/ui/JettyUtils.scala b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala index bc6f9c10d5..7211dbc7c6 100644 --- a/core/src/main/scala/spark/ui/JettyUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala @@ -1,19 +1,36 @@ -package spark.ui - -import annotation.tailrec +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui import javax.servlet.http.{HttpServletResponse, HttpServletRequest} +import scala.annotation.tailrec +import scala.util.{Try, Success, Failure} +import scala.xml.Node + import net.liftweb.json.{JValue, pretty, render} import org.eclipse.jetty.server.{Server, Request, Handler} import org.eclipse.jetty.server.handler.{ResourceHandler, HandlerList, ContextHandler, AbstractHandler} import org.eclipse.jetty.util.thread.QueuedThreadPool -import scala.util.{Try, Success, Failure} -import scala.xml.Node +import org.apache.spark.Logging -import spark.Logging /** Utilities for launching a web server using Jetty's HTTP Server class */ private[spark] object JettyUtils extends Logging { @@ -31,7 +48,7 @@ private[spark] object JettyUtils extends Logging { implicit def textResponderToHandler(responder: Responder[String]): Handler = createHandler(responder, "text/plain") - private def createHandler[T <% AnyRef](responder: Responder[T], contentType: String, + def createHandler[T <% AnyRef](responder: Responder[T], contentType: String, extractFn: T => String = (in: Any) => in.toString): Handler = { new AbstractHandler { def handle(target: String, @@ -100,7 +117,6 @@ private[spark] object JettyUtils extends Logging { Try { server.start() } match { case s: Success[_] => - sys.addShutdownHook(server.stop()) // Be kind, un-bind (server, server.getConnectors.head.getLocalPort) case f: Failure[_] => server.stop() diff --git a/core/src/main/scala/org/apache/spark/ui/Page.scala b/core/src/main/scala/org/apache/spark/ui/Page.scala new file mode 100644 index 0000000000..b2a069a375 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/Page.scala @@ -0,0 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui + +private[spark] object Page extends Enumeration { + val Stages, Storage, Environment, Executors = Value +} diff --git a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala new file mode 100644 index 0000000000..48eb096063 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala @@ -0,0 +1,89 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui + +import javax.servlet.http.HttpServletRequest + +import org.eclipse.jetty.server.{Handler, Server} + +import org.apache.spark.{Logging, SparkContext, SparkEnv} +import org.apache.spark.ui.env.EnvironmentUI +import org.apache.spark.ui.exec.ExecutorsUI +import org.apache.spark.ui.storage.BlockManagerUI +import org.apache.spark.ui.jobs.JobProgressUI +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.util.Utils + +/** Top level user interface for Spark */ +private[spark] class SparkUI(sc: SparkContext) extends Logging { + val host = Option(System.getenv("SPARK_PUBLIC_DNS")).getOrElse(Utils.localHostName()) + val port = Option(System.getProperty("spark.ui.port")).getOrElse(SparkUI.DEFAULT_PORT).toInt + var boundPort: Option[Int] = None + var server: Option[Server] = None + + val handlers = Seq[(String, Handler)]( + ("/static", createStaticHandler(SparkUI.STATIC_RESOURCE_DIR)), + ("/", createRedirectHandler("/stages")) + ) + val storage = new BlockManagerUI(sc) + val jobs = new JobProgressUI(sc) + val env = new EnvironmentUI(sc) + val exec = new ExecutorsUI(sc) + + // Add MetricsServlet handlers by default + val metricsServletHandlers = SparkEnv.get.metricsSystem.getServletHandlers + + val allHandlers = storage.getHandlers ++ jobs.getHandlers ++ env.getHandlers ++ + exec.getHandlers ++ metricsServletHandlers ++ handlers + + /** Bind the HTTP server which backs this web interface */ + def bind() { + try { + val (srv, usedPort) = JettyUtils.startJettyServer("0.0.0.0", port, allHandlers) + logInfo("Started Spark Web UI at http://%s:%d".format(host, usedPort)) + server = Some(srv) + boundPort = Some(usedPort) + } catch { + case e: Exception => + logError("Failed to create Spark JettyUtils", e) + System.exit(1) + } + } + + /** Initialize all components of the server */ + def start() { + // NOTE: This is decoupled from bind() because of the following dependency cycle: + // DAGScheduler() requires that the port of this server is known + // This server must register all handlers, including JobProgressUI, before binding + // JobProgressUI registers a listener with SparkContext, which requires sc to initialize + jobs.start() + exec.start() + } + + def stop() { + server.foreach(_.stop()) + } + + private[spark] def appUIAddress = host + ":" + boundPort.getOrElse("-1") + +} + +private[spark] object SparkUI { + val DEFAULT_PORT = "3030" + val STATIC_RESOURCE_DIR = "org/apache/spark/ui/static" +} diff --git a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala new file mode 100644 index 0000000000..5573b3847b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala @@ -0,0 +1,138 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui + +import scala.xml.Node + +import org.apache.spark.SparkContext + +/** Utility functions for generating XML pages with spark content. */ +private[spark] object UIUtils { + import Page._ + + // Yarn has to go through a proxy so the base uri is provided and has to be on all links + private[spark] val uiRoot : String = Option(System.getenv("APPLICATION_WEB_PROXY_BASE")). + getOrElse("") + + def prependBaseUri(resource: String = "") = uiRoot + resource + + /** Returns a spark page with correctly formatted headers */ + def headerSparkPage(content: => Seq[Node], sc: SparkContext, title: String, page: Page.Value) + : Seq[Node] = { + val jobs = page match { + case Stages => <li class="active"><a href={prependBaseUri("/stages")}>Stages</a></li> + case _ => <li><a href={prependBaseUri("/stages")}>Stages</a></li> + } + val storage = page match { + case Storage => <li class="active"><a href={prependBaseUri("/storage")}>Storage</a></li> + case _ => <li><a href={prependBaseUri("/storage")}>Storage</a></li> + } + val environment = page match { + case Environment => + <li class="active"><a href={prependBaseUri("/environment")}>Environment</a></li> + case _ => <li><a href={prependBaseUri("/environment")}>Environment</a></li> + } + val executors = page match { + case Executors => <li class="active"><a href={prependBaseUri("/executors")}>Executors</a></li> + case _ => <li><a href={prependBaseUri("/executors")}>Executors</a></li> + } + + <html> + <head> + <meta http-equiv="Content-type" content="text/html; charset=utf-8" /> + <link rel="stylesheet" href={prependBaseUri("/static/bootstrap.min.css")} type="text/css" /> + <link rel="stylesheet" href={prependBaseUri("/static/webui.css")} type="text/css" /> + <script src={prependBaseUri("/static/sorttable.js")} ></script> + <title>{sc.appName} - {title}</title> + </head> + <body> + <div class="navbar navbar-static-top"> + <div class="navbar-inner"> + <a href={prependBaseUri("/")} class="brand"><img src={prependBaseUri("/static/spark-logo-77x50px-hd.png")} /></a> + <ul class="nav"> + {jobs} + {storage} + {environment} + {executors} + </ul> + <p class="navbar-text pull-right"><strong>{sc.appName}</strong> application UI</p> + </div> + </div> + + <div class="container-fluid"> + <div class="row-fluid"> + <div class="span12"> + <h3 style="vertical-align: bottom; display: inline-block;"> + {title} + </h3> + </div> + </div> + {content} + </div> + </body> + </html> + } + + /** Returns a page with the spark css/js and a simple format. Used for scheduler UI. */ + def basicSparkPage(content: => Seq[Node], title: String): Seq[Node] = { + <html> + <head> + <meta http-equiv="Content-type" content="text/html; charset=utf-8" /> + <link rel="stylesheet" href={prependBaseUri("/static/bootstrap.min.css")} type="text/css" /> + <link rel="stylesheet" href={prependBaseUri("/static/webui.css")} type="text/css" /> + <script src={prependBaseUri("/static/sorttable.js")} ></script> + <title>{title}</title> + </head> + <body> + <div class="container-fluid"> + <div class="row-fluid"> + <div class="span12"> + <h3 style="vertical-align: middle; display: inline-block;"> + <img src={prependBaseUri("/static/spark-logo-77x50px-hd.png")} style="margin-right: 15px;" /> + {title} + </h3> + </div> + </div> + {content} + </div> + </body> + </html> + } + + /** Returns an HTML table constructed by generating a row for each object in a sequence. */ + def listingTable[T]( + headers: Seq[String], + makeRow: T => Seq[Node], + rows: Seq[T], + fixedWidth: Boolean = false): Seq[Node] = { + + val colWidth = 100.toDouble / headers.size + val colWidthAttr = if (fixedWidth) colWidth + "%" else "" + var tableClass = "table table-bordered table-striped table-condensed sortable" + if (fixedWidth) { + tableClass += " table-fixed" + } + + <table class={tableClass}> + <thead>{headers.map(h => <th width={colWidthAttr}>{h}</th>)}</thead> + <tbody> + {rows.map(r => makeRow(r))} + </tbody> + </table> + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala new file mode 100644 index 0000000000..0ecb22d2f9 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala @@ -0,0 +1,105 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui + +import scala.util.Random + +import org.apache.spark.SparkContext +import org.apache.spark.SparkContext._ +import org.apache.spark.scheduler.cluster.SchedulingMode + + +/** + * Continuously generates jobs that expose various features of the WebUI (internal testing tool). + * + * Usage: ./run spark.ui.UIWorkloadGenerator [master] + */ +private[spark] object UIWorkloadGenerator { + val NUM_PARTITIONS = 100 + val INTER_JOB_WAIT_MS = 5000 + + def main(args: Array[String]) { + if (args.length < 2) { + println("usage: ./spark-class spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]") + System.exit(1) + } + val master = args(0) + val schedulingMode = SchedulingMode.withName(args(1)) + val appName = "Spark UI Tester" + + if (schedulingMode == SchedulingMode.FAIR) { + System.setProperty("spark.cluster.schedulingmode", "FAIR") + } + val sc = new SparkContext(master, appName) + + def setProperties(s: String) = { + if(schedulingMode == SchedulingMode.FAIR) { + sc.setLocalProperty("spark.scheduler.cluster.fair.pool", s) + } + sc.setLocalProperty(SparkContext.SPARK_JOB_DESCRIPTION, s) + } + + val baseData = sc.makeRDD(1 to NUM_PARTITIONS * 10, NUM_PARTITIONS) + def nextFloat() = (new Random()).nextFloat() + + val jobs = Seq[(String, () => Long)]( + ("Count", baseData.count), + ("Cache and Count", baseData.map(x => x).cache.count), + ("Single Shuffle", baseData.map(x => (x % 10, x)).reduceByKey(_ + _).count), + ("Entirely failed phase", baseData.map(x => throw new Exception).count), + ("Partially failed phase", { + baseData.map{x => + val probFailure = (4.0 / NUM_PARTITIONS) + if (nextFloat() < probFailure) { + throw new Exception("This is a task failure") + } + 1 + }.count + }), + ("Partially failed phase (longer tasks)", { + baseData.map{x => + val probFailure = (4.0 / NUM_PARTITIONS) + if (nextFloat() < probFailure) { + Thread.sleep(100) + throw new Exception("This is a task failure") + } + 1 + }.count + }), + ("Job with delays", baseData.map(x => Thread.sleep(100)).count) + ) + + while (true) { + for ((desc, job) <- jobs) { + new Thread { + override def run() { + try { + setProperties(desc) + job() + println("Job funished: " + desc) + } catch { + case e: Exception => + println("Job Failed: " + desc) + } + } + }.start + Thread.sleep(INTER_JOB_WAIT_MS) + } + } + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/env/EnvironmentUI.scala b/core/src/main/scala/org/apache/spark/ui/env/EnvironmentUI.scala new file mode 100644 index 0000000000..c5bf2acc9e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/env/EnvironmentUI.scala @@ -0,0 +1,91 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.env + +import javax.servlet.http.HttpServletRequest + +import scala.collection.JavaConversions._ +import scala.util.Properties +import scala.xml.Node + +import org.eclipse.jetty.server.Handler + +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.ui.UIUtils +import org.apache.spark.ui.Page.Environment +import org.apache.spark.SparkContext + + +private[spark] class EnvironmentUI(sc: SparkContext) { + + def getHandlers = Seq[(String, Handler)]( + ("/environment", (request: HttpServletRequest) => envDetails(request)) + ) + + def envDetails(request: HttpServletRequest): Seq[Node] = { + val jvmInformation = Seq( + ("Java Version", "%s (%s)".format(Properties.javaVersion, Properties.javaVendor)), + ("Java Home", Properties.javaHome), + ("Scala Version", Properties.versionString), + ("Scala Home", Properties.scalaHome) + ).sorted + def jvmRow(kv: (String, String)) = <tr><td>{kv._1}</td><td>{kv._2}</td></tr> + def jvmTable = + UIUtils.listingTable(Seq("Name", "Value"), jvmRow, jvmInformation, fixedWidth = true) + + val properties = System.getProperties.iterator.toSeq + val classPathProperty = properties.find { case (k, v) => + k.contains("java.class.path") + }.getOrElse(("", "")) + val sparkProperties = properties.filter(_._1.startsWith("spark")).sorted + val otherProperties = properties.diff(sparkProperties :+ classPathProperty).sorted + + val propertyHeaders = Seq("Name", "Value") + def propertyRow(kv: (String, String)) = <tr><td>{kv._1}</td><td>{kv._2}</td></tr> + val sparkPropertyTable = + UIUtils.listingTable(propertyHeaders, propertyRow, sparkProperties, fixedWidth = true) + val otherPropertyTable = + UIUtils.listingTable(propertyHeaders, propertyRow, otherProperties, fixedWidth = true) + + val classPathEntries = classPathProperty._2 + .split(System.getProperty("path.separator", ":")) + .filterNot(e => e.isEmpty) + .map(e => (e, "System Classpath")) + val addedJars = sc.addedJars.iterator.toSeq.map{case (path, time) => (path, "Added By User")} + val addedFiles = sc.addedFiles.iterator.toSeq.map{case (path, time) => (path, "Added By User")} + val classPath = (addedJars ++ addedFiles ++ classPathEntries).sorted + + val classPathHeaders = Seq("Resource", "Source") + def classPathRow(data: (String, String)) = <tr><td>{data._1}</td><td>{data._2}</td></tr> + val classPathTable = + UIUtils.listingTable(classPathHeaders, classPathRow, classPath, fixedWidth = true) + + val content = + <span> + <h4>Runtime Information</h4> {jvmTable} + <h4>Spark Properties</h4> + {sparkPropertyTable} + <h4>System Properties</h4> + {otherPropertyTable} + <h4>Classpath Entries</h4> + {classPathTable} + </span> + + UIUtils.headerSparkPage(content, sc, "Environment", Environment) + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsUI.scala b/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsUI.scala new file mode 100644 index 0000000000..d1868dcf78 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsUI.scala @@ -0,0 +1,154 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.exec + +import javax.servlet.http.HttpServletRequest + +import scala.collection.mutable.{HashMap, HashSet} +import scala.xml.Node + +import org.eclipse.jetty.server.Handler + +import org.apache.spark.{ExceptionFailure, Logging, SparkContext} +import org.apache.spark.executor.TaskMetrics +import org.apache.spark.scheduler.cluster.TaskInfo +import org.apache.spark.scheduler.{SparkListenerTaskStart, SparkListenerTaskEnd, SparkListener} +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.ui.Page.Executors +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils + + +private[spark] class ExecutorsUI(val sc: SparkContext) { + + private var _listener: Option[ExecutorsListener] = None + def listener = _listener.get + + def start() { + _listener = Some(new ExecutorsListener) + sc.addSparkListener(listener) + } + + def getHandlers = Seq[(String, Handler)]( + ("/executors", (request: HttpServletRequest) => render(request)) + ) + + def render(request: HttpServletRequest): Seq[Node] = { + val storageStatusList = sc.getExecutorStorageStatus + + val maxMem = storageStatusList.map(_.maxMem).fold(0L)(_+_) + val memUsed = storageStatusList.map(_.memUsed()).fold(0L)(_+_) + val diskSpaceUsed = storageStatusList.flatMap(_.blocks.values.map(_.diskSize)).fold(0L)(_+_) + + val execHead = Seq("Executor ID", "Address", "RDD blocks", "Memory used", "Disk used", + "Active tasks", "Failed tasks", "Complete tasks", "Total tasks") + + def execRow(kv: Seq[String]) = { + <tr> + <td>{kv(0)}</td> + <td>{kv(1)}</td> + <td>{kv(2)}</td> + <td sorttable_customkey={kv(3)}> + {Utils.bytesToString(kv(3).toLong)} / {Utils.bytesToString(kv(4).toLong)} + </td> + <td sorttable_customkey={kv(5)}> + {Utils.bytesToString(kv(5).toLong)} + </td> + <td>{kv(6)}</td> + <td>{kv(7)}</td> + <td>{kv(8)}</td> + <td>{kv(9)}</td> + </tr> + } + + val execInfo = for (b <- 0 until storageStatusList.size) yield getExecInfo(b) + val execTable = UIUtils.listingTable(execHead, execRow, execInfo) + + val content = + <div class="row-fluid"> + <div class="span12"> + <ul class="unstyled"> + <li><strong>Memory:</strong> + {Utils.bytesToString(memUsed)} Used + ({Utils.bytesToString(maxMem)} Total) </li> + <li><strong>Disk:</strong> {Utils.bytesToString(diskSpaceUsed)} Used </li> + </ul> + </div> + </div> + <div class = "row"> + <div class="span12"> + {execTable} + </div> + </div>; + + UIUtils.headerSparkPage(content, sc, "Executors (" + execInfo.size + ")", Executors) + } + + def getExecInfo(a: Int): Seq[String] = { + val execId = sc.getExecutorStorageStatus(a).blockManagerId.executorId + val hostPort = sc.getExecutorStorageStatus(a).blockManagerId.hostPort + val rddBlocks = sc.getExecutorStorageStatus(a).blocks.size.toString + val memUsed = sc.getExecutorStorageStatus(a).memUsed().toString + val maxMem = sc.getExecutorStorageStatus(a).maxMem.toString + val diskUsed = sc.getExecutorStorageStatus(a).diskUsed().toString + val activeTasks = listener.executorToTasksActive.get(a.toString).map(l => l.size).getOrElse(0) + val failedTasks = listener.executorToTasksFailed.getOrElse(a.toString, 0) + val completedTasks = listener.executorToTasksComplete.getOrElse(a.toString, 0) + val totalTasks = activeTasks + failedTasks + completedTasks + + Seq( + execId, + hostPort, + rddBlocks, + memUsed, + maxMem, + diskUsed, + activeTasks.toString, + failedTasks.toString, + completedTasks.toString, + totalTasks.toString + ) + } + + private[spark] class ExecutorsListener extends SparkListener with Logging { + val executorToTasksActive = HashMap[String, HashSet[TaskInfo]]() + val executorToTasksComplete = HashMap[String, Int]() + val executorToTasksFailed = HashMap[String, Int]() + + override def onTaskStart(taskStart: SparkListenerTaskStart) { + val eid = taskStart.taskInfo.executorId + val activeTasks = executorToTasksActive.getOrElseUpdate(eid, new HashSet[TaskInfo]()) + activeTasks += taskStart.taskInfo + } + + override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { + val eid = taskEnd.taskInfo.executorId + val activeTasks = executorToTasksActive.getOrElseUpdate(eid, new HashSet[TaskInfo]()) + activeTasks -= taskEnd.taskInfo + val (failureInfo, metrics): (Option[ExceptionFailure], Option[TaskMetrics]) = + taskEnd.reason match { + case e: ExceptionFailure => + executorToTasksFailed(eid) = executorToTasksFailed.getOrElse(eid, 0) + 1 + (Some(e), e.metrics) + case _ => + executorToTasksComplete(eid) = executorToTasksComplete.getOrElse(eid, 0) + 1 + (None, Option(taskEnd.taskMetrics)) + } + } + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala new file mode 100644 index 0000000000..3b428effaf --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala @@ -0,0 +1,90 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import javax.servlet.http.HttpServletRequest + +import scala.xml.{NodeSeq, Node} + +import org.apache.spark.scheduler.cluster.SchedulingMode +import org.apache.spark.ui.Page._ +import org.apache.spark.ui.UIUtils._ + + +/** Page showing list of all ongoing and recently finished stages and pools*/ +private[spark] class IndexPage(parent: JobProgressUI) { + def listener = parent.listener + + def render(request: HttpServletRequest): Seq[Node] = { + listener.synchronized { + val activeStages = listener.activeStages.toSeq + val completedStages = listener.completedStages.reverse.toSeq + val failedStages = listener.failedStages.reverse.toSeq + val now = System.currentTimeMillis() + + var activeTime = 0L + for (tasks <- listener.stageToTasksActive.values; t <- tasks) { + activeTime += t.timeRunning(now) + } + + val activeStagesTable = new StageTable(activeStages.sortBy(_.submissionTime).reverse, parent) + val completedStagesTable = new StageTable(completedStages.sortBy(_.submissionTime).reverse, parent) + val failedStagesTable = new StageTable(failedStages.sortBy(_.submissionTime).reverse, parent) + + val pools = listener.sc.getAllPools + val poolTable = new PoolTable(pools, listener) + val summary: NodeSeq = + <div> + <ul class="unstyled"> + <li> + <strong>Total Duration: </strong> + {parent.formatDuration(now - listener.sc.startTime)} + </li> + <li><strong>Scheduling Mode:</strong> {parent.sc.getSchedulingMode}</li> + <li> + <a href="#active"><strong>Active Stages:</strong></a> + {activeStages.size} + </li> + <li> + <a href="#completed"><strong>Completed Stages:</strong></a> + {completedStages.size} + </li> + <li> + <a href="#failed"><strong>Failed Stages:</strong></a> + {failedStages.size} + </li> + </ul> + </div> + + val content = summary ++ + {if (listener.sc.getSchedulingMode == SchedulingMode.FAIR) { + <h4>{pools.size} Fair Scheduler Pools</h4> ++ poolTable.toNodeSeq + } else { + Seq() + }} ++ + <h4 id="active">Active Stages ({activeStages.size})</h4> ++ + activeStagesTable.toNodeSeq++ + <h4 id="completed">Completed Stages ({completedStages.size})</h4> ++ + completedStagesTable.toNodeSeq++ + <h4 id ="failed">Failed Stages ({failedStages.size})</h4> ++ + failedStagesTable.toNodeSeq + + headerSparkPage(content, parent.sc, "Spark Stages", Stages) + } + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala new file mode 100644 index 0000000000..e2bcd98545 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala @@ -0,0 +1,173 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import scala.Seq +import scala.collection.mutable.{ListBuffer, HashMap, HashSet} + +import org.apache.spark.{ExceptionFailure, SparkContext, Success} +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster.TaskInfo +import org.apache.spark.executor.TaskMetrics +import collection.mutable + +/** + * Tracks task-level information to be displayed in the UI. + * + * All access to the data structures in this class must be synchronized on the + * class, since the UI thread and the DAGScheduler event loop may otherwise + * be reading/updating the internal data structures concurrently. + */ +private[spark] class JobProgressListener(val sc: SparkContext) extends SparkListener { + // How many stages to remember + val RETAINED_STAGES = System.getProperty("spark.ui.retained_stages", "1000").toInt + val DEFAULT_POOL_NAME = "default" + + val stageToPool = new HashMap[Stage, String]() + val stageToDescription = new HashMap[Stage, String]() + val poolToActiveStages = new HashMap[String, HashSet[Stage]]() + + val activeStages = HashSet[Stage]() + val completedStages = ListBuffer[Stage]() + val failedStages = ListBuffer[Stage]() + + // Total metrics reflect metrics only for completed tasks + var totalTime = 0L + var totalShuffleRead = 0L + var totalShuffleWrite = 0L + + val stageToTime = HashMap[Int, Long]() + val stageToShuffleRead = HashMap[Int, Long]() + val stageToShuffleWrite = HashMap[Int, Long]() + val stageToTasksActive = HashMap[Int, HashSet[TaskInfo]]() + val stageToTasksComplete = HashMap[Int, Int]() + val stageToTasksFailed = HashMap[Int, Int]() + val stageToTaskInfos = + HashMap[Int, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]]() + + override def onJobStart(jobStart: SparkListenerJobStart) {} + + override def onStageCompleted(stageCompleted: StageCompleted) = synchronized { + val stage = stageCompleted.stageInfo.stage + poolToActiveStages(stageToPool(stage)) -= stage + activeStages -= stage + completedStages += stage + trimIfNecessary(completedStages) + } + + /** If stages is too large, remove and garbage collect old stages */ + def trimIfNecessary(stages: ListBuffer[Stage]) = synchronized { + if (stages.size > RETAINED_STAGES) { + val toRemove = RETAINED_STAGES / 10 + stages.takeRight(toRemove).foreach( s => { + stageToTaskInfos.remove(s.id) + stageToTime.remove(s.id) + stageToShuffleRead.remove(s.id) + stageToShuffleWrite.remove(s.id) + stageToTasksActive.remove(s.id) + stageToTasksComplete.remove(s.id) + stageToTasksFailed.remove(s.id) + stageToPool.remove(s) + if (stageToDescription.contains(s)) {stageToDescription.remove(s)} + }) + stages.trimEnd(toRemove) + } + } + + /** For FIFO, all stages are contained by "default" pool but "default" pool here is meaningless */ + override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) = synchronized { + val stage = stageSubmitted.stage + activeStages += stage + + val poolName = Option(stageSubmitted.properties).map { + p => p.getProperty("spark.scheduler.cluster.fair.pool", DEFAULT_POOL_NAME) + }.getOrElse(DEFAULT_POOL_NAME) + stageToPool(stage) = poolName + + val description = Option(stageSubmitted.properties).flatMap { + p => Option(p.getProperty(SparkContext.SPARK_JOB_DESCRIPTION)) + } + description.map(d => stageToDescription(stage) = d) + + val stages = poolToActiveStages.getOrElseUpdate(poolName, new HashSet[Stage]()) + stages += stage + } + + override def onTaskStart(taskStart: SparkListenerTaskStart) = synchronized { + val sid = taskStart.task.stageId + val tasksActive = stageToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]()) + tasksActive += taskStart.taskInfo + val taskList = stageToTaskInfos.getOrElse( + sid, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]()) + taskList += ((taskStart.taskInfo, None, None)) + stageToTaskInfos(sid) = taskList + } + + override def onTaskEnd(taskEnd: SparkListenerTaskEnd) = synchronized { + val sid = taskEnd.task.stageId + val tasksActive = stageToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]()) + tasksActive -= taskEnd.taskInfo + val (failureInfo, metrics): (Option[ExceptionFailure], Option[TaskMetrics]) = + taskEnd.reason match { + case e: ExceptionFailure => + stageToTasksFailed(sid) = stageToTasksFailed.getOrElse(sid, 0) + 1 + (Some(e), e.metrics) + case _ => + stageToTasksComplete(sid) = stageToTasksComplete.getOrElse(sid, 0) + 1 + (None, Option(taskEnd.taskMetrics)) + } + + stageToTime.getOrElseUpdate(sid, 0L) + val time = metrics.map(m => m.executorRunTime).getOrElse(0) + stageToTime(sid) += time + totalTime += time + + stageToShuffleRead.getOrElseUpdate(sid, 0L) + val shuffleRead = metrics.flatMap(m => m.shuffleReadMetrics).map(s => + s.remoteBytesRead).getOrElse(0L) + stageToShuffleRead(sid) += shuffleRead + totalShuffleRead += shuffleRead + + stageToShuffleWrite.getOrElseUpdate(sid, 0L) + val shuffleWrite = metrics.flatMap(m => m.shuffleWriteMetrics).map(s => + s.shuffleBytesWritten).getOrElse(0L) + stageToShuffleWrite(sid) += shuffleWrite + totalShuffleWrite += shuffleWrite + + val taskList = stageToTaskInfos.getOrElse( + sid, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]()) + taskList -= ((taskEnd.taskInfo, None, None)) + taskList += ((taskEnd.taskInfo, metrics, failureInfo)) + stageToTaskInfos(sid) = taskList + } + + override def onJobEnd(jobEnd: SparkListenerJobEnd) = synchronized { + jobEnd match { + case end: SparkListenerJobEnd => + end.jobResult match { + case JobFailed(ex, Some(stage)) => + activeStages -= stage + poolToActiveStages(stageToPool(stage)) -= stage + failedStages += stage + trimIfNecessary(failedStages) + case _ => + } + case _ => + } + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressUI.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressUI.scala new file mode 100644 index 0000000000..54e273fd8b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressUI.scala @@ -0,0 +1,60 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import scala.concurrent.duration._ + +import java.text.SimpleDateFormat + +import javax.servlet.http.HttpServletRequest + +import org.eclipse.jetty.server.Handler + +import scala.Seq +import scala.collection.mutable.{HashSet, ListBuffer, HashMap, ArrayBuffer} + +import org.apache.spark.ui.JettyUtils._ +import org.apache.spark.{ExceptionFailure, SparkContext, Success} +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster.SchedulingMode +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode +import org.apache.spark.util.Utils + +/** Web UI showing progress status of all jobs in the given SparkContext. */ +private[spark] class JobProgressUI(val sc: SparkContext) { + private var _listener: Option[JobProgressListener] = None + def listener = _listener.get + val dateFmt = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss") + + private val indexPage = new IndexPage(this) + private val stagePage = new StagePage(this) + private val poolPage = new PoolPage(this) + + def start() { + _listener = Some(new JobProgressListener(sc)) + sc.addSparkListener(listener) + } + + def formatDuration(ms: Long) = Utils.msDurationToString(ms) + + def getHandlers = Seq[(String, Handler)]( + ("/stages/stage", (request: HttpServletRequest) => stagePage.render(request)), + ("/stages/pool", (request: HttpServletRequest) => poolPage.render(request)), + ("/stages", (request: HttpServletRequest) => indexPage.render(request)) + ) +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/PoolPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/PoolPage.scala new file mode 100644 index 0000000000..89fffcb80d --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/PoolPage.scala @@ -0,0 +1,49 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import javax.servlet.http.HttpServletRequest + +import scala.xml.{NodeSeq, Node} +import scala.collection.mutable.HashSet + +import org.apache.spark.scheduler.Stage +import org.apache.spark.ui.UIUtils._ +import org.apache.spark.ui.Page._ + +/** Page showing specific pool details */ +private[spark] class PoolPage(parent: JobProgressUI) { + def listener = parent.listener + + def render(request: HttpServletRequest): Seq[Node] = { + listener.synchronized { + val poolName = request.getParameter("poolname") + val poolToActiveStages = listener.poolToActiveStages + val activeStages = poolToActiveStages.get(poolName).toSeq.flatten + val activeStagesTable = new StageTable(activeStages.sortBy(_.submissionTime).reverse, parent) + + val pool = listener.sc.getPoolForName(poolName).get + val poolTable = new PoolTable(Seq(pool), listener) + + val content = <h4>Summary </h4> ++ poolTable.toNodeSeq() ++ + <h4>{activeStages.size} Active Stages</h4> ++ activeStagesTable.toNodeSeq() + + headerSparkPage(content, parent.sc, "Fair Scheduler Pool: " + poolName, Stages) + } + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala b/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala new file mode 100644 index 0000000000..b3d3666944 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala @@ -0,0 +1,73 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import scala.collection.mutable.HashMap +import scala.collection.mutable.HashSet +import scala.xml.Node + +import org.apache.spark.scheduler.Stage +import org.apache.spark.scheduler.cluster.Schedulable +import org.apache.spark.ui.UIUtils + +/** Table showing list of pools */ +private[spark] class PoolTable(pools: Seq[Schedulable], listener: JobProgressListener) { + + var poolToActiveStages: HashMap[String, HashSet[Stage]] = listener.poolToActiveStages + + def toNodeSeq(): Seq[Node] = { + listener.synchronized { + poolTable(poolRow, pools) + } + } + + private def poolTable(makeRow: (Schedulable, HashMap[String, HashSet[Stage]]) => Seq[Node], + rows: Seq[Schedulable] + ): Seq[Node] = { + <table class="table table-bordered table-striped table-condensed sortable table-fixed"> + <thead> + <th>Pool Name</th> + <th>Minimum Share</th> + <th>Pool Weight</th> + <th>Active Stages</th> + <th>Running Tasks</th> + <th>SchedulingMode</th> + </thead> + <tbody> + {rows.map(r => makeRow(r, poolToActiveStages))} + </tbody> + </table> + } + + private def poolRow(p: Schedulable, poolToActiveStages: HashMap[String, HashSet[Stage]]) + : Seq[Node] = { + val activeStages = poolToActiveStages.get(p.name) match { + case Some(stages) => stages.size + case None => 0 + } + <tr> + <td><a href={"%s/stages/pool?poolname=%s".format(UIUtils.prependBaseUri(),p.name)}>{p.name}</a></td> + <td>{p.minShare}</td> + <td>{p.weight}</td> + <td>{activeStages}</td> + <td>{p.runningTasks}</td> + <td>{p.schedulingMode}</td> + </tr> + } +} + diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala new file mode 100644 index 0000000000..a9969ab1c0 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala @@ -0,0 +1,183 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import java.util.Date + +import javax.servlet.http.HttpServletRequest + +import scala.xml.Node + +import org.apache.spark.ui.UIUtils._ +import org.apache.spark.ui.Page._ +import org.apache.spark.util.{Utils, Distribution} +import org.apache.spark.{ExceptionFailure} +import org.apache.spark.scheduler.cluster.TaskInfo +import org.apache.spark.executor.TaskMetrics + +/** Page showing statistics and task list for a given stage */ +private[spark] class StagePage(parent: JobProgressUI) { + def listener = parent.listener + val dateFmt = parent.dateFmt + + def render(request: HttpServletRequest): Seq[Node] = { + listener.synchronized { + val stageId = request.getParameter("id").toInt + val now = System.currentTimeMillis() + + if (!listener.stageToTaskInfos.contains(stageId)) { + val content = + <div> + <h4>Summary Metrics</h4> No tasks have started yet + <h4>Tasks</h4> No tasks have started yet + </div> + return headerSparkPage(content, parent.sc, "Details for Stage %s".format(stageId), Stages) + } + + val tasks = listener.stageToTaskInfos(stageId).toSeq.sortBy(_._1.launchTime) + + val numCompleted = tasks.count(_._1.finished) + val shuffleReadBytes = listener.stageToShuffleRead.getOrElse(stageId, 0L) + val hasShuffleRead = shuffleReadBytes > 0 + val shuffleWriteBytes = listener.stageToShuffleWrite.getOrElse(stageId, 0L) + val hasShuffleWrite = shuffleWriteBytes > 0 + + var activeTime = 0L + listener.stageToTasksActive(stageId).foreach(activeTime += _.timeRunning(now)) + + val summary = + <div> + <ul class="unstyled"> + <li> + <strong>CPU time: </strong> + {parent.formatDuration(listener.stageToTime.getOrElse(stageId, 0L) + activeTime)} + </li> + {if (hasShuffleRead) + <li> + <strong>Shuffle read: </strong> + {Utils.bytesToString(shuffleReadBytes)} + </li> + } + {if (hasShuffleWrite) + <li> + <strong>Shuffle write: </strong> + {Utils.bytesToString(shuffleWriteBytes)} + </li> + } + </ul> + </div> + + val taskHeaders: Seq[String] = + Seq("Task ID", "Status", "Locality Level", "Executor", "Launch Time", "Duration") ++ + Seq("GC Time") ++ + {if (hasShuffleRead) Seq("Shuffle Read") else Nil} ++ + {if (hasShuffleWrite) Seq("Shuffle Write") else Nil} ++ + Seq("Errors") + + val taskTable = listingTable(taskHeaders, taskRow(hasShuffleRead, hasShuffleWrite), tasks) + + // Excludes tasks which failed and have incomplete metrics + val validTasks = tasks.filter(t => t._1.status == "SUCCESS" && (t._2.isDefined)) + + val summaryTable: Option[Seq[Node]] = + if (validTasks.size == 0) { + None + } + else { + val serviceTimes = validTasks.map{case (info, metrics, exception) => + metrics.get.executorRunTime.toDouble} + val serviceQuantiles = "Duration" +: Distribution(serviceTimes).get.getQuantiles().map( + ms => parent.formatDuration(ms.toLong)) + + def getQuantileCols(data: Seq[Double]) = + Distribution(data).get.getQuantiles().map(d => Utils.bytesToString(d.toLong)) + + val shuffleReadSizes = validTasks.map { + case(info, metrics, exception) => + metrics.get.shuffleReadMetrics.map(_.remoteBytesRead).getOrElse(0L).toDouble + } + val shuffleReadQuantiles = "Shuffle Read (Remote)" +: getQuantileCols(shuffleReadSizes) + + val shuffleWriteSizes = validTasks.map { + case(info, metrics, exception) => + metrics.get.shuffleWriteMetrics.map(_.shuffleBytesWritten).getOrElse(0L).toDouble + } + val shuffleWriteQuantiles = "Shuffle Write" +: getQuantileCols(shuffleWriteSizes) + + val listings: Seq[Seq[String]] = Seq(serviceQuantiles, + if (hasShuffleRead) shuffleReadQuantiles else Nil, + if (hasShuffleWrite) shuffleWriteQuantiles else Nil) + + val quantileHeaders = Seq("Metric", "Min", "25th percentile", + "Median", "75th percentile", "Max") + def quantileRow(data: Seq[String]): Seq[Node] = <tr> {data.map(d => <td>{d}</td>)} </tr> + Some(listingTable(quantileHeaders, quantileRow, listings, fixedWidth = true)) + } + + val content = + summary ++ + <h4>Summary Metrics for {numCompleted} Completed Tasks</h4> ++ + <div>{summaryTable.getOrElse("No tasks have reported metrics yet.")}</div> ++ + <h4>Tasks</h4> ++ taskTable; + + headerSparkPage(content, parent.sc, "Details for Stage %d".format(stageId), Stages) + } + } + + + def taskRow(shuffleRead: Boolean, shuffleWrite: Boolean) + (taskData: (TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])): Seq[Node] = { + def fmtStackTrace(trace: Seq[StackTraceElement]): Seq[Node] = + trace.map(e => <span style="display:block;">{e.toString}</span>) + val (info, metrics, exception) = taskData + + val duration = if (info.status == "RUNNING") info.timeRunning(System.currentTimeMillis()) + else metrics.map(m => m.executorRunTime).getOrElse(1) + val formatDuration = if (info.status == "RUNNING") parent.formatDuration(duration) + else metrics.map(m => parent.formatDuration(m.executorRunTime)).getOrElse("") + val gcTime = metrics.map(m => m.jvmGCTime).getOrElse(0L) + + <tr> + <td>{info.taskId}</td> + <td>{info.status}</td> + <td>{info.taskLocality}</td> + <td>{info.host}</td> + <td>{dateFmt.format(new Date(info.launchTime))}</td> + <td sorttable_customkey={duration.toString}> + {formatDuration} + </td> + <td sorttable_customkey={gcTime.toString}> + {if (gcTime > 0) parent.formatDuration(gcTime) else ""} + </td> + {if (shuffleRead) { + <td>{metrics.flatMap{m => m.shuffleReadMetrics}.map{s => + Utils.bytesToString(s.remoteBytesRead)}.getOrElse("")}</td> + }} + {if (shuffleWrite) { + <td>{metrics.flatMap{m => m.shuffleWriteMetrics}.map{s => + Utils.bytesToString(s.shuffleBytesWritten)}.getOrElse("")}</td> + }} + <td>{exception.map(e => + <span> + {e.className} ({e.description})<br/> + {fmtStackTrace(e.stackTrace)} + </span>).getOrElse("")} + </td> + </tr> + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala b/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala new file mode 100644 index 0000000000..32776eaa25 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala @@ -0,0 +1,127 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.jobs + +import java.util.Date + +import scala.xml.Node +import scala.collection.mutable.HashSet + +import org.apache.spark.scheduler.cluster.{SchedulingMode, TaskInfo} +import org.apache.spark.scheduler.Stage +import org.apache.spark.ui.UIUtils +import org.apache.spark.util.Utils + + +/** Page showing list of all ongoing and recently finished stages */ +private[spark] class StageTable(val stages: Seq[Stage], val parent: JobProgressUI) { + + val listener = parent.listener + val dateFmt = parent.dateFmt + val isFairScheduler = listener.sc.getSchedulingMode == SchedulingMode.FAIR + + def toNodeSeq(): Seq[Node] = { + listener.synchronized { + stageTable(stageRow, stages) + } + } + + /** Special table which merges two header cells. */ + private def stageTable[T](makeRow: T => Seq[Node], rows: Seq[T]): Seq[Node] = { + <table class="table table-bordered table-striped table-condensed sortable"> + <thead> + <th>Stage Id</th> + {if (isFairScheduler) {<th>Pool Name</th>} else {}} + <th>Description</th> + <th>Submitted</th> + <th>Duration</th> + <th>Tasks: Succeeded/Total</th> + <th>Shuffle Read</th> + <th>Shuffle Write</th> + </thead> + <tbody> + {rows.map(r => makeRow(r))} + </tbody> + </table> + } + + private def makeProgressBar(started: Int, completed: Int, failed: String, total: Int): Seq[Node] = { + val completeWidth = "width: %s%%".format((completed.toDouble/total)*100) + val startWidth = "width: %s%%".format((started.toDouble/total)*100) + + <div class="progress"> + <span style="text-align:center; position:absolute; width:100%;"> + {completed}/{total} {failed} + </span> + <div class="bar bar-completed" style={completeWidth}></div> + <div class="bar bar-running" style={startWidth}></div> + </div> + } + + + private def stageRow(s: Stage): Seq[Node] = { + val submissionTime = s.submissionTime match { + case Some(t) => dateFmt.format(new Date(t)) + case None => "Unknown" + } + + val shuffleRead = listener.stageToShuffleRead.getOrElse(s.id, 0L) match { + case 0 => "" + case b => Utils.bytesToString(b) + } + val shuffleWrite = listener.stageToShuffleWrite.getOrElse(s.id, 0L) match { + case 0 => "" + case b => Utils.bytesToString(b) + } + + val startedTasks = listener.stageToTasksActive.getOrElse(s.id, HashSet[TaskInfo]()).size + val completedTasks = listener.stageToTasksComplete.getOrElse(s.id, 0) + val failedTasks = listener.stageToTasksFailed.getOrElse(s.id, 0) match { + case f if f > 0 => "(%s failed)".format(f) + case _ => "" + } + val totalTasks = s.numPartitions + + val poolName = listener.stageToPool.get(s) + + val nameLink = + <a href={"%s/stages/stage?id=%s".format(UIUtils.prependBaseUri(),s.id)}>{s.name}</a> + val description = listener.stageToDescription.get(s) + .map(d => <div><em>{d}</em></div><div>{nameLink}</div>).getOrElse(nameLink) + val finishTime = s.completionTime.getOrElse(System.currentTimeMillis()) + val duration = s.submissionTime.map(t => finishTime - t) + + <tr> + <td>{s.id}</td> + {if (isFairScheduler) { + <td><a href={"%s/stages/pool?poolname=%s".format(UIUtils.prependBaseUri(),poolName.get)}> + {poolName.get}</a></td>} + } + <td>{description}</td> + <td valign="middle">{submissionTime}</td> + <td sorttable_customkey={duration.getOrElse(-1).toString}> + {duration.map(d => parent.formatDuration(d)).getOrElse("Unknown")} + </td> + <td class="progress-cell"> + {makeProgressBar(startedTasks, completedTasks, failedTasks, totalTasks)} + </td> + <td>{shuffleRead}</td> + <td>{shuffleWrite}</td> + </tr> + } +} diff --git a/core/src/main/scala/org/apache/spark/ui/storage/BlockManagerUI.scala b/core/src/main/scala/org/apache/spark/ui/storage/BlockManagerUI.scala new file mode 100644 index 0000000000..a5446b3fc3 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/storage/BlockManagerUI.scala @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.storage + +import scala.concurrent.duration._ + +import javax.servlet.http.HttpServletRequest + +import org.eclipse.jetty.server.Handler + +import org.apache.spark.{Logging, SparkContext} +import org.apache.spark.ui.JettyUtils._ + +/** Web UI showing storage status of all RDD's in the given SparkContext. */ +private[spark] class BlockManagerUI(val sc: SparkContext) extends Logging { + implicit val timeout = Duration.create( + System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds") + + val indexPage = new IndexPage(this) + val rddPage = new RDDPage(this) + + def getHandlers = Seq[(String, Handler)]( + ("/storage/rdd", (request: HttpServletRequest) => rddPage.render(request)), + ("/storage", (request: HttpServletRequest) => indexPage.render(request)) + ) +} diff --git a/core/src/main/scala/org/apache/spark/ui/storage/IndexPage.scala b/core/src/main/scala/org/apache/spark/ui/storage/IndexPage.scala new file mode 100644 index 0000000000..109a7d4094 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ui/storage/IndexPage.scala @@ -0,0 +1,65 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.storage + +import javax.servlet.http.HttpServletRequest + +import scala.xml.Node + +import org.apache.spark.storage.{RDDInfo, StorageUtils} +import org.apache.spark.ui.UIUtils._ +import org.apache.spark.ui.Page._ +import org.apache.spark.util.Utils + +/** Page showing list of RDD's currently stored in the cluster */ +private[spark] class IndexPage(parent: BlockManagerUI) { + val sc = parent.sc + + def render(request: HttpServletRequest): Seq[Node] = { + val storageStatusList = sc.getExecutorStorageStatus + // Calculate macro-level statistics + + val rddHeaders = Seq( + "RDD Name", + "Storage Level", + "Cached Partitions", + "Fraction Cached", + "Size in Memory", + "Size on Disk") + val rdds = StorageUtils.rddInfoFromStorageStatus(storageStatusList, sc) + val content = listingTable(rddHeaders, rddRow, rdds) + + headerSparkPage(content, parent.sc, "Storage ", Storage) + } + + def rddRow(rdd: RDDInfo): Seq[Node] = { + <tr> + <td> + <a href={"%s/storage/rdd?id=%s".format(prependBaseUri(),rdd.id)}> + {rdd.name} + </a> + </td> + <td>{rdd.storageLevel.description} + </td> + <td>{rdd.numCachedPartitions}</td> + <td>{"%.0f%%".format(rdd.numCachedPartitions * 100.0 / rdd.numPartitions)}</td> + <td>{Utils.bytesToString(rdd.memSize)}</td> + <td>{Utils.bytesToString(rdd.diskSize)}</td> + </tr> + } +} diff --git a/core/src/main/scala/spark/ui/storage/RDDPage.scala b/core/src/main/scala/org/apache/spark/ui/storage/RDDPage.scala index 428db6fa95..43c1257677 100644 --- a/core/src/main/scala/spark/ui/storage/RDDPage.scala +++ b/core/src/main/scala/org/apache/spark/ui/storage/RDDPage.scala @@ -1,14 +1,32 @@ -package spark.ui.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui.storage import javax.servlet.http.HttpServletRequest import scala.xml.Node -import spark.storage.{StorageStatus, StorageUtils} -import spark.ui.UIUtils._ -import spark.Utils -import spark.storage.BlockManagerMasterActor.BlockStatus -import spark.ui.Page._ +import org.apache.spark.storage.{StorageStatus, StorageUtils} +import org.apache.spark.storage.BlockManagerMasterActor.BlockStatus +import org.apache.spark.ui.UIUtils._ +import org.apache.spark.ui.Page._ +import org.apache.spark.util.Utils + /** Page showing storage details for a given RDD */ private[spark] class RDDPage(parent: BlockManagerUI) { @@ -27,7 +45,7 @@ private[spark] class RDDPage(parent: BlockManagerUI) { val workerTable = listingTable(workerHeaders, workerRow, workers) val blockHeaders = Seq("Block Name", "Storage Level", "Size in Memory", "Size on Disk", - "Locations") + "Executors") val blockStatuses = filteredStorageStatusList.flatMap(_.blocks).toArray.sortWith(_._1 < _._1) val blockLocations = StorageUtils.blockLocationsFromStorageStatus(filteredStorageStatusList) @@ -37,7 +55,7 @@ private[spark] class RDDPage(parent: BlockManagerUI) { val blockTable = listingTable(blockHeaders, blockRow, blocks) val content = - <div class="row"> + <div class="row-fluid"> <div class="span12"> <ul class="unstyled"> <li> @@ -54,30 +72,31 @@ private[spark] class RDDPage(parent: BlockManagerUI) { </li> <li> <strong>Memory Size:</strong> - {Utils.memoryBytesToString(rddInfo.memSize)} + {Utils.bytesToString(rddInfo.memSize)} </li> <li> <strong>Disk Size:</strong> - {Utils.memoryBytesToString(rddInfo.diskSize)} + {Utils.bytesToString(rddInfo.diskSize)} </li> </ul> </div> </div> - <hr/> - <div class="row"> + + <div class="row-fluid"> <div class="span12"> + <h4> Data Distribution on {workers.size} Executors </h4> {workerTable} </div> </div> - <hr/> - <div class="row"> + + <div class="row-fluid"> <div class="span12"> - <h3> RDD Summary </h3> + <h4> {blocks.size} Partitions </h4> {blockTable} </div> </div>; - headerSparkPage(content, parent.sc, "RDD Info: " + rddInfo.name, Jobs) + headerSparkPage(content, parent.sc, "RDD Storage Info for " + rddInfo.name, Storage) } def blockRow(row: (String, BlockStatus, Seq[String])): Seq[Node] = { @@ -88,10 +107,10 @@ private[spark] class RDDPage(parent: BlockManagerUI) { {block.storageLevel.description} </td> <td sorttable_customkey={block.memSize.toString}> - {Utils.memoryBytesToString(block.memSize)} + {Utils.bytesToString(block.memSize)} </td> <td sorttable_customkey={block.diskSize.toString}> - {Utils.memoryBytesToString(block.diskSize)} + {Utils.bytesToString(block.diskSize)} </td> <td> {locations.map(l => <span>{l}<br/></span>)} @@ -104,10 +123,10 @@ private[spark] class RDDPage(parent: BlockManagerUI) { <tr> <td>{status.blockManagerId.host + ":" + status.blockManagerId.port}</td> <td> - {Utils.memoryBytesToString(status.memUsed(prefix))} - ({Utils.memoryBytesToString(status.memRemaining)} Total Available) + {Utils.bytesToString(status.memUsed(prefix))} + ({Utils.bytesToString(status.memRemaining)} Remaining) </td> - <td>{Utils.memoryBytesToString(status.diskUsed(prefix))}</td> + <td>{Utils.bytesToString(status.diskUsed(prefix))}</td> </tr> } } diff --git a/core/src/main/scala/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index c381a0510b..e674d120ea 100644 --- a/core/src/main/scala/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import akka.actor.{ActorSystem, ExtendedActorSystem} import com.typesafe.config.ConfigFactory diff --git a/core/src/main/scala/spark/util/BoundedPriorityQueue.scala b/core/src/main/scala/org/apache/spark/util/BoundedPriorityQueue.scala index 4bc5db8bb7..0b51c23f7b 100644 --- a/core/src/main/scala/spark/util/BoundedPriorityQueue.scala +++ b/core/src/main/scala/org/apache/spark/util/BoundedPriorityQueue.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.io.Serializable import java.util.{PriorityQueue => JPriorityQueue} diff --git a/core/src/main/scala/spark/util/ByteBufferInputStream.scala b/core/src/main/scala/org/apache/spark/util/ByteBufferInputStream.scala index d7e67497fe..e214d2a519 100644 --- a/core/src/main/scala/spark/util/ByteBufferInputStream.scala +++ b/core/src/main/scala/org/apache/spark/util/ByteBufferInputStream.scala @@ -1,8 +1,25 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.io.InputStream import java.nio.ByteBuffer -import spark.storage.BlockManager +import org.apache.spark.storage.BlockManager /** * Reads data from a ByteBuffer, and optionally cleans it up using BlockManager.dispose() diff --git a/core/src/main/scala/org/apache/spark/util/Clock.scala b/core/src/main/scala/org/apache/spark/util/Clock.scala new file mode 100644 index 0000000000..97c2b45aab --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/Clock.scala @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +/** + * An interface to represent clocks, so that they can be mocked out in unit tests. + */ +private[spark] trait Clock { + def getTime(): Long +} + +private[spark] object SystemClock extends Clock { + def getTime(): Long = System.currentTimeMillis() +} diff --git a/core/src/main/scala/spark/ClosureCleaner.scala b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala index d5e7132ff9..7108595e3e 100644 --- a/core/src/main/scala/spark/ClosureCleaner.scala +++ b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.lang.reflect.Field @@ -8,6 +25,7 @@ import scala.collection.mutable.Set import org.objectweb.asm.{ClassReader, ClassVisitor, MethodVisitor, Type} import org.objectweb.asm.Opcodes._ import java.io.{InputStream, IOException, ByteArrayOutputStream, ByteArrayInputStream, BufferedInputStream} +import org.apache.spark.Logging private[spark] object ClosureCleaner extends Logging { // Get an ASM class reader for a given class from the JAR that loaded it diff --git a/core/src/main/scala/org/apache/spark/util/CompletionIterator.scala b/core/src/main/scala/org/apache/spark/util/CompletionIterator.scala new file mode 100644 index 0000000000..dc15a38b29 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/CompletionIterator.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +/** + * Wrapper around an iterator which calls a completion method after it successfully iterates through all the elements + */ +abstract class CompletionIterator[+A, +I <: Iterator[A]](sub: I) extends Iterator[A]{ + def next = sub.next + def hasNext = { + val r = sub.hasNext + if (!r) { + completion + } + r + } + + def completion() +} + +object CompletionIterator { + def apply[A, I <: Iterator[A]](sub: I, completionFunction: => Unit) : CompletionIterator[A,I] = { + new CompletionIterator[A,I](sub) { + def completion() = completionFunction + } + } +} diff --git a/core/src/main/scala/spark/util/Distribution.scala b/core/src/main/scala/org/apache/spark/util/Distribution.scala index 24738b4307..33bf3562fe 100644 --- a/core/src/main/scala/spark/util/Distribution.scala +++ b/core/src/main/scala/org/apache/spark/util/Distribution.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.io.PrintStream @@ -62,4 +79,4 @@ object Distribution { quantiles.foreach{q => out.print(q + "\t")} out.println } -}
\ No newline at end of file +} diff --git a/core/src/main/scala/org/apache/spark/util/IdGenerator.scala b/core/src/main/scala/org/apache/spark/util/IdGenerator.scala new file mode 100644 index 0000000000..17e55f7996 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/IdGenerator.scala @@ -0,0 +1,31 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +import java.util.concurrent.atomic.AtomicInteger + +/** + * A util used to get a unique generation ID. This is a wrapper around Java's + * AtomicInteger. An example usage is in BlockManager, where each BlockManager + * instance would start an Akka actor and we use this utility to assign the Akka + * actors unique names. + */ +private[spark] class IdGenerator { + private var id = new AtomicInteger + def next: Int = id.incrementAndGet +} diff --git a/core/src/main/scala/org/apache/spark/util/IntParam.scala b/core/src/main/scala/org/apache/spark/util/IntParam.scala new file mode 100644 index 0000000000..626bb49eea --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/IntParam.scala @@ -0,0 +1,31 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +/** + * An extractor object for parsing strings into integers. + */ +private[spark] object IntParam { + def unapply(str: String): Option[Int] = { + try { + Some(str.toInt) + } catch { + case e: NumberFormatException => None + } + } +} diff --git a/core/src/main/scala/org/apache/spark/util/MemoryParam.scala b/core/src/main/scala/org/apache/spark/util/MemoryParam.scala new file mode 100644 index 0000000000..4869c9897a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/MemoryParam.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +/** + * An extractor object for parsing JVM memory strings, such as "10g", into an Int representing + * the number of megabytes. Supports the same formats as Utils.memoryStringToMb. + */ +private[spark] object MemoryParam { + def unapply(str: String): Option[Int] = { + try { + Some(Utils.memoryStringToMb(str)) + } catch { + case e: NumberFormatException => None + } + } +} diff --git a/core/src/main/scala/spark/util/MetadataCleaner.scala b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala index dafa906712..a430a75451 100644 --- a/core/src/main/scala/spark/util/MetadataCleaner.scala +++ b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala @@ -1,8 +1,25 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.util.concurrent.{TimeUnit, ScheduledFuture, Executors} import java.util.{TimerTask, Timer} -import spark.Logging +import org.apache.spark.Logging /** diff --git a/core/src/main/scala/org/apache/spark/util/MutablePair.scala b/core/src/main/scala/org/apache/spark/util/MutablePair.scala new file mode 100644 index 0000000000..34f1f6606f --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/MutablePair.scala @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + + +/** + * A tuple of 2 elements. This can be used as an alternative to Scala's Tuple2 when we want to + * minimize object allocation. + * + * @param _1 Element 1 of this MutablePair + * @param _2 Element 2 of this MutablePair + */ +case class MutablePair[@specialized(Int, Long, Double, Char, Boolean/*, AnyRef*/) T1, + @specialized(Int, Long, Double, Char, Boolean/*, AnyRef*/) T2] + (var _1: T1, var _2: T2) + extends Product2[T1, T2] +{ + override def toString = "(" + _1 + "," + _2 + ")" + + override def canEqual(that: Any): Boolean = that.isInstanceOf[MutablePair[_,_]] +} diff --git a/core/src/main/scala/spark/util/NextIterator.scala b/core/src/main/scala/org/apache/spark/util/NextIterator.scala index 48b5018ddd..8266e5e495 100644 --- a/core/src/main/scala/spark/util/NextIterator.scala +++ b/core/src/main/scala/org/apache/spark/util/NextIterator.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util /** Provides a basic/boilerplate Iterator implementation. */ private[spark] abstract class NextIterator[U] extends Iterator[U] { @@ -68,4 +85,4 @@ private[spark] abstract class NextIterator[U] extends Iterator[U] { gotNext = false nextValue } -}
\ No newline at end of file +} diff --git a/core/src/main/scala/spark/util/RateLimitedOutputStream.scala b/core/src/main/scala/org/apache/spark/util/RateLimitedOutputStream.scala index e3f00ea8c7..47e1b45004 100644 --- a/core/src/main/scala/spark/util/RateLimitedOutputStream.scala +++ b/core/src/main/scala/org/apache/spark/util/RateLimitedOutputStream.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import scala.annotation.tailrec diff --git a/core/src/main/scala/spark/util/SerializableBuffer.scala b/core/src/main/scala/org/apache/spark/util/SerializableBuffer.scala index 09d588fe1c..f2b1ad7d0e 100644 --- a/core/src/main/scala/spark/util/SerializableBuffer.scala +++ b/core/src/main/scala/org/apache/spark/util/SerializableBuffer.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.nio.ByteBuffer import java.io.{IOException, ObjectOutputStream, EOFException, ObjectInputStream} diff --git a/core/src/main/scala/spark/SizeEstimator.scala b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala index f8a4c4e489..a25b37a2a9 100644 --- a/core/src/main/scala/spark/SizeEstimator.scala +++ b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.lang.reflect.Field import java.lang.reflect.Modifier @@ -13,6 +30,7 @@ import java.lang.management.ManagementFactory import scala.collection.mutable.ArrayBuffer import it.unimi.dsi.fastutil.ints.IntOpenHashSet +import org.apache.spark.Logging /** * Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in diff --git a/core/src/main/scala/spark/util/StatCounter.scala b/core/src/main/scala/org/apache/spark/util/StatCounter.scala index 2b980340b7..020d5edba9 100644 --- a/core/src/main/scala/spark/util/StatCounter.scala +++ b/core/src/main/scala/org/apache/spark/util/StatCounter.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util /** * A class for tracking the statistics of a set of numbers (count, mean and variance) in a diff --git a/core/src/main/scala/spark/util/TimeStampedHashMap.scala b/core/src/main/scala/org/apache/spark/util/TimeStampedHashMap.scala index e95ca1fc8e..dbff571de9 100644 --- a/core/src/main/scala/spark/util/TimeStampedHashMap.scala +++ b/core/src/main/scala/org/apache/spark/util/TimeStampedHashMap.scala @@ -1,9 +1,28 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.util.concurrent.ConcurrentHashMap import scala.collection.JavaConversions import scala.collection.mutable.Map -import spark.scheduler.MapStatus +import scala.collection.immutable +import org.apache.spark.scheduler.MapStatus +import org.apache.spark.Logging /** * This is a custom implementation of scala.collection.mutable.Map which stores the insertion @@ -11,7 +30,7 @@ import spark.scheduler.MapStatus * threshold time can them be removed using the clearOldValues method. This is intended to be a drop-in * replacement of scala.collection.mutable.HashMap. */ -class TimeStampedHashMap[A, B] extends Map[A, B]() with spark.Logging { +class TimeStampedHashMap[A, B] extends Map[A, B]() with Logging { val internalMap = new ConcurrentHashMap[A, (B, Long)]() def get(key: A): Option[B] = { @@ -82,6 +101,8 @@ class TimeStampedHashMap[A, B] extends Map[A, B]() with spark.Logging { } } + def toMap: immutable.Map[A, B] = iterator.toMap + /** * Removes old key-value pairs that have timestamp earlier than `threshTime` */ diff --git a/core/src/main/scala/spark/util/TimeStampedHashSet.scala b/core/src/main/scala/org/apache/spark/util/TimeStampedHashSet.scala index 5f1cc93752..26983138ff 100644 --- a/core/src/main/scala/spark/util/TimeStampedHashSet.scala +++ b/core/src/main/scala/org/apache/spark/util/TimeStampedHashSet.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import scala.collection.mutable.Set import scala.collection.JavaConversions diff --git a/core/src/main/scala/spark/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index e40c5c5c8d..d8d014de7d 100644 --- a/core/src/main/scala/spark/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.io._ import java.net.{InetAddress, URL, URI, NetworkInterface, Inet4Address, ServerSocket} @@ -21,14 +38,18 @@ import scala.Some import com.google.common.io.Files import com.google.common.util.concurrent.ThreadFactoryBuilder -import spark.serializer.SerializerInstance -import spark.deploy.SparkHadoopUtil +import org.apache.hadoop.fs.{Path, FileSystem, FileUtil} + +import org.apache.spark.serializer.{DeserializationStream, SerializationStream, SerializerInstance} +import org.apache.spark.deploy.SparkHadoopUtil +import java.nio.ByteBuffer +import org.apache.spark.{SparkEnv, SparkException, Logging} /** * Various utility methods used by Spark. */ -private object Utils extends Logging { +private[spark] object Utils extends Logging { /** Serialize an object using Java serialization */ def serialize[T](o: T): Array[Byte] = { @@ -56,6 +77,47 @@ private object Utils extends Logging { return ois.readObject.asInstanceOf[T] } + /** Serialize via nested stream using specific serializer */ + def serializeViaNestedStream(os: OutputStream, ser: SerializerInstance)(f: SerializationStream => Unit) = { + val osWrapper = ser.serializeStream(new OutputStream { + def write(b: Int) = os.write(b) + + override def write(b: Array[Byte], off: Int, len: Int) = os.write(b, off, len) + }) + try { + f(osWrapper) + } finally { + osWrapper.close() + } + } + + /** Deserialize via nested stream using specific serializer */ + def deserializeViaNestedStream(is: InputStream, ser: SerializerInstance)(f: DeserializationStream => Unit) = { + val isWrapper = ser.deserializeStream(new InputStream { + def read(): Int = is.read() + + override def read(b: Array[Byte], off: Int, len: Int): Int = is.read(b, off, len) + }) + try { + f(isWrapper) + } finally { + isWrapper.close() + } + } + + /** + * Primitive often used when writing {@link java.nio.ByteBuffer} to {@link java.io.DataOutput}. + */ + def writeByteBuffer(bb: ByteBuffer, out: ObjectOutput) = { + if (bb.hasArray) { + out.write(bb.array(), bb.arrayOffset() + bb.position(), bb.remaining()) + } else { + val bbval = new Array[Byte](bb.remaining()) + bb.get(bbval) + out.write(bbval) + } + } + def isAlpha(c: Char): Boolean = { (c >= 'A' && c <= 'Z') || (c >= 'a' && c <= 'z') } @@ -212,8 +274,9 @@ private object Utils extends Logging { } case _ => // Use the Hadoop filesystem library, which supports file://, hdfs://, s3://, and others + val env = SparkEnv.get val uri = new URI(url) - val conf = SparkHadoopUtil.newConfiguration() + val conf = env.hadoop.newConfiguration() val fs = FileSystem.get(uri, conf) val in = fs.open(new Path(uri)) val out = new FileOutputStream(tempFile) @@ -339,48 +402,17 @@ private object Utils extends Logging { retval } -/* - // Used by DEBUG code : remove when all testing done - private val ipPattern = Pattern.compile("^[0-9]+(\\.[0-9]+)*$") def checkHost(host: String, message: String = "") { - // Currently catches only ipv4 pattern, this is just a debugging tool - not rigourous ! - // if (host.matches("^[0-9]+(\\.[0-9]+)*$")) { - if (ipPattern.matcher(host).matches()) { - Utils.logErrorWithStack("Unexpected to have host " + host + " which matches IP pattern. Message " + message) - } - if (Utils.parseHostPort(host)._2 != 0){ - Utils.logErrorWithStack("Unexpected to have host " + host + " which has port in it. Message " + message) - } + assert(host.indexOf(':') == -1, message) } - // Used by DEBUG code : remove when all testing done def checkHostPort(hostPort: String, message: String = "") { - val (host, port) = Utils.parseHostPort(hostPort) - checkHost(host) - if (port <= 0){ - Utils.logErrorWithStack("Unexpected to have port " + port + " which is not valid in " + hostPort + ". Message " + message) - } + assert(hostPort.indexOf(':') != -1, message) } // Used by DEBUG code : remove when all testing done def logErrorWithStack(msg: String) { try { throw new Exception } catch { case ex: Exception => { logError(msg, ex) } } - // temp code for debug - System.exit(-1) - } -*/ - - // Once testing is complete in various modes, replace with this ? - def checkHost(host: String, message: String = "") {} - def checkHostPort(hostPort: String, message: String = "") {} - - // Used by DEBUG code : remove when all testing done - def logErrorWithStack(msg: String) { - try { throw new Exception } catch { case ex: Exception => { logError(msg, ex) } } - } - - def getUserNameFromEnvironment(): String = { - SparkHadoopUtil.getUserNameFromEnvironment } // Typically, this will be of order of number of nodes in cluster @@ -467,9 +499,9 @@ private object Utils extends Logging { } /** - * Convert a memory quantity in bytes to a human-readable string such as "4.0 MB". + * Convert a quantity in bytes to a human-readable string such as "4.0 MB". */ - def memoryBytesToString(size: Long): String = { + def bytesToString(size: Long): String = { val TB = 1L << 40 val GB = 1L << 30 val MB = 1L << 20 @@ -512,10 +544,10 @@ private object Utils extends Logging { } /** - * Convert a memory quantity in megabytes to a human-readable string such as "4.0 MB". + * Convert a quantity in megabytes to a human-readable string such as "4.0 MB". */ - def memoryMegabytesToString(megabytes: Long): String = { - memoryBytesToString(megabytes * 1024L * 1024L) + def megabytesToString(megabytes: Long): String = { + bytesToString(megabytes * 1024L * 1024L) } /** @@ -588,7 +620,7 @@ private object Utils extends Logging { * A regular expression to match classes of the "core" Spark API that we want to skip when * finding the call site of a method. */ - private val SPARK_CLASS_REGEX = """^spark(\.api\.java)?(\.rdd)?\.[A-Z]""".r + private val SPARK_CLASS_REGEX = """^org\.apache\.spark(\.api\.java)?(\.util)?(\.rdd)?\.[A-Z]""".r private[spark] class CallSiteInfo(val lastSparkMethod: String, val firstUserFile: String, val firstUserLine: Int, val firstUserClass: String) @@ -744,4 +776,13 @@ private object Utils extends Logging { } return buf } + + /* Calculates 'x' modulo 'mod', takes to consideration sign of x, + * i.e. if 'x' is negative, than 'x' % 'mod' is negative too + * so function return (x % mod) + mod in that case. + */ + def nonNegativeMod(x: Int, mod: Int): Int = { + val rawMod = x % mod + rawMod + (if (rawMod < 0) mod else 0) + } } diff --git a/core/src/main/scala/spark/util/Vector.scala b/core/src/main/scala/org/apache/spark/util/Vector.scala index 835822edb2..fe710c58ac 100644 --- a/core/src/main/scala/spark/util/Vector.scala +++ b/core/src/main/scala/org/apache/spark/util/Vector.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util class Vector(val elements: Array[Double]) extends Serializable { def length = elements.length @@ -56,7 +73,6 @@ class Vector(val elements: Array[Double]) extends Serializable { def += (other: Vector): Vector = { if (length != other.length) throw new IllegalArgumentException("Vectors of different length") - var ans = 0.0 var i = 0 while (i < length) { elements(i) += other(i) @@ -100,9 +116,7 @@ object Vector { def apply(elements: Double*) = new Vector(elements.toArray) def apply(length: Int, initializer: Int => Double): Vector = { - val elements = new Array[Double](length) - for (i <- 0 until length) - elements(i) = initializer(i) + val elements: Array[Double] = Array.tabulate(length)(initializer) return new Vector(elements) } @@ -116,7 +130,7 @@ object Vector { implicit def doubleToMultiplier(num: Double) = new Multiplier(num) - implicit object VectorAccumParam extends spark.AccumulatorParam[Vector] { + implicit object VectorAccumParam extends org.apache.spark.AccumulatorParam[Vector] { def addInPlace(t1: Vector, t2: Vector) = t1 + t2 def zero(initialValue: Vector) = Vector.zeros(initialValue.length) diff --git a/core/src/main/scala/spark/Aggregator.scala b/core/src/main/scala/spark/Aggregator.scala deleted file mode 100644 index df8ce9c054..0000000000 --- a/core/src/main/scala/spark/Aggregator.scala +++ /dev/null @@ -1,44 +0,0 @@ -package spark - -import java.util.{HashMap => JHashMap} - -import scala.collection.JavaConversions._ - -/** A set of functions used to aggregate data. - * - * @param createCombiner function to create the initial value of the aggregation. - * @param mergeValue function to merge a new value into the aggregation result. - * @param mergeCombiners function to merge outputs from multiple mergeValue function. - */ -case class Aggregator[K, V, C] ( - val createCombiner: V => C, - val mergeValue: (C, V) => C, - val mergeCombiners: (C, C) => C) { - - def combineValuesByKey(iter: Iterator[(K, V)]) : Iterator[(K, C)] = { - val combiners = new JHashMap[K, C] - for ((k, v) <- iter) { - val oldC = combiners.get(k) - if (oldC == null) { - combiners.put(k, createCombiner(v)) - } else { - combiners.put(k, mergeValue(oldC, v)) - } - } - combiners.iterator - } - - def combineCombinersByKey(iter: Iterator[(K, C)]) : Iterator[(K, C)] = { - val combiners = new JHashMap[K, C] - for ((k, c) <- iter) { - val oldC = combiners.get(k) - if (oldC == null) { - combiners.put(k, c) - } else { - combiners.put(k, mergeCombiners(oldC, c)) - } - } - combiners.iterator - } -} - diff --git a/core/src/main/scala/spark/Cache.scala b/core/src/main/scala/spark/Cache.scala deleted file mode 100644 index 20d677a854..0000000000 --- a/core/src/main/scala/spark/Cache.scala +++ /dev/null @@ -1,63 +0,0 @@ -package spark - -import java.util.concurrent.atomic.AtomicInteger - -private[spark] sealed trait CachePutResponse -private[spark] case class CachePutSuccess(size: Long) extends CachePutResponse -private[spark] case class CachePutFailure() extends CachePutResponse - -/** - * An interface for caches in Spark, to allow for multiple implementations. Caches are used to store - * both partitions of cached RDDs and broadcast variables on Spark executors. Caches are also aware - * of which entries are part of the same dataset (for example, partitions in the same RDD). The key - * for each value in a cache is a (datasetID, partition) pair. - * - * A single Cache instance gets created on each machine and is shared by all caches (i.e. both the - * RDD split cache and the broadcast variable cache), to enable global replacement policies. - * However, because these several independent modules all perform caching, it is important to give - * them separate key namespaces, so that an RDD and a broadcast variable (for example) do not use - * the same key. For this purpose, Cache has the notion of KeySpaces. Each client module must first - * ask for a KeySpace, and then call get() and put() on that space using its own keys. - * - * This abstract class handles the creation of key spaces, so that subclasses need only deal with - * keys that are unique across modules. - */ -private[spark] abstract class Cache { - private val nextKeySpaceId = new AtomicInteger(0) - private def newKeySpaceId() = nextKeySpaceId.getAndIncrement() - - def newKeySpace() = new KeySpace(this, newKeySpaceId()) - - /** - * Get the value for a given (datasetId, partition), or null if it is not - * found. - */ - def get(datasetId: Any, partition: Int): Any - - /** - * Attempt to put a value in the cache; returns CachePutFailure if this was - * not successful (e.g. because the cache replacement policy forbids it), and - * CachePutSuccess if successful. If size estimation is available, the cache - * implementation should set the size field in CachePutSuccess. - */ - def put(datasetId: Any, partition: Int, value: Any): CachePutResponse - - /** - * Report the capacity of the cache partition. By default this just reports - * zero. Specific implementations can choose to provide the capacity number. - */ - def getCapacity: Long = 0L -} - -/** - * A key namespace in a Cache. - */ -private[spark] class KeySpace(cache: Cache, val keySpaceId: Int) { - def get(datasetId: Any, partition: Int): Any = - cache.get((keySpaceId, datasetId), partition) - - def put(datasetId: Any, partition: Int, value: Any): CachePutResponse = - cache.put((keySpaceId, datasetId), partition, value) - - def getCapacity: Long = cache.getCapacity -} diff --git a/core/src/main/scala/spark/FetchFailedException.scala b/core/src/main/scala/spark/FetchFailedException.scala deleted file mode 100644 index 40b0193f19..0000000000 --- a/core/src/main/scala/spark/FetchFailedException.scala +++ /dev/null @@ -1,27 +0,0 @@ -package spark - -import spark.storage.BlockManagerId - -private[spark] class FetchFailedException( - taskEndReason: TaskEndReason, - message: String, - cause: Throwable) - extends Exception { - - def this (bmAddress: BlockManagerId, shuffleId: Int, mapId: Int, reduceId: Int, cause: Throwable) = - this(FetchFailed(bmAddress, shuffleId, mapId, reduceId), - "Fetch failed: %s %d %d %d".format(bmAddress, shuffleId, mapId, reduceId), - cause) - - def this (shuffleId: Int, reduceId: Int, cause: Throwable) = - this(FetchFailed(null, shuffleId, -1, reduceId), - "Unable to fetch locations from master: %d %d".format(shuffleId, reduceId), cause) - - override def getMessage(): String = message - - - override def getCause(): Throwable = cause - - def toTaskEndReason: TaskEndReason = taskEndReason - -} diff --git a/core/src/main/scala/spark/KryoSerializer.scala b/core/src/main/scala/spark/KryoSerializer.scala deleted file mode 100644 index c7dbcc6fbc..0000000000 --- a/core/src/main/scala/spark/KryoSerializer.scala +++ /dev/null @@ -1,224 +0,0 @@ -package spark - -import java.io._ -import java.nio.ByteBuffer -import java.nio.channels.Channels - -import scala.collection.immutable -import scala.collection.mutable - -import com.esotericsoftware.kryo._ -import com.esotericsoftware.kryo.{Serializer => KSerializer} -import com.esotericsoftware.kryo.io.{Input => KryoInput, Output => KryoOutput} -import com.esotericsoftware.kryo.serializers.{JavaSerializer => KryoJavaSerializer} -import de.javakaffee.kryoserializers.KryoReflectionFactorySupport - -import serializer.{SerializerInstance, DeserializationStream, SerializationStream} -import spark.broadcast._ -import spark.storage._ - -private[spark] -class KryoSerializationStream(kryo: Kryo, outStream: OutputStream) extends SerializationStream { - - val output = new KryoOutput(outStream) - - def writeObject[T](t: T): SerializationStream = { - kryo.writeClassAndObject(output, t) - this - } - - def flush() { output.flush() } - def close() { output.close() } -} - -private[spark] -class KryoDeserializationStream(kryo: Kryo, inStream: InputStream) extends DeserializationStream { - - val input = new KryoInput(inStream) - - def readObject[T](): T = { - try { - kryo.readClassAndObject(input).asInstanceOf[T] - } catch { - // DeserializationStream uses the EOF exception to indicate stopping condition. - case e: com.esotericsoftware.kryo.KryoException => throw new java.io.EOFException - } - } - - def close() { - // Kryo's Input automatically closes the input stream it is using. - input.close() - } -} - -private[spark] class KryoSerializerInstance(ks: KryoSerializer) extends SerializerInstance { - - val kryo = ks.kryo.get() - val output = ks.output.get() - val input = ks.input.get() - - def serialize[T](t: T): ByteBuffer = { - output.clear() - kryo.writeClassAndObject(output, t) - ByteBuffer.wrap(output.toBytes) - } - - def deserialize[T](bytes: ByteBuffer): T = { - input.setBuffer(bytes.array) - kryo.readClassAndObject(input).asInstanceOf[T] - } - - def deserialize[T](bytes: ByteBuffer, loader: ClassLoader): T = { - val oldClassLoader = kryo.getClassLoader - kryo.setClassLoader(loader) - input.setBuffer(bytes.array) - val obj = kryo.readClassAndObject(input).asInstanceOf[T] - kryo.setClassLoader(oldClassLoader) - obj - } - - def serializeStream(s: OutputStream): SerializationStream = { - new KryoSerializationStream(kryo, s) - } - - def deserializeStream(s: InputStream): DeserializationStream = { - new KryoDeserializationStream(kryo, s) - } -} - -/** - * Interface implemented by clients to register their classes with Kryo when using Kryo - * serialization. - */ -trait KryoRegistrator { - def registerClasses(kryo: Kryo): Unit -} - -/** - * A Spark serializer that uses the [[http://code.google.com/p/kryo/wiki/V1Documentation Kryo 1.x library]]. - */ -class KryoSerializer extends spark.serializer.Serializer with Logging { - - val bufferSize = System.getProperty("spark.kryoserializer.buffer.mb", "2").toInt * 1024 * 1024 - - val kryo = new ThreadLocal[Kryo] { - override def initialValue = createKryo() - } - - val output = new ThreadLocal[KryoOutput] { - override def initialValue = new KryoOutput(bufferSize) - } - - val input = new ThreadLocal[KryoInput] { - override def initialValue = new KryoInput(bufferSize) - } - - def createKryo(): Kryo = { - val kryo = new KryoReflectionFactorySupport() - - // Register some commonly used classes - val toRegister: Seq[AnyRef] = Seq( - // Arrays - Array(1), Array(1.0), Array(1.0f), Array(1L), Array(""), Array(("", "")), - Array(new java.lang.Object), Array(1.toByte), Array(true), Array('c'), - // Specialized Tuple2s - ("", ""), ("", 1), (1, 1), (1.0, 1.0), (1L, 1L), - (1, 1.0), (1.0, 1), (1L, 1.0), (1.0, 1L), (1, 1L), (1L, 1), - // Scala collections - List(1), mutable.ArrayBuffer(1), - // Options and Either - Some(1), Left(1), Right(1), - // Higher-dimensional tuples - (1, 1, 1), (1, 1, 1, 1), (1, 1, 1, 1, 1), - None, - ByteBuffer.allocate(1), - StorageLevel.MEMORY_ONLY, - PutBlock("1", ByteBuffer.allocate(1), StorageLevel.MEMORY_ONLY), - GotBlock("1", ByteBuffer.allocate(1)), - GetBlock("1") - ) - for (obj <- toRegister) { - kryo.register(obj.getClass) - } - - // Allow sending SerializableWritable - kryo.register(classOf[SerializableWritable[_]], new KryoJavaSerializer()) - kryo.register(classOf[HttpBroadcast[_]], new KryoJavaSerializer()) - - // Register some commonly used Scala singleton objects. Because these - // are singletons, we must return the exact same local object when we - // deserialize rather than returning a clone as FieldSerializer would. - class SingletonSerializer[T](obj: T) extends KSerializer[T] { - override def write(kryo: Kryo, output: KryoOutput, obj: T) {} - override def read(kryo: Kryo, input: KryoInput, cls: java.lang.Class[T]): T = obj - } - kryo.register(None.getClass, new SingletonSerializer[AnyRef](None)) - kryo.register(Nil.getClass, new SingletonSerializer[AnyRef](Nil)) - - // Register maps with a special serializer since they have complex internal structure - class ScalaMapSerializer(buildMap: Array[(Any, Any)] => scala.collection.Map[Any, Any]) - extends KSerializer[Array[(Any, Any)] => scala.collection.Map[Any, Any]] { - - //hack, look at https://groups.google.com/forum/#!msg/kryo-users/Eu5V4bxCfws/k-8UQ22y59AJ - private final val FAKE_REFERENCE = new Object() - override def write( - kryo: Kryo, - output: KryoOutput, - obj: Array[(Any, Any)] => scala.collection.Map[Any, Any]) { - val map = obj.asInstanceOf[scala.collection.Map[Any, Any]] - output.writeInt(map.size) - for ((k, v) <- map) { - kryo.writeClassAndObject(output, k) - kryo.writeClassAndObject(output, v) - } - } - override def read ( - kryo: Kryo, - input: KryoInput, - cls: Class[Array[(Any, Any)] => scala.collection.Map[Any, Any]]) - : Array[(Any, Any)] => scala.collection.Map[Any, Any] = { - kryo.reference(FAKE_REFERENCE) - val size = input.readInt() - val elems = new Array[(Any, Any)](size) - for (i <- 0 until size) { - val k = kryo.readClassAndObject(input) - val v = kryo.readClassAndObject(input) - elems(i)=(k,v) - } - buildMap(elems).asInstanceOf[Array[(Any, Any)] => scala.collection.Map[Any, Any]] - } - } - kryo.register(mutable.HashMap().getClass, new ScalaMapSerializer(mutable.HashMap() ++ _)) - // TODO: add support for immutable maps too; this is more annoying because there are many - // subclasses of immutable.Map for small maps (with <= 4 entries) - val map1 = Map[Any, Any](1 -> 1) - val map2 = Map[Any, Any](1 -> 1, 2 -> 2) - val map3 = Map[Any, Any](1 -> 1, 2 -> 2, 3 -> 3) - val map4 = Map[Any, Any](1 -> 1, 2 -> 2, 3 -> 3, 4 -> 4) - val map5 = Map[Any, Any](1 -> 1, 2 -> 2, 3 -> 3, 4 -> 4, 5 -> 5) - kryo.register(map1.getClass, new ScalaMapSerializer(mutable.HashMap() ++ _ toMap)) - kryo.register(map2.getClass, new ScalaMapSerializer(mutable.HashMap() ++ _ toMap)) - kryo.register(map3.getClass, new ScalaMapSerializer(mutable.HashMap() ++ _ toMap)) - kryo.register(map4.getClass, new ScalaMapSerializer(mutable.HashMap() ++ _ toMap)) - kryo.register(map5.getClass, new ScalaMapSerializer(mutable.HashMap() ++ _ toMap)) - - // Allow the user to register their own classes by setting spark.kryo.registrator - val regCls = System.getProperty("spark.kryo.registrator") - if (regCls != null) { - logInfo("Running user registrator: " + regCls) - val classLoader = Thread.currentThread.getContextClassLoader - val reg = Class.forName(regCls, true, classLoader).newInstance().asInstanceOf[KryoRegistrator] - reg.registerClasses(kryo) - } - - // Allow disabling Kryo reference tracking if user knows their object graphs don't have loops - kryo.setReferences(System.getProperty("spark.kryo.referenceTracking", "true").toBoolean) - - kryo - } - - def newInstance(): SerializerInstance = { - this.kryo.get().setClassLoader(Thread.currentThread().getContextClassLoader) - new KryoSerializerInstance(this) - } -} diff --git a/core/src/main/scala/spark/Partition.scala b/core/src/main/scala/spark/Partition.scala deleted file mode 100644 index e384308ef6..0000000000 --- a/core/src/main/scala/spark/Partition.scala +++ /dev/null @@ -1,14 +0,0 @@ -package spark - -/** - * A partition of an RDD. - */ -trait Partition extends Serializable { - /** - * Get the split's index within its parent RDD - */ - def index: Int - - // A better default implementation of HashCode - override def hashCode(): Int = index -} diff --git a/core/src/main/scala/spark/SerializableWritable.scala b/core/src/main/scala/spark/SerializableWritable.scala deleted file mode 100644 index 8306fbf570..0000000000 --- a/core/src/main/scala/spark/SerializableWritable.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark - -import java.io._ - -import org.apache.hadoop.io.ObjectWritable -import org.apache.hadoop.io.Writable -import org.apache.hadoop.mapred.JobConf - -class SerializableWritable[T <: Writable](@transient var t: T) extends Serializable { - def value = t - override def toString = t.toString - - private def writeObject(out: ObjectOutputStream) { - out.defaultWriteObject() - new ObjectWritable(t).write(out) - } - - private def readObject(in: ObjectInputStream) { - in.defaultReadObject() - val ow = new ObjectWritable() - ow.setConf(new JobConf()) - ow.readFields(in) - t = ow.get().asInstanceOf[T] - } -} diff --git a/core/src/main/scala/spark/ShuffleFetcher.scala b/core/src/main/scala/spark/ShuffleFetcher.scala deleted file mode 100644 index 9513a00126..0000000000 --- a/core/src/main/scala/spark/ShuffleFetcher.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark - -import spark.executor.TaskMetrics -import spark.serializer.Serializer - - -private[spark] abstract class ShuffleFetcher { - /** - * Fetch the shuffle outputs for a given ShuffleDependency. - * @return An iterator over the elements of the fetched shuffle outputs. - */ - def fetch[K, V](shuffleId: Int, reduceId: Int, metrics: TaskMetrics, - serializer: Serializer = SparkEnv.get.serializerManager.default): Iterator[(K,V)] - - /** Stop the fetcher */ - def stop() {} -} diff --git a/core/src/main/scala/spark/SoftReferenceCache.scala b/core/src/main/scala/spark/SoftReferenceCache.scala deleted file mode 100644 index 3dd0a4b1f9..0000000000 --- a/core/src/main/scala/spark/SoftReferenceCache.scala +++ /dev/null @@ -1,18 +0,0 @@ -package spark - -import com.google.common.collect.MapMaker - -/** - * An implementation of Cache that uses soft references. - */ -private[spark] class SoftReferenceCache extends Cache { - val map = new MapMaker().softValues().makeMap[Any, Any]() - - override def get(datasetId: Any, partition: Int): Any = - map.get((datasetId, partition)) - - override def put(datasetId: Any, partition: Int, value: Any): CachePutResponse = { - map.put((datasetId, partition), value) - return CachePutSuccess(0) - } -} diff --git a/core/src/main/scala/spark/SparkException.scala b/core/src/main/scala/spark/SparkException.scala deleted file mode 100644 index aa7a16d7dd..0000000000 --- a/core/src/main/scala/spark/SparkException.scala +++ /dev/null @@ -1,7 +0,0 @@ -package spark - -class SparkException(message: String, cause: Throwable) - extends Exception(message, cause) { - - def this(message: String) = this(message, null) -} diff --git a/core/src/main/scala/spark/SparkFiles.java b/core/src/main/scala/spark/SparkFiles.java deleted file mode 100644 index 566aec622c..0000000000 --- a/core/src/main/scala/spark/SparkFiles.java +++ /dev/null @@ -1,25 +0,0 @@ -package spark; - -import java.io.File; - -/** - * Resolves paths to files added through `SparkContext.addFile()`. - */ -public class SparkFiles { - - private SparkFiles() {} - - /** - * Get the absolute path of a file added through `SparkContext.addFile()`. - */ - public static String get(String filename) { - return new File(getRootDirectory(), filename).getAbsolutePath(); - } - - /** - * Get the root directory that contains files added through `SparkContext.addFile()`. - */ - public static String getRootDirectory() { - return SparkEnv.get().sparkFilesDir(); - } -} diff --git a/core/src/main/scala/spark/TaskContext.scala b/core/src/main/scala/spark/TaskContext.scala deleted file mode 100644 index dd0609026a..0000000000 --- a/core/src/main/scala/spark/TaskContext.scala +++ /dev/null @@ -1,24 +0,0 @@ -package spark - -import executor.TaskMetrics -import scala.collection.mutable.ArrayBuffer - -class TaskContext( - val stageId: Int, - val splitId: Int, - val attemptId: Long, - val taskMetrics: TaskMetrics = TaskMetrics.empty() -) extends Serializable { - - @transient val onCompleteCallbacks = new ArrayBuffer[() => Unit] - - // Add a callback function to be executed on task completion. An example use - // is for HadoopRDD to register a callback to close the input stream. - def addOnCompleteCallback(f: () => Unit) { - onCompleteCallbacks += f - } - - def executeOnCompleteCallbacks() { - onCompleteCallbacks.foreach{_()} - } -} diff --git a/core/src/main/scala/spark/api/java/function/DoubleFlatMapFunction.java b/core/src/main/scala/spark/api/java/function/DoubleFlatMapFunction.java deleted file mode 100644 index 3a8192be3a..0000000000 --- a/core/src/main/scala/spark/api/java/function/DoubleFlatMapFunction.java +++ /dev/null @@ -1,20 +0,0 @@ -package spark.api.java.function; - - -import scala.runtime.AbstractFunction1; - -import java.io.Serializable; - -/** - * A function that returns zero or more records of type Double from each input record. - */ -// DoubleFlatMapFunction does not extend FlatMapFunction because flatMap is -// overloaded for both FlatMapFunction and DoubleFlatMapFunction. -public abstract class DoubleFlatMapFunction<T> extends AbstractFunction1<T, Iterable<Double>> - implements Serializable { - - public abstract Iterable<Double> call(T t); - - @Override - public final Iterable<Double> apply(T t) { return call(t); } -} diff --git a/core/src/main/scala/spark/api/java/function/DoubleFunction.java b/core/src/main/scala/spark/api/java/function/DoubleFunction.java deleted file mode 100644 index c6ef76d088..0000000000 --- a/core/src/main/scala/spark/api/java/function/DoubleFunction.java +++ /dev/null @@ -1,17 +0,0 @@ -package spark.api.java.function; - - -import scala.runtime.AbstractFunction1; - -import java.io.Serializable; - -/** - * A function that returns Doubles, and can be used to construct DoubleRDDs. - */ -// DoubleFunction does not extend Function because some UDF functions, like map, -// are overloaded for both Function and DoubleFunction. -public abstract class DoubleFunction<T> extends WrappedFunction1<T, Double> - implements Serializable { - - public abstract Double call(T t) throws Exception; -} diff --git a/core/src/main/scala/spark/api/java/function/FlatMapFunction.scala b/core/src/main/scala/spark/api/java/function/FlatMapFunction.scala deleted file mode 100644 index e69480607e..0000000000 --- a/core/src/main/scala/spark/api/java/function/FlatMapFunction.scala +++ /dev/null @@ -1,13 +0,0 @@ -package spark.api.java.function - -import scala.reflect.ClassTag - -/** - * A function that returns zero or more output records from each input record. - */ -abstract class FlatMapFunction[T, R] extends Function[T, java.lang.Iterable[R]] { - @throws(classOf[Exception]) - def call(x: T) : java.lang.Iterable[R] - - def elementType() : ClassTag[R] = ClassTag.Any.asInstanceOf[ClassTag[R]] -} diff --git a/core/src/main/scala/spark/api/java/function/FlatMapFunction2.scala b/core/src/main/scala/spark/api/java/function/FlatMapFunction2.scala deleted file mode 100644 index 4562884eb3..0000000000 --- a/core/src/main/scala/spark/api/java/function/FlatMapFunction2.scala +++ /dev/null @@ -1,13 +0,0 @@ -package spark.api.java.function - -import scala.reflect.ClassTag - -/** - * A function that takes two inputs and returns zero or more output records. - */ -abstract class FlatMapFunction2[A, B, C] extends Function2[A, B, java.lang.Iterable[C]] { - @throws(classOf[Exception]) - def call(a: A, b:B) : java.lang.Iterable[C] - - def elementType() : ClassTag[C] = ClassTag.Any.asInstanceOf[ClassTag[C]] -} diff --git a/core/src/main/scala/spark/api/java/function/Function.java b/core/src/main/scala/spark/api/java/function/Function.java deleted file mode 100644 index 9f6ab9a592..0000000000 --- a/core/src/main/scala/spark/api/java/function/Function.java +++ /dev/null @@ -1,22 +0,0 @@ -package spark.api.java.function; - -import scala.reflect.ClassTag; -import scala.reflect.ClassTag$; -import scala.runtime.AbstractFunction1; - -import java.io.Serializable; - - -/** - * Base class for functions whose return types do not create special RDDs. PairFunction and - * DoubleFunction are handled separately, to allow PairRDDs and DoubleRDDs to be constructed - * when mapping RDDs of other types. - */ -public abstract class Function<T, R> extends WrappedFunction1<T, R> implements Serializable { - public abstract R call(T t) throws Exception; - - public ClassTag<R> returnType() { - return (ClassTag<R>) ClassTag$.MODULE$.apply(Object.class); - } -} - diff --git a/core/src/main/scala/spark/api/java/function/Function2.java b/core/src/main/scala/spark/api/java/function/Function2.java deleted file mode 100644 index b32c178aa3..0000000000 --- a/core/src/main/scala/spark/api/java/function/Function2.java +++ /dev/null @@ -1,22 +0,0 @@ -package spark.api.java.function; - -import scala.reflect.ClassTag; -import scala.reflect.ClassTag$; -import scala.runtime.AbstractFunction2; - -import java.io.Serializable; - -/** - * A two-argument function that takes arguments of type T1 and T2 and returns an R. - */ -public abstract class Function2<T1, T2, R> extends WrappedFunction2<T1, T2, R> - implements Serializable { - - public abstract R call(T1 t1, T2 t2) throws Exception; - - public ClassTag<R> returnType() { - return (ClassTag<R>) ClassTag$.MODULE$.apply(Object.class); - } - -} - diff --git a/core/src/main/scala/spark/api/java/function/PairFunction.java b/core/src/main/scala/spark/api/java/function/PairFunction.java deleted file mode 100644 index e3f94788e2..0000000000 --- a/core/src/main/scala/spark/api/java/function/PairFunction.java +++ /dev/null @@ -1,28 +0,0 @@ -package spark.api.java.function; - -import scala.Tuple2; -import scala.reflect.ClassTag; -import scala.reflect.ClassTag$; -import scala.runtime.AbstractFunction1; - -import java.io.Serializable; - -/** - * A function that returns key-value pairs (Tuple2<K, V>), and can be used to construct PairRDDs. - */ -// PairFunction does not extend Function because some UDF functions, like map, -// are overloaded for both Function and PairFunction. -public abstract class PairFunction<T, K, V> - extends WrappedFunction1<T, Tuple2<K, V>> - implements Serializable { - - public abstract Tuple2<K, V> call(T t) throws Exception; - - public ClassTag<K> keyType() { - return (ClassTag<K>) ClassTag$.MODULE$.apply(Object.class); - } - - public ClassTag<V> valueType() { - return (ClassTag<V>) ClassTag$.MODULE$.apply(Object.class); - } -} diff --git a/core/src/main/scala/spark/api/java/function/VoidFunction.scala b/core/src/main/scala/spark/api/java/function/VoidFunction.scala deleted file mode 100644 index b0096cf2bf..0000000000 --- a/core/src/main/scala/spark/api/java/function/VoidFunction.scala +++ /dev/null @@ -1,16 +0,0 @@ -package spark.api.java.function - -/** - * A function with no return value. - */ -// This allows Java users to write void methods without having to return Unit. -abstract class VoidFunction[T] extends Serializable { - @throws(classOf[Exception]) - def call(t: T) : Unit -} - -// VoidFunction cannot extend AbstractFunction1 (because that would force users to explicitly -// return Unit), so it is implicitly converted to a Function1[T, Unit]: -object VoidFunction { - implicit def toFunction[T](f: VoidFunction[T]) : Function1[T, Unit] = ((x : T) => f.call(x)) -}
\ No newline at end of file diff --git a/core/src/main/scala/spark/api/java/function/WrappedFunction1.scala b/core/src/main/scala/spark/api/java/function/WrappedFunction1.scala deleted file mode 100644 index 923f5cdf4f..0000000000 --- a/core/src/main/scala/spark/api/java/function/WrappedFunction1.scala +++ /dev/null @@ -1,15 +0,0 @@ -package spark.api.java.function - -import scala.runtime.AbstractFunction1 - -/** - * Subclass of Function1 for ease of calling from Java. The main thing it does is re-expose the - * apply() method as call() and declare that it can throw Exception (since AbstractFunction1.apply - * isn't marked to allow that). - */ -private[spark] abstract class WrappedFunction1[T, R] extends AbstractFunction1[T, R] { - @throws(classOf[Exception]) - def call(t: T): R - - final def apply(t: T): R = call(t) -} diff --git a/core/src/main/scala/spark/api/java/function/WrappedFunction2.scala b/core/src/main/scala/spark/api/java/function/WrappedFunction2.scala deleted file mode 100644 index 2c6e9b1571..0000000000 --- a/core/src/main/scala/spark/api/java/function/WrappedFunction2.scala +++ /dev/null @@ -1,15 +0,0 @@ -package spark.api.java.function - -import scala.runtime.AbstractFunction2 - -/** - * Subclass of Function2 for ease of calling from Java. The main thing it does is re-expose the - * apply() method as call() and declare that it can throw Exception (since AbstractFunction2.apply - * isn't marked to allow that). - */ -private[spark] abstract class WrappedFunction2[T1, T2, R] extends AbstractFunction2[T1, T2, R] { - @throws(classOf[Exception]) - def call(t1: T1, t2: T2): R - - final def apply(t1: T1, t2: T2): R = call(t1, t2) -} diff --git a/core/src/main/scala/spark/api/python/PythonPartitioner.scala b/core/src/main/scala/spark/api/python/PythonPartitioner.scala deleted file mode 100644 index d618c098c2..0000000000 --- a/core/src/main/scala/spark/api/python/PythonPartitioner.scala +++ /dev/null @@ -1,48 +0,0 @@ -package spark.api.python - -import spark.Partitioner - -import java.util.Arrays - -/** - * A [[spark.Partitioner]] that performs handling of byte arrays, for use by the Python API. - * - * Stores the unique id() of the Python-side partitioning function so that it is incorporated into - * equality comparisons. Correctness requires that the id is a unique identifier for the - * lifetime of the program (i.e. that it is not re-used as the id of a different partitioning - * function). This can be ensured by using the Python id() function and maintaining a reference - * to the Python partitioning function so that its id() is not reused. - */ -private[spark] class PythonPartitioner( - override val numPartitions: Int, - val pyPartitionFunctionId: Long) - extends Partitioner { - - override def getPartition(key: Any): Int = { - if (key == null) { - return 0 - } - else { - val hashCode = { - if (key.isInstanceOf[Array[Byte]]) { - Arrays.hashCode(key.asInstanceOf[Array[Byte]]) - } else { - key.hashCode() - } - } - val mod = hashCode % numPartitions - if (mod < 0) { - mod + numPartitions - } else { - mod // Guard against negative hash codes - } - } - } - - override def equals(other: Any): Boolean = other match { - case h: PythonPartitioner => - h.numPartitions == numPartitions && h.pyPartitionFunctionId == pyPartitionFunctionId - case _ => - false - } -} diff --git a/core/src/main/scala/spark/api/python/PythonWorkerFactory.scala b/core/src/main/scala/spark/api/python/PythonWorkerFactory.scala deleted file mode 100644 index 7163f01b24..0000000000 --- a/core/src/main/scala/spark/api/python/PythonWorkerFactory.scala +++ /dev/null @@ -1,113 +0,0 @@ -package spark.api.python - -import java.io.{DataInputStream, IOException} -import java.net.{Socket, SocketException, InetAddress} - -import scala.collection.JavaConversions._ - -import spark._ - -private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String, String]) - extends Logging { - var daemon: Process = null - val daemonHost = InetAddress.getByAddress(Array(127, 0, 0, 1)) - var daemonPort: Int = 0 - - def create(): Socket = { - synchronized { - // Start the daemon if it hasn't been started - startDaemon() - - // Attempt to connect, restart and retry once if it fails - try { - new Socket(daemonHost, daemonPort) - } catch { - case exc: SocketException => { - logWarning("Python daemon unexpectedly quit, attempting to restart") - stopDaemon() - startDaemon() - new Socket(daemonHost, daemonPort) - } - case e : Throwable => throw e - } - } - } - - def stop() { - stopDaemon() - } - - private def startDaemon() { - synchronized { - // Is it already running? - if (daemon != null) { - return - } - - try { - // Create and start the daemon - val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME") - val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/daemon.py")) - val workerEnv = pb.environment() - workerEnv.putAll(envVars) - daemon = pb.start() - - // Redirect the stderr to ours - new Thread("stderr reader for " + pythonExec) { - override def run() { - scala.util.control.Exception.ignoring(classOf[IOException]) { - // FIXME HACK: We copy the stream on the level of bytes to - // attempt to dodge encoding problems. - val in = daemon.getErrorStream - var buf = new Array[Byte](1024) - var len = in.read(buf) - while (len != -1) { - System.err.write(buf, 0, len) - len = in.read(buf) - } - } - } - }.start() - - val in = new DataInputStream(daemon.getInputStream) - daemonPort = in.readInt() - - // Redirect further stdout output to our stderr - new Thread("stdout reader for " + pythonExec) { - override def run() { - scala.util.control.Exception.ignoring(classOf[IOException]) { - // FIXME HACK: We copy the stream on the level of bytes to - // attempt to dodge encoding problems. - var buf = new Array[Byte](1024) - var len = in.read(buf) - while (len != -1) { - System.err.write(buf, 0, len) - len = in.read(buf) - } - } - } - }.start() - } catch { - case e :Throwable => { - stopDaemon() - throw e - } - } - - // Important: don't close daemon's stdin (daemon.getOutputStream) so it can correctly - // detect our disappearance. - } - } - - private def stopDaemon() { - synchronized { - // Request shutdown of existing daemon by sending SIGTERM - if (daemon != null) { - daemon.destroy() - } - - daemon = null - daemonPort = 0 - } - } -} diff --git a/core/src/main/scala/spark/broadcast/BroadcastFactory.scala b/core/src/main/scala/spark/broadcast/BroadcastFactory.scala deleted file mode 100644 index 5c6184c3c7..0000000000 --- a/core/src/main/scala/spark/broadcast/BroadcastFactory.scala +++ /dev/null @@ -1,13 +0,0 @@ -package spark.broadcast - -/** - * An interface for all the broadcast implementations in Spark (to allow - * multiple broadcast implementations). SparkContext uses a user-specified - * BroadcastFactory implementation to instantiate a particular broadcast for the - * entire Spark job. - */ -private[spark] trait BroadcastFactory { - def initialize(isDriver: Boolean): Unit - def newBroadcast[T](value: T, isLocal: Boolean, id: Long): Broadcast[T] - def stop(): Unit -} diff --git a/core/src/main/scala/spark/deploy/ApplicationDescription.scala b/core/src/main/scala/spark/deploy/ApplicationDescription.scala deleted file mode 100644 index 02193c7008..0000000000 --- a/core/src/main/scala/spark/deploy/ApplicationDescription.scala +++ /dev/null @@ -1,15 +0,0 @@ -package spark.deploy - -private[spark] class ApplicationDescription( - val name: String, - val maxCores: Int, /* Integer.MAX_VALUE denotes an unlimited number of cores */ - val memoryPerSlave: Int, - val command: Command, - val sparkHome: String, - val appUiUrl: String) - extends Serializable { - - val user = System.getProperty("user.name", "<unknown>") - - override def toString: String = "ApplicationDescription(" + name + ")" -} diff --git a/core/src/main/scala/spark/deploy/Command.scala b/core/src/main/scala/spark/deploy/Command.scala deleted file mode 100644 index 577101e3c3..0000000000 --- a/core/src/main/scala/spark/deploy/Command.scala +++ /dev/null @@ -1,9 +0,0 @@ -package spark.deploy - -import scala.collection.Map - -private[spark] case class Command( - mainClass: String, - arguments: Seq[String], - environment: Map[String, String]) { -} diff --git a/core/src/main/scala/spark/deploy/DeployMessage.scala b/core/src/main/scala/spark/deploy/DeployMessage.scala deleted file mode 100644 index 51274acb1e..0000000000 --- a/core/src/main/scala/spark/deploy/DeployMessage.scala +++ /dev/null @@ -1,108 +0,0 @@ -package spark.deploy - -import spark.deploy.ExecutorState.ExecutorState -import spark.deploy.master.{WorkerInfo, ApplicationInfo} -import spark.deploy.worker.ExecutorRunner -import scala.collection.immutable.List -import spark.Utils - - -private[spark] sealed trait DeployMessage extends Serializable - -// Worker to Master - -private[spark] -case class RegisterWorker( - id: String, - host: String, - port: Int, - cores: Int, - memory: Int, - webUiPort: Int, - publicAddress: String) - extends DeployMessage { - Utils.checkHost(host, "Required hostname") - assert (port > 0) -} - -private[spark] -case class ExecutorStateChanged( - appId: String, - execId: Int, - state: ExecutorState, - message: Option[String], - exitStatus: Option[Int]) - extends DeployMessage - -private[spark] case class Heartbeat(workerId: String) extends DeployMessage - -// Master to Worker - -private[spark] case class RegisteredWorker(masterWebUiUrl: String) extends DeployMessage -private[spark] case class RegisterWorkerFailed(message: String) extends DeployMessage -private[spark] case class KillExecutor(appId: String, execId: Int) extends DeployMessage - -private[spark] case class LaunchExecutor( - appId: String, - execId: Int, - appDesc: ApplicationDescription, - cores: Int, - memory: Int, - sparkHome: String) - extends DeployMessage - -// Client to Master - -private[spark] case class RegisterApplication(appDescription: ApplicationDescription) - extends DeployMessage - -// Master to Client - -private[spark] -case class RegisteredApplication(appId: String) extends DeployMessage - -private[spark] -case class ExecutorAdded(id: Int, workerId: String, hostPort: String, cores: Int, memory: Int) { - Utils.checkHostPort(hostPort, "Required hostport") -} - -private[spark] -case class ExecutorUpdated(id: Int, state: ExecutorState, message: Option[String], - exitStatus: Option[Int]) - -private[spark] -case class ApplicationRemoved(message: String) - -// Internal message in Client - -private[spark] case object StopClient - -// MasterWebUI To Master - -private[spark] case object RequestMasterState - -// Master to MasterWebUI - -private[spark] -case class MasterState(host: String, port: Int, workers: Array[WorkerInfo], - activeApps: Array[ApplicationInfo], completedApps: Array[ApplicationInfo]) { - - Utils.checkHost(host, "Required hostname") - assert (port > 0) - - def uri = "spark://" + host + ":" + port -} - -// WorkerWebUI to Worker -private[spark] case object RequestWorkerState - -// Worker to WorkerWebUI - -private[spark] -case class WorkerState(host: String, port: Int, workerId: String, executors: List[ExecutorRunner], - finishedExecutors: List[ExecutorRunner], masterUrl: String, cores: Int, memory: Int, - coresUsed: Int, memoryUsed: Int, masterWebUiUrl: String) { - - Utils.checkHost(host, "Required hostname") - assert (port > 0) -} diff --git a/core/src/main/scala/spark/deploy/ExecutorState.scala b/core/src/main/scala/spark/deploy/ExecutorState.scala deleted file mode 100644 index a487e11f2c..0000000000 --- a/core/src/main/scala/spark/deploy/ExecutorState.scala +++ /dev/null @@ -1,10 +0,0 @@ -package spark.deploy - -private[spark] object ExecutorState extends Enumeration { - - val LAUNCHING, LOADING, RUNNING, KILLED, FAILED, LOST = Value - - type ExecutorState = Value - - def isFinished(state: ExecutorState): Boolean = Seq(KILLED, FAILED, LOST).contains(state) -} diff --git a/core/src/main/scala/spark/deploy/WebUI.scala b/core/src/main/scala/spark/deploy/WebUI.scala deleted file mode 100644 index 844c4142c7..0000000000 --- a/core/src/main/scala/spark/deploy/WebUI.scala +++ /dev/null @@ -1,30 +0,0 @@ -package spark.deploy - -import java.text.SimpleDateFormat -import java.util.Date - -/** - * Utilities used throughout the web UI. - */ -private[spark] object DeployWebUI { - val DATE_FORMAT = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss") - - def formatDate(date: Date): String = DATE_FORMAT.format(date) - - def formatDate(timestamp: Long): String = DATE_FORMAT.format(new Date(timestamp)) - - def formatDuration(milliseconds: Long): String = { - val seconds = milliseconds.toDouble / 1000 - if (seconds < 60) { - return "%.0f s".format(seconds) - } - val minutes = seconds / 60 - if (minutes < 10) { - return "%.1f min".format(minutes) - } else if (minutes < 60) { - return "%.0f min".format(minutes) - } - val hours = minutes / 60 - return "%.1f h".format(hours) - } -} diff --git a/core/src/main/scala/spark/deploy/client/ClientListener.scala b/core/src/main/scala/spark/deploy/client/ClientListener.scala deleted file mode 100644 index e8c4083f9d..0000000000 --- a/core/src/main/scala/spark/deploy/client/ClientListener.scala +++ /dev/null @@ -1,18 +0,0 @@ -package spark.deploy.client - -/** - * Callbacks invoked by deploy client when various events happen. There are currently four events: - * connecting to the cluster, disconnecting, being given an executor, and having an executor - * removed (either due to failure or due to revocation). - * - * Users of this API should *not* block inside the callback methods. - */ -private[spark] trait ClientListener { - def connected(appId: String): Unit - - def disconnected(): Unit - - def executorAdded(fullId: String, workerId: String, hostPort: String, cores: Int, memory: Int): Unit - - def executorRemoved(fullId: String, message: String, exitStatus: Option[Int]): Unit -} diff --git a/core/src/main/scala/spark/deploy/client/TestClient.scala b/core/src/main/scala/spark/deploy/client/TestClient.scala deleted file mode 100644 index f195082808..0000000000 --- a/core/src/main/scala/spark/deploy/client/TestClient.scala +++ /dev/null @@ -1,34 +0,0 @@ -package spark.deploy.client - -import spark.util.AkkaUtils -import spark.{Logging, Utils} -import spark.deploy.{Command, ApplicationDescription} - -private[spark] object TestClient { - - class TestListener extends ClientListener with Logging { - def connected(id: String) { - logInfo("Connected to master, got app ID " + id) - } - - def disconnected() { - logInfo("Disconnected from master") - System.exit(0) - } - - def executorAdded(id: String, workerId: String, hostPort: String, cores: Int, memory: Int) {} - - def executorRemoved(id: String, message: String, exitStatus: Option[Int]) {} - } - - def main(args: Array[String]) { - val url = args(0) - val (actorSystem, port) = AkkaUtils.createActorSystem("spark", Utils.localIpAddress, 0) - val desc = new ApplicationDescription( - "TestClient", 1, 512, Command("spark.deploy.client.TestExecutor", Seq(), Map()), "dummy-spark-home", "ignored") - val listener = new TestListener - val client = new Client(actorSystem, url, desc, listener) - client.start() - actorSystem.awaitTermination() - } -} diff --git a/core/src/main/scala/spark/deploy/client/TestExecutor.scala b/core/src/main/scala/spark/deploy/client/TestExecutor.scala deleted file mode 100644 index 0e46db2272..0000000000 --- a/core/src/main/scala/spark/deploy/client/TestExecutor.scala +++ /dev/null @@ -1,10 +0,0 @@ -package spark.deploy.client - -private[spark] object TestExecutor { - def main(args: Array[String]) { - println("Hello world!") - while (true) { - Thread.sleep(1000) - } - } -} diff --git a/core/src/main/scala/spark/deploy/master/ApplicationState.scala b/core/src/main/scala/spark/deploy/master/ApplicationState.scala deleted file mode 100644 index 4f359711c5..0000000000 --- a/core/src/main/scala/spark/deploy/master/ApplicationState.scala +++ /dev/null @@ -1,10 +0,0 @@ -package spark.deploy.master - -private[spark] object ApplicationState extends Enumeration { - - type ApplicationState = Value - - val WAITING, RUNNING, FINISHED, FAILED = Value - - val MAX_NUM_RETRY = 10 -} diff --git a/core/src/main/scala/spark/deploy/master/ExecutorInfo.scala b/core/src/main/scala/spark/deploy/master/ExecutorInfo.scala deleted file mode 100644 index 48e6055fb5..0000000000 --- a/core/src/main/scala/spark/deploy/master/ExecutorInfo.scala +++ /dev/null @@ -1,15 +0,0 @@ -package spark.deploy.master - -import spark.deploy.ExecutorState - -private[spark] class ExecutorInfo( - val id: Int, - val application: ApplicationInfo, - val worker: WorkerInfo, - val cores: Int, - val memory: Int) { - - var state = ExecutorState.LAUNCHING - - def fullId: String = application.id + "/" + id -} diff --git a/core/src/main/scala/spark/deploy/master/WorkerState.scala b/core/src/main/scala/spark/deploy/master/WorkerState.scala deleted file mode 100644 index 1e347bee20..0000000000 --- a/core/src/main/scala/spark/deploy/master/WorkerState.scala +++ /dev/null @@ -1,7 +0,0 @@ -package spark.deploy.master - -private[spark] object WorkerState extends Enumeration { - type WorkerState = Value - - val ALIVE, DEAD, DECOMMISSIONED = Value -} diff --git a/core/src/main/scala/spark/deploy/master/ui/MasterWebUI.scala b/core/src/main/scala/spark/deploy/master/ui/MasterWebUI.scala deleted file mode 100644 index bcc4d49234..0000000000 --- a/core/src/main/scala/spark/deploy/master/ui/MasterWebUI.scala +++ /dev/null @@ -1,59 +0,0 @@ -package spark.deploy.master.ui - -import akka.actor.ActorRef -import scala.concurrent.duration._ - -import javax.servlet.http.HttpServletRequest - -import org.eclipse.jetty.server.{Handler, Server} - -import spark.{Logging, Utils} -import spark.ui.JettyUtils -import spark.ui.JettyUtils._ - -/** - * Web UI server for the standalone master. - */ -private[spark] -class MasterWebUI(val master: ActorRef, requestedPort: Option[Int] = None) extends Logging { - implicit val timeout = Duration.create( - System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds") - val host = Utils.localHostName() - val port = requestedPort.getOrElse( - System.getProperty("master.ui.port", MasterWebUI.DEFAULT_PORT).toInt) - - var server: Option[Server] = None - var boundPort: Option[Int] = None - - val applicationPage = new ApplicationPage(this) - val indexPage = new IndexPage(this) - - def start() { - try { - val (srv, bPort) = JettyUtils.startJettyServer("0.0.0.0", port, handlers) - server = Some(srv) - boundPort = Some(bPort) - logInfo("Started Master web UI at http://%s:%d".format(host, boundPort.get)) - } catch { - case e: Exception => - logError("Failed to create Master JettyUtils", e) - System.exit(1) - } - } - - val handlers = Array[(String, Handler)]( - ("/static", createStaticHandler(MasterWebUI.STATIC_RESOURCE_DIR)), - ("/app/json", (request: HttpServletRequest) => applicationPage.renderJson(request)), - ("/app", (request: HttpServletRequest) => applicationPage.render(request)), - ("*", (request: HttpServletRequest) => indexPage.render(request)) - ) - - def stop() { - server.foreach(_.stop()) - } -} - -private[spark] object MasterWebUI { - val STATIC_RESOURCE_DIR = "spark/ui/static" - val DEFAULT_PORT = "8080" -} diff --git a/core/src/main/scala/spark/executor/ExecutorBackend.scala b/core/src/main/scala/spark/executor/ExecutorBackend.scala deleted file mode 100644 index e97e509700..0000000000 --- a/core/src/main/scala/spark/executor/ExecutorBackend.scala +++ /dev/null @@ -1,11 +0,0 @@ -package spark.executor - -import java.nio.ByteBuffer -import spark.TaskState.TaskState - -/** - * A pluggable interface used by the Executor to send updates to the cluster scheduler. - */ -private[spark] trait ExecutorBackend { - def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) -} diff --git a/core/src/main/scala/spark/executor/ExecutorURLClassLoader.scala b/core/src/main/scala/spark/executor/ExecutorURLClassLoader.scala deleted file mode 100644 index 5beb4d049e..0000000000 --- a/core/src/main/scala/spark/executor/ExecutorURLClassLoader.scala +++ /dev/null @@ -1,14 +0,0 @@ -package spark.executor - -import java.net.{URLClassLoader, URL} - -/** - * The addURL method in URLClassLoader is protected. We subclass it to make this accessible. - */ -private[spark] class ExecutorURLClassLoader(urls: Array[URL], parent: ClassLoader) - extends URLClassLoader(urls, parent) { - - override def addURL(url: URL) { - super.addURL(url) - } -} diff --git a/core/src/main/scala/spark/network/ConnectionManagerId.scala b/core/src/main/scala/spark/network/ConnectionManagerId.scala deleted file mode 100644 index b554e84251..0000000000 --- a/core/src/main/scala/spark/network/ConnectionManagerId.scala +++ /dev/null @@ -1,21 +0,0 @@ -package spark.network - -import java.net.InetSocketAddress - -import spark.Utils - - -private[spark] case class ConnectionManagerId(host: String, port: Int) { - // DEBUG code - Utils.checkHost(host) - assert (port > 0) - - def toSocketAddress() = new InetSocketAddress(host, port) -} - - -private[spark] object ConnectionManagerId { - def fromSocketAddress(socketAddress: InetSocketAddress): ConnectionManagerId = { - new ConnectionManagerId(socketAddress.getHostName(), socketAddress.getPort()) - } -} diff --git a/core/src/main/scala/spark/network/MessageChunk.scala b/core/src/main/scala/spark/network/MessageChunk.scala deleted file mode 100644 index aaf9204d0e..0000000000 --- a/core/src/main/scala/spark/network/MessageChunk.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark.network - -import java.nio.ByteBuffer - -import scala.collection.mutable.ArrayBuffer - - -private[network] -class MessageChunk(val header: MessageChunkHeader, val buffer: ByteBuffer) { - - val size = if (buffer == null) 0 else buffer.remaining - - lazy val buffers = { - val ab = new ArrayBuffer[ByteBuffer]() - ab += header.buffer - if (buffer != null) { - ab += buffer - } - ab - } - - override def toString = { - "" + this.getClass.getSimpleName + " (id = " + header.id + ", size = " + size + ")" - } -} diff --git a/core/src/main/scala/spark/network/ReceiverTest.scala b/core/src/main/scala/spark/network/ReceiverTest.scala deleted file mode 100644 index a174d5f403..0000000000 --- a/core/src/main/scala/spark/network/ReceiverTest.scala +++ /dev/null @@ -1,20 +0,0 @@ -package spark.network - -import java.nio.ByteBuffer -import java.net.InetAddress - -private[spark] object ReceiverTest { - - def main(args: Array[String]) { - val manager = new ConnectionManager(9999) - println("Started connection manager with id = " + manager.id) - - manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { - /*println("Received [" + msg + "] from [" + id + "] at " + System.currentTimeMillis)*/ - val buffer = ByteBuffer.wrap("response".getBytes()) - Some(Message.createBufferMessage(buffer, msg.id)) - }) - Thread.currentThread.join() - } -} - diff --git a/core/src/main/scala/spark/package.scala b/core/src/main/scala/spark/package.scala deleted file mode 100644 index 389ec4da3e..0000000000 --- a/core/src/main/scala/spark/package.scala +++ /dev/null @@ -1,15 +0,0 @@ -/** - * Core Spark functionality. [[spark.SparkContext]] serves as the main entry point to Spark, while - * [[spark.RDD]] is the data type representing a distributed collection, and provides most - * parallel operations. - * - * In addition, [[spark.PairRDDFunctions]] contains operations available only on RDDs of key-value - * pairs, such as `groupByKey` and `join`; [[spark.DoubleRDDFunctions]] contains operations - * available only on RDDs of Doubles; and [[spark.SequenceFileRDDFunctions]] contains operations - * available on RDDs that can be saved as SequenceFiles. These operations are automatically - * available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit conversions when - * you `import spark.SparkContext._`. - */ -package object spark { - // For package docs only -} diff --git a/core/src/main/scala/spark/partial/ApproximateEvaluator.scala b/core/src/main/scala/spark/partial/ApproximateEvaluator.scala deleted file mode 100644 index 75713b2eaa..0000000000 --- a/core/src/main/scala/spark/partial/ApproximateEvaluator.scala +++ /dev/null @@ -1,10 +0,0 @@ -package spark.partial - -/** - * An object that computes a function incrementally by merging in results of type U from multiple - * tasks. Allows partial evaluation at any point by calling currentResult(). - */ -private[spark] trait ApproximateEvaluator[U, R] { - def merge(outputId: Int, taskResult: U): Unit - def currentResult(): R -} diff --git a/core/src/main/scala/spark/partial/BoundedDouble.scala b/core/src/main/scala/spark/partial/BoundedDouble.scala deleted file mode 100644 index 463c33d6e2..0000000000 --- a/core/src/main/scala/spark/partial/BoundedDouble.scala +++ /dev/null @@ -1,8 +0,0 @@ -package spark.partial - -/** - * A Double with error bars on it. - */ -class BoundedDouble(val mean: Double, val confidence: Double, val low: Double, val high: Double) { - override def toString(): String = "[%.3f, %.3f]".format(low, high) -} diff --git a/core/src/main/scala/spark/rdd/BlockRDD.scala b/core/src/main/scala/spark/rdd/BlockRDD.scala deleted file mode 100644 index 3e60860b3e..0000000000 --- a/core/src/main/scala/spark/rdd/BlockRDD.scala +++ /dev/null @@ -1,36 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag - -import spark.{RDD, SparkContext, SparkEnv, Partition, TaskContext} -import spark.storage.BlockManager - -private[spark] class BlockRDDPartition(val blockId: String, idx: Int) extends Partition { - val index = idx -} - -private[spark] -class BlockRDD[T: ClassTag](sc: SparkContext, @transient blockIds: Array[String]) - extends RDD[T](sc, Nil) { - - @transient lazy val locations_ = BlockManager.blockIdsToExecutorLocations(blockIds, SparkEnv.get) - - override def getPartitions: Array[Partition] = (0 until blockIds.size).map(i => { - new BlockRDDPartition(blockIds(i), i).asInstanceOf[Partition] - }).toArray - - - override def compute(split: Partition, context: TaskContext): Iterator[T] = { - val blockManager = SparkEnv.get.blockManager - val blockId = split.asInstanceOf[BlockRDDPartition].blockId - blockManager.get(blockId) match { - case Some(block) => block.asInstanceOf[Iterator[T]] - case None => - throw new Exception("Could not compute split, block " + blockId + " not found") - } - } - - override def getPreferredLocations(split: Partition): Seq[String] = - locations_(split.asInstanceOf[BlockRDDPartition].blockId) - -} diff --git a/core/src/main/scala/spark/rdd/CoalescedRDD.scala b/core/src/main/scala/spark/rdd/CoalescedRDD.scala deleted file mode 100644 index 0ca678e4af..0000000000 --- a/core/src/main/scala/spark/rdd/CoalescedRDD.scala +++ /dev/null @@ -1,65 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{Dependency, OneToOneDependency, NarrowDependency, RDD, Partition, TaskContext} -import java.io.{ObjectOutputStream, IOException} - -private[spark] case class CoalescedRDDPartition( - index: Int, - @transient rdd: RDD[_], - parentsIndices: Array[Int] - ) extends Partition { - var parents: Seq[Partition] = parentsIndices.map(rdd.partitions(_)) - - @throws(classOf[IOException]) - private def writeObject(oos: ObjectOutputStream) { - // Update the reference to parent split at the time of task serialization - parents = parentsIndices.map(rdd.partitions(_)) - oos.defaultWriteObject() - } -} - -/** - * Coalesce the partitions of a parent RDD (`prev`) into fewer partitions, so that each partition of - * this RDD computes one or more of the parent ones. Will produce exactly `maxPartitions` if the - * parent had more than this many partitions, or fewer if the parent had fewer. - * - * This transformation is useful when an RDD with many partitions gets filtered into a smaller one, - * or to avoid having a large number of small tasks when processing a directory with many files. - */ -class CoalescedRDD[T: ClassTag]( - @transient var prev: RDD[T], - maxPartitions: Int) - extends RDD[T](prev.context, Nil) { // Nil since we implement getDependencies - - override def getPartitions: Array[Partition] = { - val prevSplits = prev.partitions - if (prevSplits.length < maxPartitions) { - prevSplits.map(_.index).map{idx => new CoalescedRDDPartition(idx, prev, Array(idx)) } - } else { - (0 until maxPartitions).map { i => - val rangeStart = ((i.toLong * prevSplits.length) / maxPartitions).toInt - val rangeEnd = (((i.toLong + 1) * prevSplits.length) / maxPartitions).toInt - new CoalescedRDDPartition(i, prev, (rangeStart until rangeEnd).toArray) - }.toArray - } - } - - override def compute(split: Partition, context: TaskContext): Iterator[T] = { - split.asInstanceOf[CoalescedRDDPartition].parents.iterator.flatMap { parentSplit => - firstParent[T].iterator(parentSplit, context) - } - } - - override def getDependencies: Seq[Dependency[_]] = { - Seq(new NarrowDependency(prev) { - def getParents(id: Int): Seq[Int] = - partitions(id).asInstanceOf[CoalescedRDDPartition].parentsIndices - }) - } - - override def clearDependencies() { - super.clearDependencies() - prev = null - } -} diff --git a/core/src/main/scala/spark/rdd/EmptyRDD.scala b/core/src/main/scala/spark/rdd/EmptyRDD.scala deleted file mode 100644 index 3b9899238c..0000000000 --- a/core/src/main/scala/spark/rdd/EmptyRDD.scala +++ /dev/null @@ -1,16 +0,0 @@ -package spark.rdd - -import spark.{RDD, SparkContext, SparkEnv, Partition, TaskContext} -import scala.reflect.ClassTag - -/** - * An RDD that is empty, i.e. has no element in it. - */ -class EmptyRDD[T: ClassTag](sc: SparkContext) extends RDD[T](sc, Nil) { - - override def getPartitions: Array[Partition] = Array.empty - - override def compute(split: Partition, context: TaskContext): Iterator[T] = { - throw new UnsupportedOperationException("empty RDD") - } -} diff --git a/core/src/main/scala/spark/rdd/FilteredRDD.scala b/core/src/main/scala/spark/rdd/FilteredRDD.scala deleted file mode 100644 index eee72520d9..0000000000 --- a/core/src/main/scala/spark/rdd/FilteredRDD.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{OneToOneDependency, RDD, Partition, TaskContext} - -private[spark] class FilteredRDD[T: ClassTag]( - prev: RDD[T], - f: T => Boolean) - extends RDD[T](prev) { - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override val partitioner = prev.partitioner // Since filter cannot change a partition's keys - - override def compute(split: Partition, context: TaskContext) = - firstParent[T].iterator(split, context).filter(f) -} diff --git a/core/src/main/scala/spark/rdd/FlatMappedRDD.scala b/core/src/main/scala/spark/rdd/FlatMappedRDD.scala deleted file mode 100644 index ab39ed6b5d..0000000000 --- a/core/src/main/scala/spark/rdd/FlatMappedRDD.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{RDD, Partition, TaskContext} - - -private[spark] -class FlatMappedRDD[U: ClassTag, T: ClassTag]( - prev: RDD[T], - f: T => TraversableOnce[U]) - extends RDD[U](prev) { - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override def compute(split: Partition, context: TaskContext) = - firstParent[T].iterator(split, context).flatMap(f) -} diff --git a/core/src/main/scala/spark/rdd/GlommedRDD.scala b/core/src/main/scala/spark/rdd/GlommedRDD.scala deleted file mode 100644 index 8783aa2e86..0000000000 --- a/core/src/main/scala/spark/rdd/GlommedRDD.scala +++ /dev/null @@ -1,13 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{RDD, Partition, TaskContext} - -private[spark] class GlommedRDD[T: ClassTag](prev: RDD[T]) - extends RDD[Array[T]](prev) { - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override def compute(split: Partition, context: TaskContext) = - Array(firstParent[T].iterator(split, context).toArray).iterator -} diff --git a/core/src/main/scala/spark/rdd/MapPartitionsRDD.scala b/core/src/main/scala/spark/rdd/MapPartitionsRDD.scala deleted file mode 100644 index 685eefa09e..0000000000 --- a/core/src/main/scala/spark/rdd/MapPartitionsRDD.scala +++ /dev/null @@ -1,21 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{RDD, Partition, TaskContext} - - -private[spark] -class MapPartitionsRDD[U: ClassTag, T: ClassTag]( - prev: RDD[T], - f: Iterator[T] => Iterator[U], - preservesPartitioning: Boolean = false) - extends RDD[U](prev) { - - override val partitioner = - if (preservesPartitioning) firstParent[T].partitioner else None - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override def compute(split: Partition, context: TaskContext) = - f(firstParent[T].iterator(split, context)) -} diff --git a/core/src/main/scala/spark/rdd/MapPartitionsWithIndexRDD.scala b/core/src/main/scala/spark/rdd/MapPartitionsWithIndexRDD.scala deleted file mode 100644 index 2a043c994b..0000000000 --- a/core/src/main/scala/spark/rdd/MapPartitionsWithIndexRDD.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{RDD, Partition, TaskContext} - - -/** - * A variant of the MapPartitionsRDD that passes the partition index into the - * closure. This can be used to generate or collect partition specific - * information such as the number of tuples in a partition. - */ -private[spark] -class MapPartitionsWithIndexRDD[U: ClassTag, T: ClassTag]( - prev: RDD[T], - f: (Int, Iterator[T]) => Iterator[U], - preservesPartitioning: Boolean - ) extends RDD[U](prev) { - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override val partitioner = if (preservesPartitioning) prev.partitioner else None - - override def compute(split: Partition, context: TaskContext) = - f(split.index, firstParent[T].iterator(split, context)) -} diff --git a/core/src/main/scala/spark/rdd/MappedRDD.scala b/core/src/main/scala/spark/rdd/MappedRDD.scala deleted file mode 100644 index 79762e46a2..0000000000 --- a/core/src/main/scala/spark/rdd/MappedRDD.scala +++ /dev/null @@ -1,14 +0,0 @@ -package spark.rdd - -import scala.reflect.ClassTag -import spark.{RDD, Partition, TaskContext} - -private[spark] -class MappedRDD[U: ClassTag, T: ClassTag](prev: RDD[T], f: T => U) - extends RDD[U](prev) { - - override def getPartitions: Array[Partition] = firstParent[T].partitions - - override def compute(split: Partition, context: TaskContext) = - firstParent[T].iterator(split, context).map(f) -} diff --git a/core/src/main/scala/spark/rdd/ShuffledRDD.scala b/core/src/main/scala/spark/rdd/ShuffledRDD.scala deleted file mode 100644 index c7d1926b83..0000000000 --- a/core/src/main/scala/spark/rdd/ShuffledRDD.scala +++ /dev/null @@ -1,37 +0,0 @@ -package spark.rdd - -import spark.{Partitioner, RDD, SparkEnv, ShuffleDependency, Partition, TaskContext} -import spark.SparkContext._ - - -private[spark] class ShuffledRDDPartition(val idx: Int) extends Partition { - override val index = idx - override def hashCode(): Int = idx -} - -/** - * The resulting RDD from a shuffle (e.g. repartitioning of data). - * @param prev the parent RDD. - * @param part the partitioner used to partition the RDD - * @param serializerClass class name of the serializer to use. - * @tparam K the key class. - * @tparam V the value class. - */ -class ShuffledRDD[K, V]( - @transient prev: RDD[(K, V)], - part: Partitioner, - serializerClass: String = null) - extends RDD[(K, V)](prev.context, List(new ShuffleDependency(prev, part, serializerClass))) { - - override val partitioner = Some(part) - - override def getPartitions: Array[Partition] = { - Array.tabulate[Partition](part.numPartitions)(i => new ShuffledRDDPartition(i)) - } - - override def compute(split: Partition, context: TaskContext): Iterator[(K, V)] = { - val shuffledId = dependencies.head.asInstanceOf[ShuffleDependency[K, V]].shuffleId - SparkEnv.get.shuffleFetcher.fetch[K, V](shuffledId, split.index, context.taskMetrics, - SparkEnv.get.serializerManager.get(serializerClass)) - } -} diff --git a/core/src/main/scala/spark/scheduler/ActiveJob.scala b/core/src/main/scala/spark/scheduler/ActiveJob.scala deleted file mode 100644 index 105eaecb22..0000000000 --- a/core/src/main/scala/spark/scheduler/ActiveJob.scala +++ /dev/null @@ -1,22 +0,0 @@ -package spark.scheduler - -import spark.TaskContext - -import java.util.Properties - -/** - * Tracks information about an active job in the DAGScheduler. - */ -private[spark] class ActiveJob( - val runId: Int, - val finalStage: Stage, - val func: (TaskContext, Iterator[_]) => _, - val partitions: Array[Int], - val callSite: String, - val listener: JobListener, - val properties: Properties) { - - val numPartitions = partitions.length - val finished = Array.fill[Boolean](numPartitions)(false) - var numFinished = 0 -} diff --git a/core/src/main/scala/spark/scheduler/JobListener.scala b/core/src/main/scala/spark/scheduler/JobListener.scala deleted file mode 100644 index f46b9d551d..0000000000 --- a/core/src/main/scala/spark/scheduler/JobListener.scala +++ /dev/null @@ -1,11 +0,0 @@ -package spark.scheduler - -/** - * Interface used to listen for job completion or failure events after submitting a job to the - * DAGScheduler. The listener is notified each time a task succeeds, as well as if the whole - * job fails (and no further taskSucceeded events will happen). - */ -private[spark] trait JobListener { - def taskSucceeded(index: Int, result: Any) - def jobFailed(exception: Exception) -} diff --git a/core/src/main/scala/spark/scheduler/JobResult.scala b/core/src/main/scala/spark/scheduler/JobResult.scala deleted file mode 100644 index a0fdf391e6..0000000000 --- a/core/src/main/scala/spark/scheduler/JobResult.scala +++ /dev/null @@ -1,9 +0,0 @@ -package spark.scheduler - -/** - * A result of a job in the DAGScheduler. - */ -private[spark] sealed trait JobResult - -private[spark] case object JobSucceeded extends JobResult -private[spark] case class JobFailed(exception: Exception, failedStage: Option[Stage]) extends JobResult diff --git a/core/src/main/scala/spark/scheduler/MapStatus.scala b/core/src/main/scala/spark/scheduler/MapStatus.scala deleted file mode 100644 index 203abb917b..0000000000 --- a/core/src/main/scala/spark/scheduler/MapStatus.scala +++ /dev/null @@ -1,27 +0,0 @@ -package spark.scheduler - -import spark.storage.BlockManagerId -import java.io.{ObjectOutput, ObjectInput, Externalizable} - -/** - * Result returned by a ShuffleMapTask to a scheduler. Includes the block manager address that the - * task ran on as well as the sizes of outputs for each reducer, for passing on to the reduce tasks. - * The map output sizes are compressed using MapOutputTracker.compressSize. - */ -private[spark] class MapStatus(var location: BlockManagerId, var compressedSizes: Array[Byte]) - extends Externalizable { - - def this() = this(null, null) // For deserialization only - - def writeExternal(out: ObjectOutput) { - location.writeExternal(out) - out.writeInt(compressedSizes.length) - out.write(compressedSizes) - } - - def readExternal(in: ObjectInput) { - location = BlockManagerId(in) - compressedSizes = new Array[Byte](in.readInt()) - in.readFully(compressedSizes) - } -} diff --git a/core/src/main/scala/spark/scheduler/StageInfo.scala b/core/src/main/scala/spark/scheduler/StageInfo.scala deleted file mode 100644 index 8d83ff10c4..0000000000 --- a/core/src/main/scala/spark/scheduler/StageInfo.scala +++ /dev/null @@ -1,12 +0,0 @@ -package spark.scheduler - -import spark.scheduler.cluster.TaskInfo -import scala.collection._ -import spark.executor.TaskMetrics - -case class StageInfo( - val stage: Stage, - val taskInfos: mutable.Buffer[(TaskInfo, TaskMetrics)] = mutable.Buffer[(TaskInfo, TaskMetrics)]() -) { - override def toString = stage.rdd.toString -}
\ No newline at end of file diff --git a/core/src/main/scala/spark/scheduler/TaskResult.scala b/core/src/main/scala/spark/scheduler/TaskResult.scala deleted file mode 100644 index 6de0aa7adf..0000000000 --- a/core/src/main/scala/spark/scheduler/TaskResult.scala +++ /dev/null @@ -1,38 +0,0 @@ -package spark.scheduler - -import java.io._ - -import scala.collection.mutable.Map -import spark.executor.TaskMetrics - -// Task result. Also contains updates to accumulator variables. -// TODO: Use of distributed cache to return result is a hack to get around -// what seems to be a bug with messages over 60KB in libprocess; fix it -private[spark] -class TaskResult[T](var value: T, var accumUpdates: Map[Long, Any], var metrics: TaskMetrics) extends Externalizable { - def this() = this(null.asInstanceOf[T], null, null) - - override def writeExternal(out: ObjectOutput) { - out.writeObject(value) - out.writeInt(accumUpdates.size) - for ((key, value) <- accumUpdates) { - out.writeLong(key) - out.writeObject(value) - } - out.writeObject(metrics) - } - - override def readExternal(in: ObjectInput) { - value = in.readObject().asInstanceOf[T] - val numUpdates = in.readInt - if (numUpdates == 0) { - accumUpdates = null - } else { - accumUpdates = Map() - for (i <- 0 until numUpdates) { - accumUpdates(in.readLong()) = in.readObject() - } - } - metrics = in.readObject().asInstanceOf[TaskMetrics] - } -} diff --git a/core/src/main/scala/spark/scheduler/TaskSchedulerListener.scala b/core/src/main/scala/spark/scheduler/TaskSchedulerListener.scala deleted file mode 100644 index b75d3736cf..0000000000 --- a/core/src/main/scala/spark/scheduler/TaskSchedulerListener.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark.scheduler - -import spark.scheduler.cluster.TaskInfo -import scala.collection.mutable.Map - -import spark.TaskEndReason -import spark.executor.TaskMetrics - -/** - * Interface for getting events back from the TaskScheduler. - */ -private[spark] trait TaskSchedulerListener { - // A task has finished or failed. - def taskEnded(task: Task[_], reason: TaskEndReason, result: Any, accumUpdates: Map[Long, Any], - taskInfo: TaskInfo, taskMetrics: TaskMetrics): Unit - - // A node was added to the cluster. - def executorGained(execId: String, hostPort: String): Unit - - // A node was lost from the cluster. - def executorLost(execId: String): Unit - - // The TaskScheduler wants to abort an entire task set. - def taskSetFailed(taskSet: TaskSet, reason: String): Unit -} diff --git a/core/src/main/scala/spark/scheduler/TaskSet.scala b/core/src/main/scala/spark/scheduler/TaskSet.scala deleted file mode 100644 index e4b5fcaedb..0000000000 --- a/core/src/main/scala/spark/scheduler/TaskSet.scala +++ /dev/null @@ -1,18 +0,0 @@ -package spark.scheduler - -import java.util.Properties - -/** - * A set of tasks submitted together to the low-level TaskScheduler, usually representing - * missing partitions of a particular stage. - */ -private[spark] class TaskSet( - val tasks: Array[Task[_]], - val stageId: Int, - val attempt: Int, - val priority: Int, - val properties: Properties) { - val id: String = stageId + "." + attempt - - override def toString: String = "TaskSet " + id -} diff --git a/core/src/main/scala/spark/scheduler/cluster/ClusterScheduler.scala b/core/src/main/scala/spark/scheduler/cluster/ClusterScheduler.scala deleted file mode 100644 index 3a0c29b27f..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/ClusterScheduler.scala +++ /dev/null @@ -1,614 +0,0 @@ -package spark.scheduler.cluster - -import java.lang.{Boolean => JBoolean} - -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap -import scala.collection.mutable.HashSet - -import spark._ -import spark.TaskState.TaskState -import spark.scheduler._ -import java.nio.ByteBuffer -import java.util.concurrent.atomic.AtomicLong -import java.util.{TimerTask, Timer} - -/** - * The main TaskScheduler implementation, for running tasks on a cluster. Clients should first call - * start(), then submit task sets through the runTasks method. - */ -private[spark] class ClusterScheduler(val sc: SparkContext) - extends TaskScheduler - with Logging { - - // How often to check for speculative tasks - val SPECULATION_INTERVAL = System.getProperty("spark.speculation.interval", "100").toLong - // Threshold above which we warn user initial TaskSet may be starved - val STARVATION_TIMEOUT = System.getProperty("spark.starvation.timeout", "15000").toLong - // How often to revive offers in case there are pending tasks - that is how often to try to get - // tasks scheduled in case there are nodes available : default 0 is to disable it - to preserve existing behavior - // Note that this is required due to delayed scheduling due to data locality waits, etc. - // TODO: rename property ? - val TASK_REVIVAL_INTERVAL = System.getProperty("spark.tasks.revive.interval", "0").toLong - - /* - This property controls how aggressive we should be to modulate waiting for node local task scheduling. - To elaborate, currently there is a time limit (3 sec def) to ensure that spark attempts to wait for node locality of tasks before - scheduling on other nodes. We have modified this in yarn branch such that offers to task set happen in prioritized order : - node-local, rack-local and then others - But once all available node local (and no pref) tasks are scheduled, instead of waiting for 3 sec before - scheduling to other nodes (which degrades performance for time sensitive tasks and on larger clusters), we can - modulate that : to also allow rack local nodes or any node. The default is still set to HOST - so that previous behavior is - maintained. This is to allow tuning the tension between pulling rdd data off node and scheduling computation asap. - - TODO: rename property ? The value is one of - - NODE_LOCAL (default, no change w.r.t current behavior), - - RACK_LOCAL and - - ANY - - Note that this property makes more sense when used in conjugation with spark.tasks.revive.interval > 0 : else it is not very effective. - - Additional Note: For non trivial clusters, there is a 4x - 5x reduction in running time (in some of our experiments) based on whether - it is left at default NODE_LOCAL, RACK_LOCAL (if cluster is configured to be rack aware) or ANY. - If cluster is rack aware, then setting it to RACK_LOCAL gives best tradeoff and a 3x - 4x performance improvement while minimizing IO impact. - Also, it brings down the variance in running time drastically. - */ - val TASK_SCHEDULING_AGGRESSION = TaskLocality.parse(System.getProperty("spark.tasks.schedule.aggression", "NODE_LOCAL")) - - val activeTaskSets = new HashMap[String, TaskSetManager] - - val taskIdToTaskSetId = new HashMap[Long, String] - val taskIdToExecutorId = new HashMap[Long, String] - val taskSetTaskIds = new HashMap[String, HashSet[Long]] - - @volatile private var hasReceivedTask = false - @volatile private var hasLaunchedTask = false - private val starvationTimer = new Timer(true) - - // Incrementing Mesos task IDs - val nextTaskId = new AtomicLong(0) - - // Which executor IDs we have executors on - val activeExecutorIds = new HashSet[String] - - // TODO: We might want to remove this and merge it with execId datastructures - but later. - // Which hosts in the cluster are alive (contains hostPort's) - used for process local and node local task locality. - private val hostPortsAlive = new HashSet[String] - private val hostToAliveHostPorts = new HashMap[String, HashSet[String]] - - // The set of executors we have on each host; this is used to compute hostsAlive, which - // in turn is used to decide when we can attain data locality on a given host - private val executorsByHostPort = new HashMap[String, HashSet[String]] - - private val executorIdToHostPort = new HashMap[String, String] - - // JAR server, if any JARs were added by the user to the SparkContext - var jarServer: HttpServer = null - - // URIs of JARs to pass to executor - var jarUris: String = "" - - // Listener object to pass upcalls into - var listener: TaskSchedulerListener = null - - var backend: SchedulerBackend = null - - val mapOutputTracker = SparkEnv.get.mapOutputTracker - - var schedulableBuilder: SchedulableBuilder = null - var rootPool: Pool = null - - override def setListener(listener: TaskSchedulerListener) { - this.listener = listener - } - - def initialize(context: SchedulerBackend) { - backend = context - //default scheduler is FIFO - val schedulingMode = System.getProperty("spark.cluster.schedulingmode", "FIFO") - //temporarily set rootPool name to empty - rootPool = new Pool("", SchedulingMode.withName(schedulingMode), 0, 0) - schedulableBuilder = { - schedulingMode match { - case "FIFO" => - new FIFOSchedulableBuilder(rootPool) - case "FAIR" => - new FairSchedulableBuilder(rootPool) - } - } - schedulableBuilder.buildPools() - // resolve executorId to hostPort mapping. - def executorToHostPort(executorId: String, defaultHostPort: String): String = { - executorIdToHostPort.getOrElse(executorId, defaultHostPort) - } - - // Unfortunately, this means that SparkEnv is indirectly referencing ClusterScheduler - // Will that be a design violation ? - SparkEnv.get.executorIdToHostPort = Some(executorToHostPort) - } - - - def newTaskId(): Long = nextTaskId.getAndIncrement() - - override def start() { - backend.start() - - if (JBoolean.getBoolean("spark.speculation")) { - new Thread("ClusterScheduler speculation check") { - setDaemon(true) - - override def run() { - logInfo("Starting speculative execution thread") - while (true) { - try { - Thread.sleep(SPECULATION_INTERVAL) - } catch { - case e: InterruptedException => {} - } - checkSpeculatableTasks() - } - } - }.start() - } - - - // Change to always run with some default if TASK_REVIVAL_INTERVAL <= 0 ? - if (TASK_REVIVAL_INTERVAL > 0) { - new Thread("ClusterScheduler task offer revival check") { - setDaemon(true) - - override def run() { - logInfo("Starting speculative task offer revival thread") - while (true) { - try { - Thread.sleep(TASK_REVIVAL_INTERVAL) - } catch { - case e: InterruptedException => {} - } - - if (hasPendingTasks()) backend.reviveOffers() - } - } - }.start() - } - } - - override def submitTasks(taskSet: TaskSet) { - val tasks = taskSet.tasks - logInfo("Adding task set " + taskSet.id + " with " + tasks.length + " tasks") - this.synchronized { - val manager = new ClusterTaskSetManager(this, taskSet) - activeTaskSets(taskSet.id) = manager - schedulableBuilder.addTaskSetManager(manager, manager.taskSet.properties) - taskSetTaskIds(taskSet.id) = new HashSet[Long]() - - if (hasReceivedTask == false) { - starvationTimer.scheduleAtFixedRate(new TimerTask() { - override def run() { - if (!hasLaunchedTask) { - logWarning("Initial job has not accepted any resources; " + - "check your cluster UI to ensure that workers are registered") - } else { - this.cancel() - } - } - }, STARVATION_TIMEOUT, STARVATION_TIMEOUT) - } - hasReceivedTask = true; - } - backend.reviveOffers() - } - - def taskSetFinished(manager: TaskSetManager) { - this.synchronized { - activeTaskSets -= manager.taskSet.id - manager.parent.removeSchedulable(manager) - logInfo("Remove TaskSet %s from pool %s".format(manager.taskSet.id, manager.parent.name)) - taskIdToTaskSetId --= taskSetTaskIds(manager.taskSet.id) - taskIdToExecutorId --= taskSetTaskIds(manager.taskSet.id) - taskSetTaskIds.remove(manager.taskSet.id) - } - } - - /** - * Called by cluster manager to offer resources on slaves. We respond by asking our active task - * sets for tasks in order of priority. We fill each node with tasks in a round-robin manner so - * that tasks are balanced across the cluster. - */ - def resourceOffers(offers: Seq[WorkerOffer]): Seq[Seq[TaskDescription]] = { - synchronized { - SparkEnv.set(sc.env) - // Mark each slave as alive and remember its hostname - for (o <- offers) { - // DEBUG Code - Utils.checkHostPort(o.hostPort) - - executorIdToHostPort(o.executorId) = o.hostPort - if (! executorsByHostPort.contains(o.hostPort)) { - executorsByHostPort(o.hostPort) = new HashSet[String]() - } - - hostPortsAlive += o.hostPort - hostToAliveHostPorts.getOrElseUpdate(Utils.parseHostPort(o.hostPort)._1, new HashSet[String]).add(o.hostPort) - executorGained(o.executorId, o.hostPort) - } - // Build a list of tasks to assign to each slave - val tasks = offers.map(o => new ArrayBuffer[TaskDescription](o.cores)) - // merge availableCpus into nodeToAvailableCpus block ? - val availableCpus = offers.map(o => o.cores).toArray - val nodeToAvailableCpus = { - val map = new HashMap[String, Int]() - for (offer <- offers) { - val hostPort = offer.hostPort - val cores = offer.cores - // DEBUG code - Utils.checkHostPort(hostPort) - - val host = Utils.parseHostPort(hostPort)._1 - - map.put(host, map.getOrElse(host, 0) + cores) - } - - map - } - var launchedTask = false - val sortedTaskSetQueue = rootPool.getSortedTaskSetQueue() - for (manager <- sortedTaskSetQueue) - { - logInfo("parentName:%s,name:%s,runningTasks:%s".format(manager.parent.name, manager.name, manager.runningTasks)) - } - for (manager <- sortedTaskSetQueue) { - - // Split offers based on node local, rack local and off-rack tasks. - val processLocalOffers = new HashMap[String, ArrayBuffer[Int]]() - val nodeLocalOffers = new HashMap[String, ArrayBuffer[Int]]() - val rackLocalOffers = new HashMap[String, ArrayBuffer[Int]]() - val otherOffers = new HashMap[String, ArrayBuffer[Int]]() - - for (i <- 0 until offers.size) { - val hostPort = offers(i).hostPort - // DEBUG code - Utils.checkHostPort(hostPort) - - val numProcessLocalTasks = math.max(0, math.min(manager.numPendingTasksForHostPort(hostPort), availableCpus(i))) - if (numProcessLocalTasks > 0){ - val list = processLocalOffers.getOrElseUpdate(hostPort, new ArrayBuffer[Int]) - for (j <- 0 until numProcessLocalTasks) list += i - } - - val host = Utils.parseHostPort(hostPort)._1 - val numNodeLocalTasks = math.max(0, - // Remove process local tasks (which are also host local btw !) from this - math.min(manager.numPendingTasksForHost(hostPort) - numProcessLocalTasks, nodeToAvailableCpus(host))) - if (numNodeLocalTasks > 0){ - val list = nodeLocalOffers.getOrElseUpdate(host, new ArrayBuffer[Int]) - for (j <- 0 until numNodeLocalTasks) list += i - } - - val numRackLocalTasks = math.max(0, - // Remove node local tasks (which are also rack local btw !) from this - math.min(manager.numRackLocalPendingTasksForHost(hostPort) - numProcessLocalTasks - numNodeLocalTasks, nodeToAvailableCpus(host))) - if (numRackLocalTasks > 0){ - val list = rackLocalOffers.getOrElseUpdate(host, new ArrayBuffer[Int]) - for (j <- 0 until numRackLocalTasks) list += i - } - if (numNodeLocalTasks <= 0 && numRackLocalTasks <= 0){ - // add to others list - spread even this across cluster. - val list = otherOffers.getOrElseUpdate(host, new ArrayBuffer[Int]) - list += i - } - } - - val offersPriorityList = new ArrayBuffer[Int]( - processLocalOffers.size + nodeLocalOffers.size + rackLocalOffers.size + otherOffers.size) - - // First process local, then host local, then rack, then others - - // numNodeLocalOffers contains count of both process local and host offers. - val numNodeLocalOffers = { - val processLocalPriorityList = ClusterScheduler.prioritizeContainers(processLocalOffers) - offersPriorityList ++= processLocalPriorityList - - val nodeLocalPriorityList = ClusterScheduler.prioritizeContainers(nodeLocalOffers) - offersPriorityList ++= nodeLocalPriorityList - - processLocalPriorityList.size + nodeLocalPriorityList.size - } - val numRackLocalOffers = { - val rackLocalPriorityList = ClusterScheduler.prioritizeContainers(rackLocalOffers) - offersPriorityList ++= rackLocalPriorityList - rackLocalPriorityList.size - } - offersPriorityList ++= ClusterScheduler.prioritizeContainers(otherOffers) - - var lastLoop = false - val lastLoopIndex = TASK_SCHEDULING_AGGRESSION match { - case TaskLocality.NODE_LOCAL => numNodeLocalOffers - case TaskLocality.RACK_LOCAL => numRackLocalOffers + numNodeLocalOffers - case TaskLocality.ANY => offersPriorityList.size - } - - do { - launchedTask = false - var loopCount = 0 - for (i <- offersPriorityList) { - val execId = offers(i).executorId - val hostPort = offers(i).hostPort - - // If last loop and within the lastLoopIndex, expand scope - else use null (which will use default/existing) - val overrideLocality = if (lastLoop && loopCount < lastLoopIndex) TASK_SCHEDULING_AGGRESSION else null - - // If last loop, override waiting for host locality - we scheduled all local tasks already and there might be more available ... - loopCount += 1 - - manager.slaveOffer(execId, hostPort, availableCpus(i), overrideLocality) match { - case Some(task) => - tasks(i) += task - val tid = task.taskId - taskIdToTaskSetId(tid) = manager.taskSet.id - taskSetTaskIds(manager.taskSet.id) += tid - taskIdToExecutorId(tid) = execId - activeExecutorIds += execId - executorsByHostPort(hostPort) += execId - availableCpus(i) -= 1 - launchedTask = true - - case None => {} - } - } - // Loop once more - when lastLoop = true, then we try to schedule task on all nodes irrespective of - // data locality (we still go in order of priority : but that would not change anything since - // if data local tasks had been available, we would have scheduled them already) - if (lastLoop) { - // prevent more looping - launchedTask = false - } else if (!lastLoop && !launchedTask) { - // Do this only if TASK_SCHEDULING_AGGRESSION != NODE_LOCAL - if (TASK_SCHEDULING_AGGRESSION != TaskLocality.NODE_LOCAL) { - // fudge launchedTask to ensure we loop once more - launchedTask = true - // dont loop anymore - lastLoop = true - } - } - } while (launchedTask) - } - - if (tasks.size > 0) { - hasLaunchedTask = true - } - return tasks - } - } - - def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { - var taskSetToUpdate: Option[TaskSetManager] = None - var failedExecutor: Option[String] = None - var taskFailed = false - synchronized { - try { - if (state == TaskState.LOST && taskIdToExecutorId.contains(tid)) { - // We lost this entire executor, so remember that it's gone - val execId = taskIdToExecutorId(tid) - if (activeExecutorIds.contains(execId)) { - removeExecutor(execId) - failedExecutor = Some(execId) - } - } - taskIdToTaskSetId.get(tid) match { - case Some(taskSetId) => - if (activeTaskSets.contains(taskSetId)) { - taskSetToUpdate = Some(activeTaskSets(taskSetId)) - } - if (TaskState.isFinished(state)) { - taskIdToTaskSetId.remove(tid) - if (taskSetTaskIds.contains(taskSetId)) { - taskSetTaskIds(taskSetId) -= tid - } - taskIdToExecutorId.remove(tid) - } - if (state == TaskState.FAILED) { - taskFailed = true - } - case None => - logInfo("Ignoring update from TID " + tid + " because its task set is gone") - } - } catch { - case e: Exception => logError("Exception in statusUpdate", e) - } - } - // Update the task set and DAGScheduler without holding a lock on this, since that can deadlock - if (taskSetToUpdate != None) { - taskSetToUpdate.get.statusUpdate(tid, state, serializedData) - } - if (failedExecutor != None) { - listener.executorLost(failedExecutor.get) - backend.reviveOffers() - } - if (taskFailed) { - - // Also revive offers if a task had failed for some reason other than host lost - backend.reviveOffers() - } - } - - def error(message: String) { - synchronized { - if (activeTaskSets.size > 0) { - // Have each task set throw a SparkException with the error - for ((taskSetId, manager) <- activeTaskSets) { - try { - manager.error(message) - } catch { - case e: Exception => logError("Exception in error callback", e) - } - } - } else { - // No task sets are active but we still got an error. Just exit since this - // must mean the error is during registration. - // It might be good to do something smarter here in the future. - logError("Exiting due to error from cluster scheduler: " + message) - System.exit(1) - } - } - } - - override def stop() { - if (backend != null) { - backend.stop() - } - if (jarServer != null) { - jarServer.stop() - } - - // sleeping for an arbitrary 5 seconds : to ensure that messages are sent out. - // TODO: Do something better ! - Thread.sleep(5000L) - } - - override def defaultParallelism() = backend.defaultParallelism() - - - // Check for speculatable tasks in all our active jobs. - def checkSpeculatableTasks() { - var shouldRevive = false - synchronized { - shouldRevive = rootPool.checkSpeculatableTasks() - } - if (shouldRevive) { - backend.reviveOffers() - } - } - - // Check for pending tasks in all our active jobs. - def hasPendingTasks(): Boolean = { - synchronized { - rootPool.hasPendingTasks() - } - } - - def executorLost(executorId: String, reason: ExecutorLossReason) { - var failedExecutor: Option[String] = None - - synchronized { - if (activeExecutorIds.contains(executorId)) { - val hostPort = executorIdToHostPort(executorId) - logError("Lost executor %s on %s: %s".format(executorId, hostPort, reason)) - removeExecutor(executorId) - failedExecutor = Some(executorId) - } else { - // We may get multiple executorLost() calls with different loss reasons. For example, one - // may be triggered by a dropped connection from the slave while another may be a report - // of executor termination from Mesos. We produce log messages for both so we eventually - // report the termination reason. - logError("Lost an executor " + executorId + " (already removed): " + reason) - } - } - // Call listener.executorLost without holding the lock on this to prevent deadlock - if (failedExecutor != None) { - listener.executorLost(failedExecutor.get) - backend.reviveOffers() - } - } - - /** Remove an executor from all our data structures and mark it as lost */ - private def removeExecutor(executorId: String) { - activeExecutorIds -= executorId - val hostPort = executorIdToHostPort(executorId) - if (hostPortsAlive.contains(hostPort)) { - // DEBUG Code - Utils.checkHostPort(hostPort) - - hostPortsAlive -= hostPort - hostToAliveHostPorts.getOrElseUpdate(Utils.parseHostPort(hostPort)._1, new HashSet[String]).remove(hostPort) - } - - val execs = executorsByHostPort.getOrElse(hostPort, new HashSet) - execs -= executorId - if (execs.isEmpty) { - executorsByHostPort -= hostPort - } - executorIdToHostPort -= executorId - rootPool.executorLost(executorId, hostPort) - } - - def executorGained(execId: String, hostPort: String) { - listener.executorGained(execId, hostPort) - } - - def getExecutorsAliveOnHost(host: String): Option[Set[String]] = { - Utils.checkHost(host) - - val retval = hostToAliveHostPorts.get(host) - if (retval.isDefined) { - return Some(retval.get.toSet) - } - - None - } - - def isExecutorAliveOnHostPort(hostPort: String): Boolean = { - // Even if hostPort is a host, it does not matter - it is just a specific check. - // But we do have to ensure that only hostPort get into hostPortsAlive ! - // So no check against Utils.checkHostPort - hostPortsAlive.contains(hostPort) - } - - // By default, rack is unknown - def getRackForHost(value: String): Option[String] = None - - // By default, (cached) hosts for rack is unknown - def getCachedHostsForRack(rack: String): Option[Set[String]] = None -} - - -object ClusterScheduler { - - // Used to 'spray' available containers across the available set to ensure too many containers on same host - // are not used up. Used in yarn mode and in task scheduling (when there are multiple containers available - // to execute a task) - // For example: yarn can returns more containers than we would have requested under ANY, this method - // prioritizes how to use the allocated containers. - // flatten the map such that the array buffer entries are spread out across the returned value. - // given <host, list[container]> == <h1, [c1 .. c5]>, <h2, [c1 .. c3]>, <h3, [c1, c2]>, <h4, c1>, <h5, c1>, i - // the return value would be something like : h1c1, h2c1, h3c1, h4c1, h5c1, h1c2, h2c2, h3c2, h1c3, h2c3, h1c4, h1c5 - // We then 'use' the containers in this order (consuming only the top K from this list where - // K = number to be user). This is to ensure that if we have multiple eligible allocations, - // they dont end up allocating all containers on a small number of hosts - increasing probability of - // multiple container failure when a host goes down. - // Note, there is bias for keys with higher number of entries in value to be picked first (by design) - // Also note that invocation of this method is expected to have containers of same 'type' - // (host-local, rack-local, off-rack) and not across types : so that reordering is simply better from - // the available list - everything else being same. - // That is, we we first consume data local, then rack local and finally off rack nodes. So the - // prioritization from this method applies to within each category - def prioritizeContainers[K, T] (map: HashMap[K, ArrayBuffer[T]]): List[T] = { - val _keyList = new ArrayBuffer[K](map.size) - _keyList ++= map.keys - - // order keyList based on population of value in map - val keyList = _keyList.sortWith( - (left, right) => map.get(left).getOrElse(Set()).size > map.get(right).getOrElse(Set()).size - ) - - val retval = new ArrayBuffer[T](keyList.size * 2) - var index = 0 - var found = true - - while (found){ - found = false - for (key <- keyList) { - val containerList: ArrayBuffer[T] = map.get(key).getOrElse(null) - assert(containerList != null) - // Get the index'th entry for this host - if present - if (index < containerList.size){ - retval += containerList.apply(index) - found = true - } - } - index += 1 - } - - retval.toList - } -} diff --git a/core/src/main/scala/spark/scheduler/cluster/ClusterTaskSetManager.scala b/core/src/main/scala/spark/scheduler/cluster/ClusterTaskSetManager.scala deleted file mode 100644 index 9d618cf531..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/ClusterTaskSetManager.scala +++ /dev/null @@ -1,748 +0,0 @@ -package spark.scheduler.cluster - -import java.util.{HashMap => JHashMap, NoSuchElementException, Arrays} - -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap -import scala.collection.mutable.HashSet -import scala.math.max -import scala.math.min - -import spark._ -import spark.scheduler._ -import spark.TaskState.TaskState -import java.nio.ByteBuffer - -private[spark] object TaskLocality extends Enumeration with Logging { - - type TaskLocality = Value - - // process local is expected to be used ONLY within tasksetmanager for now. - val PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL, ANY = Value - - def isAllowed(constraint: TaskLocality, condition: TaskLocality): Boolean = { - - // Must not be the constraint. - assert (constraint != TaskLocality.PROCESS_LOCAL) - - constraint match { - case TaskLocality.NODE_LOCAL => condition == TaskLocality.NODE_LOCAL - case TaskLocality.RACK_LOCAL => condition == TaskLocality.NODE_LOCAL || condition == TaskLocality.RACK_LOCAL - // For anything else, allow - case _ => true - } - } - - def parse(str: String): TaskLocality = { - // better way to do this ? - try { - val retval = TaskLocality.withName(str) - // Must not specify PROCESS_LOCAL ! - assert (retval != TaskLocality.PROCESS_LOCAL) - - retval - } catch { - case nEx: NoSuchElementException => { - logWarning("Invalid task locality specified '" + str + "', defaulting to NODE_LOCAL"); - // default to preserve earlier behavior - NODE_LOCAL - } - } - } -} - -/** - * Schedules the tasks within a single TaskSet in the ClusterScheduler. - */ -private[spark] class ClusterTaskSetManager( - sched: ClusterScheduler, - val taskSet: TaskSet) - extends TaskSetManager - with Logging { - - // Maximum time to wait to run a task in a preferred location (in ms) - val LOCALITY_WAIT = System.getProperty("spark.locality.wait", "3000").toLong - - // CPUs to request per task - val CPUS_PER_TASK = System.getProperty("spark.task.cpus", "1").toDouble - - // Maximum times a task is allowed to fail before failing the job - val MAX_TASK_FAILURES = 4 - - // Quantile of tasks at which to start speculation - val SPECULATION_QUANTILE = System.getProperty("spark.speculation.quantile", "0.75").toDouble - val SPECULATION_MULTIPLIER = System.getProperty("spark.speculation.multiplier", "1.5").toDouble - - // Serializer for closures and tasks. - val ser = SparkEnv.get.closureSerializer.newInstance() - - val tasks = taskSet.tasks - val numTasks = tasks.length - val copiesRunning = new Array[Int](numTasks) - val finished = new Array[Boolean](numTasks) - val numFailures = new Array[Int](numTasks) - val taskAttempts = Array.fill[List[TaskInfo]](numTasks)(Nil) - var tasksFinished = 0 - - var weight = 1 - var minShare = 0 - var runningTasks = 0 - var priority = taskSet.priority - var stageId = taskSet.stageId - var name = "TaskSet_"+taskSet.stageId.toString - var parent:Schedulable = null - - // Last time when we launched a preferred task (for delay scheduling) - var lastPreferredLaunchTime = System.currentTimeMillis - - // List of pending tasks for each node (process local to container). These collections are actually - // treated as stacks, in which new tasks are added to the end of the - // ArrayBuffer and removed from the end. This makes it faster to detect - // tasks that repeatedly fail because whenever a task failed, it is put - // back at the head of the stack. They are also only cleaned up lazily; - // when a task is launched, it remains in all the pending lists except - // the one that it was launched from, but gets removed from them later. - private val pendingTasksForHostPort = new HashMap[String, ArrayBuffer[Int]] - - // List of pending tasks for each node. - // Essentially, similar to pendingTasksForHostPort, except at host level - private val pendingTasksForHost = new HashMap[String, ArrayBuffer[Int]] - - // List of pending tasks for each node based on rack locality. - // Essentially, similar to pendingTasksForHost, except at rack level - private val pendingRackLocalTasksForHost = new HashMap[String, ArrayBuffer[Int]] - - // List containing pending tasks with no locality preferences - val pendingTasksWithNoPrefs = new ArrayBuffer[Int] - - // List containing all pending tasks (also used as a stack, as above) - val allPendingTasks = new ArrayBuffer[Int] - - // Tasks that can be speculated. Since these will be a small fraction of total - // tasks, we'll just hold them in a HashSet. - val speculatableTasks = new HashSet[Int] - - // Task index, start and finish time for each task attempt (indexed by task ID) - val taskInfos = new HashMap[Long, TaskInfo] - - // Did the job fail? - var failed = false - var causeOfFailure = "" - - // How frequently to reprint duplicate exceptions in full, in milliseconds - val EXCEPTION_PRINT_INTERVAL = - System.getProperty("spark.logging.exceptionPrintInterval", "10000").toLong - // Map of recent exceptions (identified by string representation and - // top stack frame) to duplicate count (how many times the same - // exception has appeared) and time the full exception was - // printed. This should ideally be an LRU map that can drop old - // exceptions automatically. - val recentExceptions = HashMap[String, (Int, Long)]() - - // Figure out the current map output tracker generation and set it on all tasks - val generation = sched.mapOutputTracker.getGeneration - logDebug("Generation for " + taskSet.id + ": " + generation) - for (t <- tasks) { - t.generation = generation - } - - // Add all our tasks to the pending lists. We do this in reverse order - // of task index so that tasks with low indices get launched first. - for (i <- (0 until numTasks).reverse) { - addPendingTask(i) - } - - // Note that it follows the hierarchy. - // if we search for NODE_LOCAL, the output will include PROCESS_LOCAL and - // if we search for RACK_LOCAL, it will include PROCESS_LOCAL & NODE_LOCAL - private def findPreferredLocations(_taskPreferredLocations: Seq[String], scheduler: ClusterScheduler, - taskLocality: TaskLocality.TaskLocality): HashSet[String] = { - - if (TaskLocality.PROCESS_LOCAL == taskLocality) { - // straight forward comparison ! Special case it. - val retval = new HashSet[String]() - scheduler.synchronized { - for (location <- _taskPreferredLocations) { - if (scheduler.isExecutorAliveOnHostPort(location)) { - retval += location - } - } - } - - return retval - } - - val taskPreferredLocations = - if (TaskLocality.NODE_LOCAL == taskLocality) { - _taskPreferredLocations - } else { - assert (TaskLocality.RACK_LOCAL == taskLocality) - // Expand set to include all 'seen' rack local hosts. - // This works since container allocation/management happens within master - so any rack locality information is updated in msater. - // Best case effort, and maybe sort of kludge for now ... rework it later ? - val hosts = new HashSet[String] - _taskPreferredLocations.foreach(h => { - val rackOpt = scheduler.getRackForHost(h) - if (rackOpt.isDefined) { - val hostsOpt = scheduler.getCachedHostsForRack(rackOpt.get) - if (hostsOpt.isDefined) { - hosts ++= hostsOpt.get - } - } - - // Ensure that irrespective of what scheduler says, host is always added ! - hosts += h - }) - - hosts - } - - val retval = new HashSet[String] - scheduler.synchronized { - for (prefLocation <- taskPreferredLocations) { - val aliveLocationsOpt = scheduler.getExecutorsAliveOnHost(Utils.parseHostPort(prefLocation)._1) - if (aliveLocationsOpt.isDefined) { - retval ++= aliveLocationsOpt.get - } - } - } - - retval - } - - // Add a task to all the pending-task lists that it should be on. - private def addPendingTask(index: Int) { - // We can infer hostLocalLocations from rackLocalLocations by joining it against tasks(index).preferredLocations (with appropriate - // hostPort <-> host conversion). But not doing it for simplicity sake. If this becomes a performance issue, modify it. - val processLocalLocations = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.PROCESS_LOCAL) - val hostLocalLocations = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.NODE_LOCAL) - val rackLocalLocations = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.RACK_LOCAL) - - if (rackLocalLocations.size == 0) { - // Current impl ensures this. - assert (processLocalLocations.size == 0) - assert (hostLocalLocations.size == 0) - pendingTasksWithNoPrefs += index - } else { - - // process local locality - for (hostPort <- processLocalLocations) { - // DEBUG Code - Utils.checkHostPort(hostPort) - - val hostPortList = pendingTasksForHostPort.getOrElseUpdate(hostPort, ArrayBuffer()) - hostPortList += index - } - - // host locality (includes process local) - for (hostPort <- hostLocalLocations) { - // DEBUG Code - Utils.checkHostPort(hostPort) - - val host = Utils.parseHostPort(hostPort)._1 - val hostList = pendingTasksForHost.getOrElseUpdate(host, ArrayBuffer()) - hostList += index - } - - // rack locality (includes process local and host local) - for (rackLocalHostPort <- rackLocalLocations) { - // DEBUG Code - Utils.checkHostPort(rackLocalHostPort) - - val rackLocalHost = Utils.parseHostPort(rackLocalHostPort)._1 - val list = pendingRackLocalTasksForHost.getOrElseUpdate(rackLocalHost, ArrayBuffer()) - list += index - } - } - - allPendingTasks += index - } - - // Return the pending tasks list for a given host port (process local), or an empty list if - // there is no map entry for that host - private def getPendingTasksForHostPort(hostPort: String): ArrayBuffer[Int] = { - // DEBUG Code - Utils.checkHostPort(hostPort) - pendingTasksForHostPort.getOrElse(hostPort, ArrayBuffer()) - } - - // Return the pending tasks list for a given host, or an empty list if - // there is no map entry for that host - private def getPendingTasksForHost(hostPort: String): ArrayBuffer[Int] = { - val host = Utils.parseHostPort(hostPort)._1 - pendingTasksForHost.getOrElse(host, ArrayBuffer()) - } - - // Return the pending tasks (rack level) list for a given host, or an empty list if - // there is no map entry for that host - private def getRackLocalPendingTasksForHost(hostPort: String): ArrayBuffer[Int] = { - val host = Utils.parseHostPort(hostPort)._1 - pendingRackLocalTasksForHost.getOrElse(host, ArrayBuffer()) - } - - // Number of pending tasks for a given host Port (which would be process local) - def numPendingTasksForHostPort(hostPort: String): Int = { - getPendingTasksForHostPort(hostPort).count( index => copiesRunning(index) == 0 && !finished(index) ) - } - - // Number of pending tasks for a given host (which would be data local) - def numPendingTasksForHost(hostPort: String): Int = { - getPendingTasksForHost(hostPort).count( index => copiesRunning(index) == 0 && !finished(index) ) - } - - // Number of pending rack local tasks for a given host - def numRackLocalPendingTasksForHost(hostPort: String): Int = { - getRackLocalPendingTasksForHost(hostPort).count( index => copiesRunning(index) == 0 && !finished(index) ) - } - - - // Dequeue a pending task from the given list and return its index. - // Return None if the list is empty. - // This method also cleans up any tasks in the list that have already - // been launched, since we want that to happen lazily. - private def findTaskFromList(list: ArrayBuffer[Int]): Option[Int] = { - while (!list.isEmpty) { - val index = list.last - list.trimEnd(1) - if (copiesRunning(index) == 0 && !finished(index)) { - return Some(index) - } - } - return None - } - - // Return a speculative task for a given host if any are available. The task should not have an - // attempt running on this host, in case the host is slow. In addition, if locality is set, the - // task must have a preference for this host/rack/no preferred locations at all. - private def findSpeculativeTask(hostPort: String, locality: TaskLocality.TaskLocality): Option[Int] = { - - assert (TaskLocality.isAllowed(locality, TaskLocality.NODE_LOCAL)) - speculatableTasks.retain(index => !finished(index)) // Remove finished tasks from set - - if (speculatableTasks.size > 0) { - val localTask = speculatableTasks.find { - index => - val locations = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.NODE_LOCAL) - val attemptLocs = taskAttempts(index).map(_.hostPort) - (locations.size == 0 || locations.contains(hostPort)) && !attemptLocs.contains(hostPort) - } - - if (localTask != None) { - speculatableTasks -= localTask.get - return localTask - } - - // check for rack locality - if (TaskLocality.isAllowed(locality, TaskLocality.RACK_LOCAL)) { - val rackTask = speculatableTasks.find { - index => - val locations = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.RACK_LOCAL) - val attemptLocs = taskAttempts(index).map(_.hostPort) - locations.contains(hostPort) && !attemptLocs.contains(hostPort) - } - - if (rackTask != None) { - speculatableTasks -= rackTask.get - return rackTask - } - } - - // Any task ... - if (TaskLocality.isAllowed(locality, TaskLocality.ANY)) { - // Check for attemptLocs also ? - val nonLocalTask = speculatableTasks.find(i => !taskAttempts(i).map(_.hostPort).contains(hostPort)) - if (nonLocalTask != None) { - speculatableTasks -= nonLocalTask.get - return nonLocalTask - } - } - } - return None - } - - // Dequeue a pending task for a given node and return its index. - // If localOnly is set to false, allow non-local tasks as well. - private def findTask(hostPort: String, locality: TaskLocality.TaskLocality): Option[Int] = { - val processLocalTask = findTaskFromList(getPendingTasksForHostPort(hostPort)) - if (processLocalTask != None) { - return processLocalTask - } - - val localTask = findTaskFromList(getPendingTasksForHost(hostPort)) - if (localTask != None) { - return localTask - } - - if (TaskLocality.isAllowed(locality, TaskLocality.RACK_LOCAL)) { - val rackLocalTask = findTaskFromList(getRackLocalPendingTasksForHost(hostPort)) - if (rackLocalTask != None) { - return rackLocalTask - } - } - - // Look for no pref tasks AFTER rack local tasks - this has side effect that we will get to failed tasks later rather than sooner. - // TODO: That code path needs to be revisited (adding to no prefs list when host:port goes down). - val noPrefTask = findTaskFromList(pendingTasksWithNoPrefs) - if (noPrefTask != None) { - return noPrefTask - } - - if (TaskLocality.isAllowed(locality, TaskLocality.ANY)) { - val nonLocalTask = findTaskFromList(allPendingTasks) - if (nonLocalTask != None) { - return nonLocalTask - } - } - - // Finally, if all else has failed, find a speculative task - return findSpeculativeTask(hostPort, locality) - } - - private def isProcessLocalLocation(task: Task[_], hostPort: String): Boolean = { - Utils.checkHostPort(hostPort) - - val locs = task.preferredLocations - - locs.contains(hostPort) - } - - private def isHostLocalLocation(task: Task[_], hostPort: String): Boolean = { - val locs = task.preferredLocations - - // If no preference, consider it as host local - if (locs.isEmpty) return true - - val host = Utils.parseHostPort(hostPort)._1 - locs.find(h => Utils.parseHostPort(h)._1 == host).isDefined - } - - // Does a host count as a rack local preferred location for a task? (assumes host is NOT preferred location). - // This is true if either the task has preferred locations and this host is one, or it has - // no preferred locations (in which we still count the launch as preferred). - private def isRackLocalLocation(task: Task[_], hostPort: String): Boolean = { - - val locs = task.preferredLocations - - val preferredRacks = new HashSet[String]() - for (preferredHost <- locs) { - val rack = sched.getRackForHost(preferredHost) - if (None != rack) preferredRacks += rack.get - } - - if (preferredRacks.isEmpty) return false - - val hostRack = sched.getRackForHost(hostPort) - - return None != hostRack && preferredRacks.contains(hostRack.get) - } - - // Respond to an offer of a single slave from the scheduler by finding a task - def slaveOffer(execId: String, hostPort: String, availableCpus: Double, overrideLocality: TaskLocality.TaskLocality = null): Option[TaskDescription] = { - - if (tasksFinished < numTasks && availableCpus >= CPUS_PER_TASK) { - // If explicitly specified, use that - val locality = if (overrideLocality != null) overrideLocality else { - // expand only if we have waited for more than LOCALITY_WAIT for a host local task ... - val time = System.currentTimeMillis - if (time - lastPreferredLaunchTime < LOCALITY_WAIT) TaskLocality.NODE_LOCAL else TaskLocality.ANY - } - - findTask(hostPort, locality) match { - case Some(index) => { - // Found a task; do some bookkeeping and return a Mesos task for it - val task = tasks(index) - val taskId = sched.newTaskId() - // Figure out whether this should count as a preferred launch - val taskLocality = - if (isProcessLocalLocation(task, hostPort)) TaskLocality.PROCESS_LOCAL - else if (isHostLocalLocation(task, hostPort)) TaskLocality.NODE_LOCAL - else if (isRackLocalLocation(task, hostPort)) TaskLocality.RACK_LOCAL - else TaskLocality.ANY - val prefStr = taskLocality.toString - logInfo("Starting task %s:%d as TID %s on slave %s: %s (%s)".format( - taskSet.id, index, taskId, execId, hostPort, prefStr)) - // Do various bookkeeping - copiesRunning(index) += 1 - val time = System.currentTimeMillis - val info = new TaskInfo(taskId, index, time, execId, hostPort, taskLocality) - taskInfos(taskId) = info - taskAttempts(index) = info :: taskAttempts(index) - if (taskLocality == TaskLocality.PROCESS_LOCAL || taskLocality == TaskLocality.NODE_LOCAL) { - lastPreferredLaunchTime = time - } - // Serialize and return the task - val startTime = System.currentTimeMillis - val serializedTask = Task.serializeWithDependencies( - task, sched.sc.addedFiles, sched.sc.addedJars, ser) - val timeTaken = System.currentTimeMillis - startTime - increaseRunningTasks(1) - logInfo("Serialized task %s:%d as %d bytes in %d ms".format( - taskSet.id, index, serializedTask.limit, timeTaken)) - val taskName = "task %s:%d".format(taskSet.id, index) - return Some(new TaskDescription(taskId, execId, taskName, serializedTask)) - } - case _ => - } - } - return None - } - - def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) { - state match { - case TaskState.FINISHED => - taskFinished(tid, state, serializedData) - case TaskState.LOST => - taskLost(tid, state, serializedData) - case TaskState.FAILED => - taskLost(tid, state, serializedData) - case TaskState.KILLED => - taskLost(tid, state, serializedData) - case _ => - } - } - - def taskFinished(tid: Long, state: TaskState, serializedData: ByteBuffer) { - val info = taskInfos(tid) - if (info.failed) { - // We might get two task-lost messages for the same task in coarse-grained Mesos mode, - // or even from Mesos itself when acks get delayed. - return - } - val index = info.index - info.markSuccessful() - decreaseRunningTasks(1) - if (!finished(index)) { - tasksFinished += 1 - logInfo("Finished TID %s in %d ms (progress: %d/%d)".format( - tid, info.duration, tasksFinished, numTasks)) - // Deserialize task result and pass it to the scheduler - try { - val result = ser.deserialize[TaskResult[_]](serializedData) - result.metrics.resultSize = serializedData.limit() - sched.listener.taskEnded(tasks(index), Success, result.value, result.accumUpdates, info, result.metrics) - } catch { - case cnf: ClassNotFoundException => - val loader = Thread.currentThread().getContextClassLoader - throw new SparkException("ClassNotFound with classloader: " + loader, cnf) - case ex : Throwable => throw ex - } - // Mark finished and stop if we've finished all the tasks - finished(index) = true - if (tasksFinished == numTasks) { - sched.taskSetFinished(this) - } - } else { - logInfo("Ignoring task-finished event for TID " + tid + - " because task " + index + " is already finished") - } - } - - def taskLost(tid: Long, state: TaskState, serializedData: ByteBuffer) { - val info = taskInfos(tid) - if (info.failed) { - // We might get two task-lost messages for the same task in coarse-grained Mesos mode, - // or even from Mesos itself when acks get delayed. - return - } - val index = info.index - info.markFailed() - decreaseRunningTasks(1) - if (!finished(index)) { - logInfo("Lost TID %s (task %s:%d)".format(tid, taskSet.id, index)) - copiesRunning(index) -= 1 - // Check if the problem is a map output fetch failure. In that case, this - // task will never succeed on any node, so tell the scheduler about it. - if (serializedData != null && serializedData.limit() > 0) { - val reason = ser.deserialize[TaskEndReason](serializedData, getClass.getClassLoader) - reason match { - case fetchFailed: FetchFailed => - logInfo("Loss was due to fetch failure from " + fetchFailed.bmAddress) - sched.listener.taskEnded(tasks(index), fetchFailed, null, null, info, null) - finished(index) = true - tasksFinished += 1 - sched.taskSetFinished(this) - decreaseRunningTasks(runningTasks) - return - - case taskResultTooBig: TaskResultTooBigFailure => - logInfo("Loss was due to task %s result exceeding Akka frame size; " + - "aborting job".format(tid)) - abort("Task %s result exceeded Akka frame size".format(tid)) - return - - case ef: ExceptionFailure => - sched.listener.taskEnded(tasks(index), ef, null, null, info, ef.metrics.getOrElse(null)) - val key = ef.description - val now = System.currentTimeMillis - val (printFull, dupCount) = { - if (recentExceptions.contains(key)) { - val (dupCount, printTime) = recentExceptions(key) - if (now - printTime > EXCEPTION_PRINT_INTERVAL) { - recentExceptions(key) = (0, now) - (true, 0) - } else { - recentExceptions(key) = (dupCount + 1, printTime) - (false, dupCount + 1) - } - } else { - recentExceptions(key) = (0, now) - (true, 0) - } - } - if (printFull) { - val locs = ef.stackTrace.map(loc => "\tat %s".format(loc.toString)) - logInfo("Loss was due to %s\n%s\n%s".format( - ef.className, ef.description, locs.mkString("\n"))) - } else { - logInfo("Loss was due to %s [duplicate %d]".format(ef.description, dupCount)) - } - - case _ => {} - } - } - // On non-fetch failures, re-enqueue the task as pending for a max number of retries - addPendingTask(index) - // Count failed attempts only on FAILED and LOST state (not on KILLED) - if (state == TaskState.FAILED || state == TaskState.LOST) { - numFailures(index) += 1 - if (numFailures(index) > MAX_TASK_FAILURES) { - logError("Task %s:%d failed more than %d times; aborting job".format( - taskSet.id, index, MAX_TASK_FAILURES)) - abort("Task %s:%d failed more than %d times".format(taskSet.id, index, MAX_TASK_FAILURES)) - } - } - } else { - logInfo("Ignoring task-lost event for TID " + tid + - " because task " + index + " is already finished") - } - } - - def error(message: String) { - // Save the error message - abort("Error: " + message) - } - - def abort(message: String) { - failed = true - causeOfFailure = message - // TODO: Kill running tasks if we were not terminated due to a Mesos error - sched.listener.taskSetFailed(taskSet, message) - decreaseRunningTasks(runningTasks) - sched.taskSetFinished(this) - } - - override def increaseRunningTasks(taskNum: Int) { - runningTasks += taskNum - if (parent != null) { - parent.increaseRunningTasks(taskNum) - } - } - - override def decreaseRunningTasks(taskNum: Int) { - runningTasks -= taskNum - if (parent != null) { - parent.decreaseRunningTasks(taskNum) - } - } - - //TODO: for now we just find Pool not TaskSetManager, we can extend this function in future if needed - override def getSchedulableByName(name: String): Schedulable = { - return null - } - - override def addSchedulable(schedulable:Schedulable) { - //nothing - } - - override def removeSchedulable(schedulable:Schedulable) { - //nothing - } - - override def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] = { - var sortedTaskSetQueue = new ArrayBuffer[TaskSetManager] - sortedTaskSetQueue += this - return sortedTaskSetQueue - } - - override def executorLost(execId: String, hostPort: String) { - logInfo("Re-queueing tasks for " + execId + " from TaskSet " + taskSet.id) - - // If some task has preferred locations only on hostname, and there are no more executors there, - // put it in the no-prefs list to avoid the wait from delay scheduling - - // host local tasks - should we push this to rack local or no pref list ? For now, preserving behavior and moving to - // no prefs list. Note, this was done due to impliations related to 'waiting' for data local tasks, etc. - // Note: NOT checking process local list - since host local list is super set of that. We need to ad to no prefs only if - // there is no host local node for the task (not if there is no process local node for the task) - for (index <- getPendingTasksForHost(Utils.parseHostPort(hostPort)._1)) { - // val newLocs = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.RACK_LOCAL) - val newLocs = findPreferredLocations(tasks(index).preferredLocations, sched, TaskLocality.NODE_LOCAL) - if (newLocs.isEmpty) { - pendingTasksWithNoPrefs += index - } - } - - // Re-enqueue any tasks that ran on the failed executor if this is a shuffle map stage - if (tasks(0).isInstanceOf[ShuffleMapTask]) { - for ((tid, info) <- taskInfos if info.executorId == execId) { - val index = taskInfos(tid).index - if (finished(index)) { - finished(index) = false - copiesRunning(index) -= 1 - tasksFinished -= 1 - addPendingTask(index) - // Tell the DAGScheduler that this task was resubmitted so that it doesn't think our - // stage finishes when a total of tasks.size tasks finish. - sched.listener.taskEnded(tasks(index), Resubmitted, null, null, info, null) - } - } - } - // Also re-enqueue any tasks that were running on the node - for ((tid, info) <- taskInfos if info.running && info.executorId == execId) { - taskLost(tid, TaskState.KILLED, null) - } - } - - /** - * Check for tasks to be speculated and return true if there are any. This is called periodically - * by the ClusterScheduler. - * - * TODO: To make this scale to large jobs, we need to maintain a list of running tasks, so that - * we don't scan the whole task set. It might also help to make this sorted by launch time. - */ - override def checkSpeculatableTasks(): Boolean = { - // Can't speculate if we only have one task, or if all tasks have finished. - if (numTasks == 1 || tasksFinished == numTasks) { - return false - } - var foundTasks = false - val minFinishedForSpeculation = (SPECULATION_QUANTILE * numTasks).floor.toInt - logDebug("Checking for speculative tasks: minFinished = " + minFinishedForSpeculation) - if (tasksFinished >= minFinishedForSpeculation) { - val time = System.currentTimeMillis() - val durations = taskInfos.values.filter(_.successful).map(_.duration).toArray - Arrays.sort(durations) - val medianDuration = durations(min((0.5 * numTasks).round.toInt, durations.size - 1)) - val threshold = max(SPECULATION_MULTIPLIER * medianDuration, 100) - // TODO: Threshold should also look at standard deviation of task durations and have a lower - // bound based on that. - logDebug("Task length threshold for speculation: " + threshold) - for ((tid, info) <- taskInfos) { - val index = info.index - if (!finished(index) && copiesRunning(index) == 1 && info.timeRunning(time) > threshold && - !speculatableTasks.contains(index)) { - logInfo( - "Marking task %s:%d (on %s) as speculatable because it ran more than %.0f ms".format( - taskSet.id, index, info.hostPort, threshold)) - speculatableTasks += index - foundTasks = true - } - } - } - return foundTasks - } - - override def hasPendingTasks(): Boolean = { - numTasks > 0 && tasksFinished < numTasks - } -} diff --git a/core/src/main/scala/spark/scheduler/cluster/ExecutorLossReason.scala b/core/src/main/scala/spark/scheduler/cluster/ExecutorLossReason.scala deleted file mode 100644 index 8bf838209f..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/ExecutorLossReason.scala +++ /dev/null @@ -1,21 +0,0 @@ -package spark.scheduler.cluster - -import spark.executor.ExecutorExitCode - -/** - * Represents an explanation for a executor or whole slave failing or exiting. - */ -private[spark] -class ExecutorLossReason(val message: String) { - override def toString: String = message -} - -private[spark] -case class ExecutorExited(val exitCode: Int) - extends ExecutorLossReason(ExecutorExitCode.explainExitCode(exitCode)) { -} - -private[spark] -case class SlaveLost(_message: String = "Slave lost") - extends ExecutorLossReason(_message) { -} diff --git a/core/src/main/scala/spark/scheduler/cluster/Schedulable.scala b/core/src/main/scala/spark/scheduler/cluster/Schedulable.scala deleted file mode 100644 index 2dd9c0564f..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/Schedulable.scala +++ /dev/null @@ -1,27 +0,0 @@ -package spark.scheduler.cluster - -import scala.collection.mutable.ArrayBuffer - -/** - * An interface for schedulable entities. - * there are two type of Schedulable entities(Pools and TaskSetManagers) - */ -private[spark] trait Schedulable { - var parent: Schedulable - def weight: Int - def minShare: Int - def runningTasks: Int - def priority: Int - def stageId: Int - def name: String - - def increaseRunningTasks(taskNum: Int): Unit - def decreaseRunningTasks(taskNum: Int): Unit - def addSchedulable(schedulable: Schedulable): Unit - def removeSchedulable(schedulable: Schedulable): Unit - def getSchedulableByName(name: String): Schedulable - def executorLost(executorId: String, host: String): Unit - def checkSpeculatableTasks(): Boolean - def getSortedTaskSetQueue(): ArrayBuffer[TaskSetManager] - def hasPendingTasks(): Boolean -} diff --git a/core/src/main/scala/spark/scheduler/cluster/SchedulableBuilder.scala b/core/src/main/scala/spark/scheduler/cluster/SchedulableBuilder.scala deleted file mode 100644 index 18cc15c2a5..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/SchedulableBuilder.scala +++ /dev/null @@ -1,115 +0,0 @@ -package spark.scheduler.cluster - -import java.io.{File, FileInputStream, FileOutputStream} - -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap -import scala.collection.mutable.HashSet -import scala.util.control.Breaks._ -import scala.xml._ - -import spark.Logging -import spark.scheduler.cluster.SchedulingMode.SchedulingMode - -import java.util.Properties - -/** - * An interface to build Schedulable tree - * buildPools: build the tree nodes(pools) - * addTaskSetManager: build the leaf nodes(TaskSetManagers) - */ -private[spark] trait SchedulableBuilder { - def buildPools() - def addTaskSetManager(manager: Schedulable, properties: Properties) -} - -private[spark] class FIFOSchedulableBuilder(val rootPool: Pool) extends SchedulableBuilder with Logging { - - override def buildPools() { - //nothing - } - - override def addTaskSetManager(manager: Schedulable, properties: Properties) { - rootPool.addSchedulable(manager) - } -} - -private[spark] class FairSchedulableBuilder(val rootPool: Pool) extends SchedulableBuilder with Logging { - - val schedulerAllocFile = System.getProperty("spark.fairscheduler.allocation.file","unspecified") - val FAIR_SCHEDULER_PROPERTIES = "spark.scheduler.cluster.fair.pool" - val DEFAULT_POOL_NAME = "default" - val MINIMUM_SHARES_PROPERTY = "minShare" - val SCHEDULING_MODE_PROPERTY = "schedulingMode" - val WEIGHT_PROPERTY = "weight" - val POOL_NAME_PROPERTY = "@name" - val POOLS_PROPERTY = "pool" - val DEFAULT_SCHEDULING_MODE = SchedulingMode.FIFO - val DEFAULT_MINIMUM_SHARE = 2 - val DEFAULT_WEIGHT = 1 - - override def buildPools() { - val file = new File(schedulerAllocFile) - if (file.exists()) { - val xml = XML.loadFile(file) - for (poolNode <- (xml \\ POOLS_PROPERTY)) { - - val poolName = (poolNode \ POOL_NAME_PROPERTY).text - var schedulingMode = DEFAULT_SCHEDULING_MODE - var minShare = DEFAULT_MINIMUM_SHARE - var weight = DEFAULT_WEIGHT - - val xmlSchedulingMode = (poolNode \ SCHEDULING_MODE_PROPERTY).text - if (xmlSchedulingMode != "") { - try { - schedulingMode = SchedulingMode.withName(xmlSchedulingMode) - } catch { - case e: Exception => logInfo("Error xml schedulingMode, using default schedulingMode") - } - } - - val xmlMinShare = (poolNode \ MINIMUM_SHARES_PROPERTY).text - if (xmlMinShare != "") { - minShare = xmlMinShare.toInt - } - - val xmlWeight = (poolNode \ WEIGHT_PROPERTY).text - if (xmlWeight != "") { - weight = xmlWeight.toInt - } - - val pool = new Pool(poolName, schedulingMode, minShare, weight) - rootPool.addSchedulable(pool) - logInfo("Create new pool with name:%s,schedulingMode:%s,minShare:%d,weight:%d".format( - poolName, schedulingMode, minShare, weight)) - } - } - - //finally create "default" pool - if (rootPool.getSchedulableByName(DEFAULT_POOL_NAME) == null) { - val pool = new Pool(DEFAULT_POOL_NAME, DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT) - rootPool.addSchedulable(pool) - logInfo("Create default pool with name:%s,schedulingMode:%s,minShare:%d,weight:%d".format( - DEFAULT_POOL_NAME, DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT)) - } - } - - override def addTaskSetManager(manager: Schedulable, properties: Properties) { - var poolName = DEFAULT_POOL_NAME - var parentPool = rootPool.getSchedulableByName(poolName) - if (properties != null) { - poolName = properties.getProperty(FAIR_SCHEDULER_PROPERTIES, DEFAULT_POOL_NAME) - parentPool = rootPool.getSchedulableByName(poolName) - if (parentPool == null) { - //we will create a new pool that user has configured in app instead of being defined in xml file - parentPool = new Pool(poolName,DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT) - rootPool.addSchedulable(parentPool) - logInfo("Create pool with name:%s,schedulingMode:%s,minShare:%d,weight:%d".format( - poolName, DEFAULT_SCHEDULING_MODE, DEFAULT_MINIMUM_SHARE, DEFAULT_WEIGHT)) - } - } - parentPool.addSchedulable(manager) - logInfo("Added task set " + manager.name + " tasks to pool "+poolName) - } -} diff --git a/core/src/main/scala/spark/scheduler/cluster/SchedulerBackend.scala b/core/src/main/scala/spark/scheduler/cluster/SchedulerBackend.scala deleted file mode 100644 index 8844057a5c..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/SchedulerBackend.scala +++ /dev/null @@ -1,20 +0,0 @@ -package spark.scheduler.cluster - -import spark.{SparkContext, Utils} - -/** - * A backend interface for cluster scheduling systems that allows plugging in different ones under - * ClusterScheduler. We assume a Mesos-like model where the application gets resource offers as - * machines become available and can launch tasks on them. - */ -private[spark] trait SchedulerBackend { - def start(): Unit - def stop(): Unit - def reviveOffers(): Unit - def defaultParallelism(): Int - - // Memory used by each executor (in megabytes) - protected val executorMemory: Int = SparkContext.executorMemoryRequested - - // TODO: Probably want to add a killTask too -} diff --git a/core/src/main/scala/spark/scheduler/cluster/SchedulingMode.scala b/core/src/main/scala/spark/scheduler/cluster/SchedulingMode.scala deleted file mode 100644 index 3ff3cd5fe4..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/SchedulingMode.scala +++ /dev/null @@ -1,7 +0,0 @@ -package spark.scheduler.cluster - -object SchedulingMode extends Enumeration { - - type SchedulingMode = Value - val FAIR,FIFO = Value -} diff --git a/core/src/main/scala/spark/scheduler/cluster/StandaloneClusterMessage.scala b/core/src/main/scala/spark/scheduler/cluster/StandaloneClusterMessage.scala deleted file mode 100644 index 3335294844..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/StandaloneClusterMessage.scala +++ /dev/null @@ -1,45 +0,0 @@ -package spark.scheduler.cluster - -import spark.TaskState.TaskState -import java.nio.ByteBuffer -import spark.util.SerializableBuffer -import spark.Utils - -private[spark] sealed trait StandaloneClusterMessage extends Serializable - -// Driver to executors -private[spark] -case class LaunchTask(task: TaskDescription) extends StandaloneClusterMessage - -private[spark] -case class RegisteredExecutor(sparkProperties: Seq[(String, String)]) - extends StandaloneClusterMessage - -private[spark] -case class RegisterExecutorFailed(message: String) extends StandaloneClusterMessage - -// Executors to driver -private[spark] -case class RegisterExecutor(executorId: String, hostPort: String, cores: Int) - extends StandaloneClusterMessage { - Utils.checkHostPort(hostPort, "Expected host port") -} - -private[spark] -case class StatusUpdate(executorId: String, taskId: Long, state: TaskState, data: SerializableBuffer) - extends StandaloneClusterMessage - -private[spark] -object StatusUpdate { - /** Alternate factory method that takes a ByteBuffer directly for the data field */ - def apply(executorId: String, taskId: Long, state: TaskState, data: ByteBuffer): StatusUpdate = { - StatusUpdate(executorId, taskId, state, new SerializableBuffer(data)) - } -} - -// Internal messages in driver -private[spark] case object ReviveOffers extends StandaloneClusterMessage -private[spark] case object StopDriver extends StandaloneClusterMessage - -private[spark] case class RemoveExecutor(executorId: String, reason: String) - extends StandaloneClusterMessage diff --git a/core/src/main/scala/spark/scheduler/cluster/TaskDescription.scala b/core/src/main/scala/spark/scheduler/cluster/TaskDescription.scala deleted file mode 100644 index b41e951be9..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/TaskDescription.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark.scheduler.cluster - -import java.nio.ByteBuffer -import spark.util.SerializableBuffer - -private[spark] class TaskDescription( - val taskId: Long, - val executorId: String, - val name: String, - _serializedTask: ByteBuffer) - extends Serializable { - - // Because ByteBuffers are not serializable, wrap the task in a SerializableBuffer - private val buffer = new SerializableBuffer(_serializedTask) - - def serializedTask: ByteBuffer = buffer.value -} diff --git a/core/src/main/scala/spark/scheduler/cluster/TaskInfo.scala b/core/src/main/scala/spark/scheduler/cluster/TaskInfo.scala deleted file mode 100644 index 718f26bfbd..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/TaskInfo.scala +++ /dev/null @@ -1,46 +0,0 @@ -package spark.scheduler.cluster - -import spark.Utils - -/** - * Information about a running task attempt inside a TaskSet. - */ -private[spark] -class TaskInfo( - val taskId: Long, - val index: Int, - val launchTime: Long, - val executorId: String, - val hostPort: String, - val taskLocality: TaskLocality.TaskLocality) { - - Utils.checkHostPort(hostPort, "Expected hostport") - - var finishTime: Long = 0 - var failed = false - - def markSuccessful(time: Long = System.currentTimeMillis) { - finishTime = time - } - - def markFailed(time: Long = System.currentTimeMillis) { - finishTime = time - failed = true - } - - def finished: Boolean = finishTime != 0 - - def successful: Boolean = finished && !failed - - def running: Boolean = !finished - - def duration: Long = { - if (!finished) { - throw new UnsupportedOperationException("duration() called on unfinished tasks") - } else { - finishTime - launchTime - } - } - - def timeRunning(currentTime: Long): Long = currentTime - launchTime -} diff --git a/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala b/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala deleted file mode 100644 index b4dd75d90f..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark.scheduler.cluster - -import scala.collection.mutable.ArrayBuffer -import spark.scheduler._ -import spark.TaskState.TaskState -import java.nio.ByteBuffer - -private[spark] trait TaskSetManager extends Schedulable { - def taskSet: TaskSet - def slaveOffer(execId: String, hostPort: String, availableCpus: Double, - overrideLocality: TaskLocality.TaskLocality = null): Option[TaskDescription] - def numPendingTasksForHostPort(hostPort: String): Int - def numRackLocalPendingTasksForHost(hostPort :String): Int - def numPendingTasksForHost(hostPort: String): Int - def statusUpdate(tid: Long, state: TaskState, serializedData: ByteBuffer) - def error(message: String) -} diff --git a/core/src/main/scala/spark/scheduler/cluster/WorkerOffer.scala b/core/src/main/scala/spark/scheduler/cluster/WorkerOffer.scala deleted file mode 100644 index c47824315c..0000000000 --- a/core/src/main/scala/spark/scheduler/cluster/WorkerOffer.scala +++ /dev/null @@ -1,8 +0,0 @@ -package spark.scheduler.cluster - -/** - * Represents free resources available on an executor. - */ -private[spark] -class WorkerOffer(val executorId: String, val hostPort: String, val cores: Int) { -} diff --git a/core/src/main/scala/spark/storage/BlockException.scala b/core/src/main/scala/spark/storage/BlockException.scala deleted file mode 100644 index f275d476df..0000000000 --- a/core/src/main/scala/spark/storage/BlockException.scala +++ /dev/null @@ -1,5 +0,0 @@ -package spark.storage - -private[spark] -case class BlockException(blockId: String, message: String) extends Exception(message) - diff --git a/core/src/main/scala/spark/storage/BlockFetchTracker.scala b/core/src/main/scala/spark/storage/BlockFetchTracker.scala deleted file mode 100644 index 0718156b1b..0000000000 --- a/core/src/main/scala/spark/storage/BlockFetchTracker.scala +++ /dev/null @@ -1,10 +0,0 @@ -package spark.storage - -private[spark] trait BlockFetchTracker { - def totalBlocks : Int - def numLocalBlocks: Int - def numRemoteBlocks: Int - def remoteFetchTime : Long - def fetchWaitTime: Long - def remoteBytesRead : Long -} diff --git a/core/src/main/scala/spark/storage/BlockManagerMessages.scala b/core/src/main/scala/spark/storage/BlockManagerMessages.scala deleted file mode 100644 index 0010726c8d..0000000000 --- a/core/src/main/scala/spark/storage/BlockManagerMessages.scala +++ /dev/null @@ -1,106 +0,0 @@ -package spark.storage - -import java.io.{Externalizable, ObjectInput, ObjectOutput} - -import akka.actor.ActorRef - - -////////////////////////////////////////////////////////////////////////////////// -// Messages from the master to slaves. -////////////////////////////////////////////////////////////////////////////////// -private[spark] -sealed trait ToBlockManagerSlave - -// Remove a block from the slaves that have it. This can only be used to remove -// blocks that the master knows about. -private[spark] -case class RemoveBlock(blockId: String) extends ToBlockManagerSlave - -// Remove all blocks belonging to a specific RDD. -private[spark] case class RemoveRdd(rddId: Int) extends ToBlockManagerSlave - - -////////////////////////////////////////////////////////////////////////////////// -// Messages from slaves to the master. -////////////////////////////////////////////////////////////////////////////////// -private[spark] -sealed trait ToBlockManagerMaster - -private[spark] -case class RegisterBlockManager( - blockManagerId: BlockManagerId, - maxMemSize: Long, - sender: ActorRef) - extends ToBlockManagerMaster - -private[spark] -case class HeartBeat(blockManagerId: BlockManagerId) extends ToBlockManagerMaster - -private[spark] -class UpdateBlockInfo( - var blockManagerId: BlockManagerId, - var blockId: String, - var storageLevel: StorageLevel, - var memSize: Long, - var diskSize: Long) - extends ToBlockManagerMaster - with Externalizable { - - def this() = this(null, null, null, 0, 0) // For deserialization only - - override def writeExternal(out: ObjectOutput) { - blockManagerId.writeExternal(out) - out.writeUTF(blockId) - storageLevel.writeExternal(out) - out.writeLong(memSize) - out.writeLong(diskSize) - } - - override def readExternal(in: ObjectInput) { - blockManagerId = BlockManagerId(in) - blockId = in.readUTF() - storageLevel = StorageLevel(in) - memSize = in.readLong() - diskSize = in.readLong() - } -} - -private[spark] -object UpdateBlockInfo { - def apply(blockManagerId: BlockManagerId, - blockId: String, - storageLevel: StorageLevel, - memSize: Long, - diskSize: Long): UpdateBlockInfo = { - new UpdateBlockInfo(blockManagerId, blockId, storageLevel, memSize, diskSize) - } - - // For pattern-matching - def unapply(h: UpdateBlockInfo): Option[(BlockManagerId, String, StorageLevel, Long, Long)] = { - Some((h.blockManagerId, h.blockId, h.storageLevel, h.memSize, h.diskSize)) - } -} - -private[spark] -case class GetLocations(blockId: String) extends ToBlockManagerMaster - -private[spark] -case class GetLocationsMultipleBlockIds(blockIds: Array[String]) extends ToBlockManagerMaster - -private[spark] -case class GetPeers(blockManagerId: BlockManagerId, size: Int) extends ToBlockManagerMaster - -private[spark] -case class RemoveExecutor(execId: String) extends ToBlockManagerMaster - -private[spark] -case object StopBlockManagerMaster extends ToBlockManagerMaster - -private[spark] -case object GetMemoryStatus extends ToBlockManagerMaster - -private[spark] -case object ExpireDeadHosts extends ToBlockManagerMaster - -private[spark] -case object GetStorageStatus extends ToBlockManagerMaster diff --git a/core/src/main/scala/spark/storage/BlockManagerSlaveActor.scala b/core/src/main/scala/spark/storage/BlockManagerSlaveActor.scala deleted file mode 100644 index b264d1deb5..0000000000 --- a/core/src/main/scala/spark/storage/BlockManagerSlaveActor.scala +++ /dev/null @@ -1,22 +0,0 @@ -package spark.storage - -import akka.actor.Actor - -import spark.{Logging, SparkException, Utils} - - -/** - * An actor to take commands from the master to execute options. For example, - * this is used to remove blocks from the slave's BlockManager. - */ -class BlockManagerSlaveActor(blockManager: BlockManager) extends Actor { - override def receive = { - - case RemoveBlock(blockId) => - blockManager.removeBlock(blockId) - - case RemoveRdd(rddId) => - val numBlocksRemoved = blockManager.removeRdd(rddId) - sender ! numBlocksRemoved - } -} diff --git a/core/src/main/scala/spark/storage/PutResult.scala b/core/src/main/scala/spark/storage/PutResult.scala deleted file mode 100644 index 76f236057b..0000000000 --- a/core/src/main/scala/spark/storage/PutResult.scala +++ /dev/null @@ -1,9 +0,0 @@ -package spark.storage - -import java.nio.ByteBuffer - -/** - * Result of adding a block into a BlockStore. Contains its estimated size, and possibly the - * values put if the caller asked for them to be returned (e.g. for chaining replication) - */ -private[spark] case class PutResult(size: Long, data: Either[Iterator[_], ByteBuffer]) diff --git a/core/src/main/scala/spark/ui/Page.scala b/core/src/main/scala/spark/ui/Page.scala deleted file mode 100644 index ed8f91842c..0000000000 --- a/core/src/main/scala/spark/ui/Page.scala +++ /dev/null @@ -1,3 +0,0 @@ -package spark.ui - -private[spark] object Page extends Enumeration { val Storage, Jobs, Environment = Value }
\ No newline at end of file diff --git a/core/src/main/scala/spark/ui/SparkUI.scala b/core/src/main/scala/spark/ui/SparkUI.scala deleted file mode 100644 index 874e5ba8ec..0000000000 --- a/core/src/main/scala/spark/ui/SparkUI.scala +++ /dev/null @@ -1,62 +0,0 @@ -package spark.ui - -import javax.servlet.http.HttpServletRequest - -import org.eclipse.jetty.server.{Handler, Server} - -import spark.{Logging, SparkContext, Utils} -import spark.ui.env.EnvironmentUI -import spark.ui.storage.BlockManagerUI -import spark.ui.jobs.JobProgressUI -import spark.ui.JettyUtils._ - -/** Top level user interface for Spark */ -private[spark] class SparkUI(sc: SparkContext) extends Logging { - val host = Utils.localHostName() - val port = Option(System.getProperty("spark.ui.port")).getOrElse(SparkUI.DEFAULT_PORT).toInt - var boundPort: Option[Int] = None - var server: Option[Server] = None - - val handlers = Seq[(String, Handler)]( - ("/static", createStaticHandler(SparkUI.STATIC_RESOURCE_DIR)), - ("/", createRedirectHandler("/stages")) - ) - val storage = new BlockManagerUI(sc) - val jobs = new JobProgressUI(sc) - val env = new EnvironmentUI(sc) - val allHandlers = storage.getHandlers ++ jobs.getHandlers ++ env.getHandlers ++ handlers - - /** Bind the HTTP server which backs this web interface */ - def bind() { - try { - val (srv, usedPort) = JettyUtils.startJettyServer("0.0.0.0", port, allHandlers) - logInfo("Started Spark Web UI at http://%s:%d".format(host, usedPort)) - server = Some(srv) - boundPort = Some(usedPort) - } catch { - case e: Exception => - logError("Failed to create Spark JettyUtils", e) - System.exit(1) - } - } - - /** Initialize all components of the server */ - def start() { - // NOTE: This is decoupled from bind() because of the following dependency cycle: - // DAGScheduler() requires that the port of this server is known - // This server must register all handlers, including JobProgressUI, before binding - // JobProgressUI registers a listener with SparkContext, which requires sc to initialize - jobs.start() - } - - def stop() { - server.foreach(_.stop()) - } - - private[spark] def appUIAddress = "http://" + host + ":" + boundPort.getOrElse("-1") -} - -private[spark] object SparkUI { - val DEFAULT_PORT = "33000" - val STATIC_RESOURCE_DIR = "spark/ui/static" -} diff --git a/core/src/main/scala/spark/ui/UIUtils.scala b/core/src/main/scala/spark/ui/UIUtils.scala deleted file mode 100644 index 36d9c47245..0000000000 --- a/core/src/main/scala/spark/ui/UIUtils.scala +++ /dev/null @@ -1,118 +0,0 @@ -package spark.ui - -import scala.xml.Node - -import spark.SparkContext - -/** Utility functions for generating XML pages with spark content. */ -private[spark] object UIUtils { - import Page._ - - /** Returns a spark page with correctly formatted headers */ - def headerSparkPage(content: => Seq[Node], sc: SparkContext, title: String, page: Page.Value) - : Seq[Node] = { - val storage = page match { - case Storage => <li class="active"><a href="/storage">Storage</a></li> - case _ => <li><a href="/storage">Storage</a></li> - } - val jobs = page match { - case Jobs => <li class="active"><a href="/stages">Jobs</a></li> - case _ => <li><a href="/stages">Jobs</a></li> - } - val environment = page match { - case Environment => <li class="active"><a href="/environment">Environment</a></li> - case _ => <li><a href="/environment">Environment</a></li> - } - - <html> - <head> - <meta http-equiv="Content-type" content="text/html; charset=utf-8" /> - <link rel="stylesheet" href="/static/bootstrap.min.css" type="text/css" /> - <link rel="stylesheet" href="/static/webui.css" type="text/css" /> - <link rel="stylesheet" href="/static/bootstrap-responsive.min.css" type="text/css" /> - <script src="/static/sorttable.js"></script> - <title>{title}</title> - <style type="text/css"> - table.sortable thead {{ cursor: pointer; }} - </style> - </head> - <body> - <div class="container"> - - <div class="row"> - <div class="span12"> - <div class="navbar"> - <div class="navbar-inner"> - <div class="container"> - <div class="brand"><img src="/static/spark-logo-77x50px-hd.png" /></div> - <ul class="nav"> - {storage} - {jobs} - {environment} - </ul> - <ul id="infolist"> - <li>Application: <strong>{sc.appName}</strong></li> - <li>Master: <strong>{sc.master}</strong></li> - <li>Executors: <strong>{sc.getExecutorStorageStatus.size}</strong></li> - </ul> - </div> - </div> - </div> - </div> - </div> - - <div class="row" style="padding-top: 5px;"> - <div class="span12"> - <h1 style="vertical-align: bottom; display: inline-block;"> - {title} - </h1> - </div> - </div> - <hr/> - {content} - </div> - </body> - </html> - } - - /** Returns a page with the spark css/js and a simple format. Used for scheduler UI. */ - def basicSparkPage(content: => Seq[Node], title: String): Seq[Node] = { - <html> - <head> - <meta http-equiv="Content-type" content="text/html; charset=utf-8" /> - <link rel="stylesheet" href="/static/bootstrap.min.css" type="text/css" /> - <link rel="stylesheet" href="/static/bootstrap-responsive.min.css" type="text/css" /> - <script src="/static/sorttable.js"></script> - <title>{title}</title> - <style type="text/css"> - table.sortable thead {{ cursor: pointer; }} - </style> - </head> - <body> - <div class="container"> - <div class="row"> - <div class="span2"> - <img src="/static/spark_logo.png" /> - </div> - <div class="span10"> - <h1 style="vertical-align: bottom; margin-top: 40px; display: inline-block;"> - {title} - </h1> - </div> - </div> - {content} - </div> - </body> - </html> - } - - /** Returns an HTML table constructed by generating a row for each object in a sequence. */ - def listingTable[T](headers: Seq[String], makeRow: T => Seq[Node], rows: Seq[T]): Seq[Node] = { - <table class="table table-bordered table-striped table-condensed sortable"> - <thead>{headers.map(h => <th>{h}</th>)}</thead> - <tbody> - {rows.map(r => makeRow(r))} - </tbody> - </table> - } -}
\ No newline at end of file diff --git a/core/src/main/scala/spark/ui/UIWorkloadGenerator.scala b/core/src/main/scala/spark/ui/UIWorkloadGenerator.scala deleted file mode 100644 index 8bbc6ce88e..0000000000 --- a/core/src/main/scala/spark/ui/UIWorkloadGenerator.scala +++ /dev/null @@ -1,71 +0,0 @@ -package spark.ui - -import scala.util.Random - -import spark.SparkContext -import spark.SparkContext._ - -/** - * Continuously generates jobs that expose various features of the WebUI (internal testing tool). - * - * Usage: ./run spark.ui.UIWorkloadGenerator [master] - */ -private[spark] object UIWorkloadGenerator { - val NUM_PARTITIONS = 100 - val INTER_JOB_WAIT_MS = 500 - - def main(args: Array[String]) { - val master = args(0) - val appName = "Spark UI Tester" - val sc = new SparkContext(master, appName) - - // NOTE: Right now there is no easy way for us to show spark.job.annotation for a given phase, - // but we pass it here anyways since it will be useful once we do. - def setName(s: String) = { - sc.addLocalProperties("spark.job.annotation", s) - } - val baseData = sc.makeRDD(1 to NUM_PARTITIONS * 10, NUM_PARTITIONS) - def nextFloat() = (new Random()).nextFloat() - - val jobs = Seq[(String, () => Long)]( - ("Count", baseData.count), - ("Cache and Count", baseData.map(x => x).cache.count), - ("Single Shuffle", baseData.map(x => (x % 10, x)).reduceByKey(_ + _).count), - ("Entirely failed phase", baseData.map(x => throw new Exception).count), - ("Partially failed phase", { - baseData.map{x => - val probFailure = (4.0 / NUM_PARTITIONS) - if (nextFloat() < probFailure) { - throw new Exception("This is a task failure") - } - 1 - }.count - }), - ("Partially failed phase (longer tasks)", { - baseData.map{x => - val probFailure = (4.0 / NUM_PARTITIONS) - if (nextFloat() < probFailure) { - Thread.sleep(100) - throw new Exception("This is a task failure") - } - 1 - }.count - }), - ("Job with delays", baseData.map(x => Thread.sleep(100)).count) - ) - - while (true) { - for ((desc, job) <- jobs) { - try { - setName(desc) - job() - println("Job funished: " + desc) - } catch { - case e: Exception => - println("Job Failed: " + desc) - } - Thread.sleep(INTER_JOB_WAIT_MS) - } - } - } -} diff --git a/core/src/main/scala/spark/ui/env/EnvironmentUI.scala b/core/src/main/scala/spark/ui/env/EnvironmentUI.scala deleted file mode 100644 index 6b8b9f05bb..0000000000 --- a/core/src/main/scala/spark/ui/env/EnvironmentUI.scala +++ /dev/null @@ -1,69 +0,0 @@ -package spark.ui.env - -import javax.servlet.http.HttpServletRequest - -import org.eclipse.jetty.server.Handler - -import scala.collection.JavaConversions._ -import scala.util.Properties - -import spark.ui.JettyUtils._ -import spark.ui.UIUtils.headerSparkPage -import spark.ui.Page.Environment -import spark.SparkContext -import spark.ui.UIUtils - -import scala.xml.Node - -private[spark] class EnvironmentUI(sc: SparkContext) { - - def getHandlers = Seq[(String, Handler)]( - ("/environment", (request: HttpServletRequest) => envDetails(request)) - ) - - def envDetails(request: HttpServletRequest): Seq[Node] = { - val jvmInformation = Seq( - ("Java Version", "%s (%s)".format(Properties.javaVersion, Properties.javaVendor)), - ("Java Home", Properties.javaHome), - ("Scala Version", Properties.versionString), - ("Scala Home", Properties.scalaHome) - ) - def jvmRow(kv: (String, String)) = <tr><td>{kv._1}</td><td>{kv._2}</td></tr> - def jvmTable = UIUtils.listingTable(Seq("Name", "Value"), jvmRow, jvmInformation) - - val properties = System.getProperties.iterator.toSeq - val classPathProperty = properties - .filter{case (k, v) => k.contains("java.class.path")} - .headOption - .getOrElse("", "") - val sparkProperties = properties.filter(_._1.startsWith("spark")) - val otherProperties = properties.diff(sparkProperties :+ classPathProperty) - - val propertyHeaders = Seq("Name", "Value") - def propertyRow(kv: (String, String)) = <tr><td>{kv._1}</td><td>{kv._2}</td></tr> - val sparkPropertyTable = UIUtils.listingTable(propertyHeaders, propertyRow, sparkProperties) - val otherPropertyTable = UIUtils.listingTable(propertyHeaders, propertyRow, otherProperties) - - val classPathEntries = classPathProperty._2 - .split(System.getProperty("path.separator", ":")) - .filterNot(e => e.isEmpty) - .map(e => (e, "System Classpath")) - val addedJars = sc.addedJars.iterator.toSeq.map{case (path, time) => (path, "Added By User")} - val addedFiles = sc.addedFiles.iterator.toSeq.map{case (path, time) => (path, "Added By User")} - val classPath = addedJars ++ addedFiles ++ classPathEntries - - val classPathHeaders = Seq("Resource", "Source") - def classPathRow(data: (String, String)) = <tr><td>{data._1}</td><td>{data._2}</td></tr> - val classPathTable = UIUtils.listingTable(classPathHeaders, classPathRow, classPath) - - val content = - <span> - <h2>Runtime Information</h2> {jvmTable} - <h2>Spark Properties</h2> {sparkPropertyTable} - <h2>System Properties</h2> {otherPropertyTable} - <h2>Classpath Entries</h2> {classPathTable} - </span> - - headerSparkPage(content, sc, "Environment", Environment) - } -} diff --git a/core/src/main/scala/spark/ui/jobs/IndexPage.scala b/core/src/main/scala/spark/ui/jobs/IndexPage.scala deleted file mode 100644 index 7907ab3bc7..0000000000 --- a/core/src/main/scala/spark/ui/jobs/IndexPage.scala +++ /dev/null @@ -1,112 +0,0 @@ -package spark.ui.jobs - -import java.util.Date - -import javax.servlet.http.HttpServletRequest - -import scala.Some -import scala.xml.{NodeSeq, Node} - -import spark.scheduler.Stage -import spark.ui.UIUtils._ -import spark.ui.Page._ -import spark.storage.StorageLevel - -/** Page showing list of all ongoing and recently finished stages */ -private[spark] class IndexPage(parent: JobProgressUI) { - def listener = parent.listener - val dateFmt = parent.dateFmt - - def render(request: HttpServletRequest): Seq[Node] = { - val activeStages = listener.activeStages.toSeq - val completedStages = listener.completedStages.reverse.toSeq - val failedStages = listener.failedStages.reverse.toSeq - - /** Special table which merges two header cells. */ - def stageTable[T](makeRow: T => Seq[Node], rows: Seq[T]): Seq[Node] = { - <table class="table table-bordered table-striped table-condensed sortable"> - <thead> - <th>Stage Id</th> - <th>Origin</th> - <th>Submitted</th> - <th>Duration</th> - <th colspan="2">Tasks: Complete/Total</th> - <th>Shuffle Activity</th> - <th>Stored RDD</th> - </thead> - <tbody> - {rows.map(r => makeRow(r))} - </tbody> - </table> - } - - val activeStageTable: NodeSeq = stageTable(stageRow, activeStages) - val completedStageTable = stageTable(stageRow, completedStages) - val failedStageTable: NodeSeq = stageTable(stageRow, failedStages) - - val content = <h2>Active Stages</h2> ++ activeStageTable ++ - <h2>Completed Stages</h2> ++ completedStageTable ++ - <h2>Failed Stages</h2> ++ failedStageTable - - headerSparkPage(content, parent.sc, "Spark Stages", Jobs) - } - - def getElapsedTime(submitted: Option[Long], completed: Long): String = { - submitted match { - case Some(t) => parent.formatDuration(completed - t) - case _ => "Unknown" - } - } - - def makeProgressBar(completed: Int, total: Int): Seq[Node] = { - val width=130 - val height=15 - val completeWidth = (completed.toDouble / total) * width - - <svg width={width.toString} height={height.toString}> - <rect width={width.toString} height={height.toString} - fill="white" stroke="rgb(51,51,51)" stroke-width="1" /> - <rect width={completeWidth.toString} height={height.toString} - fill="rgb(0,136,204)" stroke="black" stroke-width="1" /> - </svg> - } - - - def stageRow(s: Stage): Seq[Node] = { - val submissionTime = s.submissionTime match { - case Some(t) => dateFmt.format(new Date(t)) - case None => "Unknown" - } - val (read, write) = (listener.hasShuffleRead(s.id), listener.hasShuffleWrite(s.id)) - val shuffleInfo = (read, write) match { - case (true, true) => "Read/Write" - case (true, false) => "Read" - case (false, true) => "Write" - case _ => "" - } - val completedTasks = listener.stageToTasksComplete.getOrElse(s.id, 0) - val totalTasks = s.numPartitions - - <tr> - <td>{s.id}</td> - <td><a href={"/stages/stage?id=%s".format(s.id)}>{s.origin}</a></td> - <td>{submissionTime}</td> - <td>{getElapsedTime(s.submissionTime, - s.completionTime.getOrElse(System.currentTimeMillis()))}</td> - <td class="progress-cell">{makeProgressBar(completedTasks, totalTasks)}</td> - <td style="border-left: 0; text-align: center;">{completedTasks} / {totalTasks} - {listener.stageToTasksFailed.getOrElse(s.id, 0) match { - case f if f > 0 => "(%s failed)".format(f) - case _ => - }} - </td> - <td>{shuffleInfo}</td> - <td>{if (s.rdd.getStorageLevel != StorageLevel.NONE) { - <a href={"/storage/rdd?id=%s".format(s.rdd.id)}> - {Option(s.rdd.name).getOrElse(s.rdd.id)} - </a> - }} - </td> - </tr> - } -} diff --git a/core/src/main/scala/spark/ui/jobs/JobProgressUI.scala b/core/src/main/scala/spark/ui/jobs/JobProgressUI.scala deleted file mode 100644 index c5d2aa5d60..0000000000 --- a/core/src/main/scala/spark/ui/jobs/JobProgressUI.scala +++ /dev/null @@ -1,127 +0,0 @@ -package spark.ui.jobs - -import scala.concurrent.duration._ - -import java.text.SimpleDateFormat - -import javax.servlet.http.HttpServletRequest - -import org.eclipse.jetty.server.Handler - -import scala.Seq -import scala.collection.mutable.{HashSet, ListBuffer, HashMap, ArrayBuffer} - -import spark.ui.JettyUtils._ -import spark.{ExceptionFailure, SparkContext, Success, Utils} -import spark.scheduler._ -import spark.scheduler.cluster.TaskInfo -import spark.executor.TaskMetrics -import collection.mutable - -/** Web UI showing progress status of all jobs in the given SparkContext. */ -private[spark] class JobProgressUI(val sc: SparkContext) { - private var _listener: Option[JobProgressListener] = None - def listener = _listener.get - val dateFmt = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss") - - private val indexPage = new IndexPage(this) - private val stagePage = new StagePage(this) - - def start() { - _listener = Some(new JobProgressListener) - sc.addSparkListener(listener) - } - - def formatDuration(ms: Long) = Utils.msDurationToString(ms) - - def getHandlers = Seq[(String, Handler)]( - ("/stages/stage", (request: HttpServletRequest) => stagePage.render(request)), - ("/stages", (request: HttpServletRequest) => indexPage.render(request)) - ) -} - -private[spark] class JobProgressListener extends SparkListener { - // How many stages to remember - val RETAINED_STAGES = System.getProperty("spark.ui.retained_stages", "1000").toInt - - val activeStages = HashSet[Stage]() - val completedStages = ListBuffer[Stage]() - val failedStages = ListBuffer[Stage]() - - val stageToTasksComplete = HashMap[Int, Int]() - val stageToTasksFailed = HashMap[Int, Int]() - val stageToTaskInfos = - HashMap[Int, ArrayBuffer[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]]() - - override def onJobStart(jobStart: SparkListenerJobStart) {} - - override def onStageCompleted(stageCompleted: StageCompleted) = { - val stage = stageCompleted.stageInfo.stage - activeStages -= stage - completedStages += stage - trimIfNecessary(completedStages) - } - - /** If stages is too large, remove and garbage collect old stages */ - def trimIfNecessary(stages: ListBuffer[Stage]) { - if (stages.size > RETAINED_STAGES) { - val toRemove = RETAINED_STAGES / 10 - stages.takeRight(toRemove).foreach( s => { - stageToTaskInfos.remove(s.id) - }) - stages.trimEnd(toRemove) - } - } - - override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) = - activeStages += stageSubmitted.stage - - override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { - val sid = taskEnd.task.stageId - val (failureInfo, metrics): (Option[ExceptionFailure], Option[TaskMetrics]) = - taskEnd.reason match { - case e: ExceptionFailure => - stageToTasksFailed(sid) = stageToTasksFailed.getOrElse(sid, 0) + 1 - (Some(e), e.metrics) - case _ => - stageToTasksComplete(sid) = stageToTasksComplete.getOrElse(sid, 0) + 1 - (None, Some(taskEnd.taskMetrics)) - } - val taskList = stageToTaskInfos.getOrElse( - sid, ArrayBuffer[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]()) - taskList += ((taskEnd.taskInfo, metrics, failureInfo)) - stageToTaskInfos(sid) = taskList - } - - override def onJobEnd(jobEnd: SparkListenerJobEnd) { - jobEnd match { - case end: SparkListenerJobEnd => - end.jobResult match { - case JobFailed(ex, Some(stage)) => - activeStages -= stage - failedStages += stage - trimIfNecessary(failedStages) - case _ => - } - case _ => - } - } - - /** Is this stage's input from a shuffle read. */ - def hasShuffleRead(stageID: Int): Boolean = { - // This is written in a slightly complicated way to avoid having to scan all tasks - for (s <- stageToTaskInfos.get(stageID).getOrElse(Seq())) { - if (s._2 != null) return s._2.flatMap(m => m.shuffleReadMetrics).isDefined - } - return false // No tasks have finished for this stage - } - - /** Is this stage's output to a shuffle write. */ - def hasShuffleWrite(stageID: Int): Boolean = { - // This is written in a slightly complicated way to avoid having to scan all tasks - for (s <- stageToTaskInfos.get(stageID).getOrElse(Seq())) { - if (s._2 != null) return s._2.flatMap(m => m.shuffleWriteMetrics).isDefined - } - return false // No tasks have finished for this stage - } -} diff --git a/core/src/main/scala/spark/ui/jobs/StagePage.scala b/core/src/main/scala/spark/ui/jobs/StagePage.scala deleted file mode 100644 index 51b82b6a8c..0000000000 --- a/core/src/main/scala/spark/ui/jobs/StagePage.scala +++ /dev/null @@ -1,114 +0,0 @@ -package spark.ui.jobs - -import java.util.Date - -import javax.servlet.http.HttpServletRequest - -import scala.xml.Node - -import spark.ui.UIUtils._ -import spark.ui.Page._ -import spark.util.Distribution -import spark.{ExceptionFailure, Utils} -import spark.scheduler.cluster.TaskInfo -import spark.executor.TaskMetrics - -/** Page showing statistics and task list for a given stage */ -private[spark] class StagePage(parent: JobProgressUI) { - def listener = parent.listener - val dateFmt = parent.dateFmt - - def render(request: HttpServletRequest): Seq[Node] = { - val stageId = request.getParameter("id").toInt - - if (!listener.stageToTaskInfos.contains(stageId)) { - val content = - <div> - <h2>Summary Metrics</h2> No tasks have finished yet - <h2>Tasks</h2> No tasks have finished yet - </div> - return headerSparkPage(content, parent.sc, "Stage Details: %s".format(stageId), Jobs) - } - - val tasks = listener.stageToTaskInfos(stageId) - - val shuffleRead = listener.hasShuffleRead(stageId) - val shuffleWrite = listener.hasShuffleWrite(stageId) - - val taskHeaders: Seq[String] = - Seq("Task ID", "Duration", "Locality Level", "Worker", "Launch Time") ++ - {if (shuffleRead) Seq("Shuffle Read") else Nil} ++ - {if (shuffleWrite) Seq("Shuffle Write") else Nil} ++ - Seq("Details") - - val taskTable = listingTable(taskHeaders, taskRow, tasks) - - // Excludes tasks which failed and have incomplete metrics - val validTasks = tasks.filter(t => Option(t._2).isDefined) - - val summaryTable: Option[Seq[Node]] = - if (validTasks.size == 0) { - None - } - else { - val serviceTimes = validTasks.map{case (info, metrics, exception) => - metrics.get.executorRunTime.toDouble} - val serviceQuantiles = "Duration" +: Distribution(serviceTimes).get.getQuantiles().map( - ms => parent.formatDuration(ms.toLong)) - - def getQuantileCols(data: Seq[Double]) = - Distribution(data).get.getQuantiles().map(d => Utils.memoryBytesToString(d.toLong)) - - val shuffleReadSizes = validTasks.map { - case(info, metrics, exception) => - metrics.get.shuffleReadMetrics.map(_.remoteBytesRead).getOrElse(0L).toDouble - } - val shuffleReadQuantiles = "Shuffle Read (Remote)" +: getQuantileCols(shuffleReadSizes) - - val shuffleWriteSizes = validTasks.map { - case(info, metrics, exception) => - metrics.get.shuffleWriteMetrics.map(_.shuffleBytesWritten).getOrElse(0L).toDouble - } - val shuffleWriteQuantiles = "Shuffle Write" +: getQuantileCols(shuffleWriteSizes) - - val listings: Seq[Seq[String]] = Seq(serviceQuantiles, - if (shuffleRead) shuffleReadQuantiles else Nil, - if (shuffleWrite) shuffleWriteQuantiles else Nil) - - val quantileHeaders = Seq("Metric", "Min", "25%", "50%", "75%", "Max") - def quantileRow(data: Seq[String]): Seq[Node] = <tr> {data.map(d => <td>{d}</td>)} </tr> - Some(listingTable(quantileHeaders, quantileRow, listings)) - } - - val content = - <h2>Summary Metrics</h2> ++ summaryTable.getOrElse(Nil) ++ <h2>Tasks</h2> ++ taskTable; - - headerSparkPage(content, parent.sc, "Stage Details: %s".format(stageId), Jobs) - } - - - def taskRow(taskData: (TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])): Seq[Node] = { - def fmtStackTrace(trace: Seq[StackTraceElement]): Seq[Node] = - trace.map(e => <span style="display:block;">{e.toString}</span>) - val (info, metrics, exception) = taskData - <tr> - <td>{info.taskId}</td> - <td sorttable_customkey={metrics.map{m => m.executorRunTime.toString}.getOrElse("1")}> - {metrics.map{m => parent.formatDuration(m.executorRunTime)}.getOrElse("")} - </td> - <td>{info.taskLocality}</td> - <td>{info.hostPort}</td> - <td>{dateFmt.format(new Date(info.launchTime))}</td> - {metrics.flatMap{m => m.shuffleReadMetrics}.map{s => - <td>{Utils.memoryBytesToString(s.remoteBytesRead)}</td>}.getOrElse("")} - {metrics.flatMap{m => m.shuffleWriteMetrics}.map{s => - <td>{Utils.memoryBytesToString(s.shuffleBytesWritten)}</td>}.getOrElse("")} - <td>{exception.map(e => - <span> - {e.className} ({e.description})<br/> - {fmtStackTrace(e.stackTrace)} - </span>).getOrElse("")} - </td> - </tr> - } -} diff --git a/core/src/main/scala/spark/ui/storage/BlockManagerUI.scala b/core/src/main/scala/spark/ui/storage/BlockManagerUI.scala deleted file mode 100644 index 252600aad4..0000000000 --- a/core/src/main/scala/spark/ui/storage/BlockManagerUI.scala +++ /dev/null @@ -1,24 +0,0 @@ -package spark.ui.storage - -import scala.concurrent.duration._ - -import javax.servlet.http.HttpServletRequest - -import org.eclipse.jetty.server.Handler - -import spark.{Logging, SparkContext} -import spark.ui.JettyUtils._ - -/** Web UI showing storage status of all RDD's in the given SparkContext. */ -private[spark] class BlockManagerUI(val sc: SparkContext) extends Logging { - implicit val timeout = Duration.create( - System.getProperty("spark.akka.askTimeout", "10").toLong, "seconds") - - val indexPage = new IndexPage(this) - val rddPage = new RDDPage(this) - - def getHandlers = Seq[(String, Handler)]( - ("/storage/rdd", (request: HttpServletRequest) => rddPage.render(request)), - ("/storage", (request: HttpServletRequest) => indexPage.render(request)) - ) -} diff --git a/core/src/main/scala/spark/ui/storage/IndexPage.scala b/core/src/main/scala/spark/ui/storage/IndexPage.scala deleted file mode 100644 index d284134391..0000000000 --- a/core/src/main/scala/spark/ui/storage/IndexPage.scala +++ /dev/null @@ -1,64 +0,0 @@ -package spark.ui.storage - -import javax.servlet.http.HttpServletRequest - -import scala.xml.Node - -import spark.storage.{RDDInfo, StorageUtils} -import spark.Utils -import spark.ui.UIUtils._ -import spark.ui.Page._ - -/** Page showing list of RDD's currently stored in the cluster */ -private[spark] class IndexPage(parent: BlockManagerUI) { - val sc = parent.sc - - def render(request: HttpServletRequest): Seq[Node] = { - val storageStatusList = sc.getExecutorStorageStatus - // Calculate macro-level statistics - val maxMem = storageStatusList.map(_.maxMem).reduce(_+_) - val remainingMem = storageStatusList.map(_.memRemaining).reduce(_+_) - val diskSpaceUsed = storageStatusList.flatMap(_.blocks.values.map(_.diskSize)) - .reduceOption(_+_).getOrElse(0L) - - val rddHeaders = Seq( - "RDD Name", - "Storage Level", - "Cached Partitions", - "Fraction Partitions Cached", - "Size in Memory", - "Size on Disk") - val rdds = StorageUtils.rddInfoFromStorageStatus(storageStatusList, sc) - val rddTable = listingTable(rddHeaders, rddRow, rdds) - - val content = - <div class="row"> - <div class="span12"> - <ul class="unstyled"> - <li><strong>Memory:</strong> - {Utils.memoryBytesToString(maxMem - remainingMem)} Used - ({Utils.memoryBytesToString(remainingMem)} Available) </li> - <li><strong>Disk:</strong> {Utils.memoryBytesToString(diskSpaceUsed)} Used </li> - </ul> - </div> - </div> ++ {rddTable}; - - headerSparkPage(content, parent.sc, "Spark Storage ", Storage) - } - - def rddRow(rdd: RDDInfo): Seq[Node] = { - <tr> - <td> - <a href={"/storage/rdd?id=%s".format(rdd.id)}> - {rdd.name} - </a> - </td> - <td>{rdd.storageLevel.description} - </td> - <td>{rdd.numCachedPartitions}</td> - <td>{rdd.numCachedPartitions / rdd.numPartitions.toDouble}</td> - <td>{Utils.memoryBytesToString(rdd.memSize)}</td> - <td>{Utils.memoryBytesToString(rdd.diskSize)}</td> - </tr> - } -} diff --git a/core/src/main/scala/spark/util/CompletionIterator.scala b/core/src/main/scala/spark/util/CompletionIterator.scala deleted file mode 100644 index 8139183780..0000000000 --- a/core/src/main/scala/spark/util/CompletionIterator.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark.util - -/** - * Wrapper around an iterator which calls a completion method after it successfully iterates through all the elements - */ -abstract class CompletionIterator[+A, +I <: Iterator[A]](sub: I) extends Iterator[A]{ - def next = sub.next - def hasNext = { - val r = sub.hasNext - if (!r) { - completion - } - r - } - - def completion() -} - -object CompletionIterator { - def apply[A, I <: Iterator[A]](sub: I, completionFunction: => Unit) : CompletionIterator[A,I] = { - new CompletionIterator[A,I](sub) { - def completion() = completionFunction - } - } -}
\ No newline at end of file diff --git a/core/src/main/scala/spark/util/IdGenerator.scala b/core/src/main/scala/spark/util/IdGenerator.scala deleted file mode 100644 index b6e309fe1a..0000000000 --- a/core/src/main/scala/spark/util/IdGenerator.scala +++ /dev/null @@ -1,14 +0,0 @@ -package spark.util - -import java.util.concurrent.atomic.AtomicInteger - -/** - * A util used to get a unique generation ID. This is a wrapper around Java's - * AtomicInteger. An example usage is in BlockManager, where each BlockManager - * instance would start an Akka actor and we use this utility to assign the Akka - * actors unique names. - */ -private[spark] class IdGenerator { - private var id = new AtomicInteger - def next: Int = id.incrementAndGet -} diff --git a/core/src/main/scala/spark/util/IntParam.scala b/core/src/main/scala/spark/util/IntParam.scala deleted file mode 100644 index 0427646747..0000000000 --- a/core/src/main/scala/spark/util/IntParam.scala +++ /dev/null @@ -1,14 +0,0 @@ -package spark.util - -/** - * An extractor object for parsing strings into integers. - */ -private[spark] object IntParam { - def unapply(str: String): Option[Int] = { - try { - Some(str.toInt) - } catch { - case e: NumberFormatException => None - } - } -} diff --git a/core/src/main/scala/spark/util/MemoryParam.scala b/core/src/main/scala/spark/util/MemoryParam.scala deleted file mode 100644 index 3726738842..0000000000 --- a/core/src/main/scala/spark/util/MemoryParam.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark.util - -import spark.Utils - -/** - * An extractor object for parsing JVM memory strings, such as "10g", into an Int representing - * the number of megabytes. Supports the same formats as Utils.memoryStringToMb. - */ -private[spark] object MemoryParam { - def unapply(str: String): Option[Int] = { - try { - Some(Utils.memoryStringToMb(str)) - } catch { - case e: NumberFormatException => None - } - } -} diff --git a/core/src/test/resources/fairscheduler.xml b/core/src/test/resources/fairscheduler.xml index 6e573b1883..996ffb1864 100644 --- a/core/src/test/resources/fairscheduler.xml +++ b/core/src/test/resources/fairscheduler.xml @@ -1,4 +1,21 @@ <?xml version="1.0"?> +<!-- + ~ Licensed to the Apache Software Foundation (ASF) under one or more + ~ contributor license agreements. See the NOTICE file distributed with + ~ this work for additional information regarding copyright ownership. + ~ The ASF licenses this file to You under the Apache License, Version 2.0 + ~ (the "License"); you may not use this file except in compliance with + ~ the License. You may obtain a copy of the License at + ~ + ~ http://www.apache.org/licenses/LICENSE-2.0 + ~ + ~ Unless required by applicable law or agreed to in writing, software + ~ distributed under the License is distributed on an "AS IS" BASIS, + ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + ~ See the License for the specific language governing permissions and + ~ limitations under the License. + --> + <allocations> <pool name="1"> <minShare>2</minShare> diff --git a/core/src/test/resources/log4j.properties b/core/src/test/resources/log4j.properties index d05cf3dec1..f6fef03689 100644 --- a/core/src/test/resources/log4j.properties +++ b/core/src/test/resources/log4j.properties @@ -1,4 +1,21 @@ -# Set everything to be logged to the file core/target/unit-tests.log +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +# Set everything to be logged to the file core/target/unit-tests.log log4j.rootCategory=INFO, file log4j.appender.file=org.apache.log4j.FileAppender log4j.appender.file.append=false diff --git a/core/src/test/resources/test_metrics_config.properties b/core/src/test/resources/test_metrics_config.properties new file mode 100644 index 0000000000..da2b29b9ce --- /dev/null +++ b/core/src/test/resources/test_metrics_config.properties @@ -0,0 +1,23 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +*.sink.console.period = 10 +*.sink.console.unit = seconds +*.source.jvm.class = org.apache.spark.metrics.source.JvmSource +master.sink.console.period = 20 +master.sink.console.unit = minutes + diff --git a/core/src/test/resources/test_metrics_system.properties b/core/src/test/resources/test_metrics_system.properties new file mode 100644 index 0000000000..35d0bd3b8d --- /dev/null +++ b/core/src/test/resources/test_metrics_system.properties @@ -0,0 +1,24 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +*.sink.console.period = 10 +*.sink.console.unit = seconds +test.sink.console.class = org.apache.spark.metrics.sink.ConsoleSink +test.sink.dummy.class = org.apache.spark.metrics.sink.DummySink +test.source.dummy.class = org.apache.spark.metrics.source.DummySource +test.sink.console.period = 20 +test.sink.console.unit = minutes diff --git a/core/src/test/scala/spark/AccumulatorSuite.scala b/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala index fb54ccb51e..c443c5266e 100644 --- a/core/src/test/scala/spark/AccumulatorSuite.scala +++ b/core/src/test/scala/org/apache/spark/AccumulatorSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.scalatest.FunSuite import org.scalatest.matchers.ShouldMatchers @@ -6,7 +23,7 @@ import collection.mutable import java.util.Random import scala.math.exp import scala.math.signum -import spark.SparkContext._ +import org.apache.spark.SparkContext._ class AccumulatorSuite extends FunSuite with ShouldMatchers with LocalSparkContext { diff --git a/core/src/test/scala/org/apache/spark/BroadcastSuite.scala b/core/src/test/scala/org/apache/spark/BroadcastSuite.scala new file mode 100644 index 0000000000..b3a53d928b --- /dev/null +++ b/core/src/test/scala/org/apache/spark/BroadcastSuite.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.FunSuite + +class BroadcastSuite extends FunSuite with LocalSparkContext { + + test("basic broadcast") { + sc = new SparkContext("local", "test") + val list = List(1, 2, 3, 4) + val listBroadcast = sc.broadcast(list) + val results = sc.parallelize(1 to 2).map(x => (x, listBroadcast.value.sum)) + assert(results.collect.toSet === Set((1, 10), (2, 10))) + } + + test("broadcast variables accessed in multiple threads") { + sc = new SparkContext("local[10]", "test") + val list = List(1, 2, 3, 4) + val listBroadcast = sc.broadcast(list) + val results = sc.parallelize(1 to 10).map(x => (x, listBroadcast.value.sum)) + assert(results.collect.toSet === (1 to 10).map(x => (x, 10)).toSet) + } +} diff --git a/core/src/test/scala/spark/CheckpointSuite.scala b/core/src/test/scala/org/apache/spark/CheckpointSuite.scala index 6785787b7e..78e35732d2 100644 --- a/core/src/test/scala/spark/CheckpointSuite.scala +++ b/core/src/test/scala/org/apache/spark/CheckpointSuite.scala @@ -1,11 +1,29 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import scala.reflect.ClassTag import org.scalatest.FunSuite import java.io.File -import spark.rdd._ -import spark.SparkContext._ +import org.apache.spark.rdd._ +import org.apache.spark.SparkContext._ import storage.StorageLevel +import org.apache.spark.util.Utils class CheckpointSuite extends FunSuite with LocalSparkContext with Logging { initLogging() @@ -83,7 +101,7 @@ class CheckpointSuite extends FunSuite with LocalSparkContext with Logging { test("ShuffledRDD") { testCheckpointing(rdd => { // Creating ShuffledRDD directly as PairRDDFunctions.combineByKey produces a MapPartitionedRDD - new ShuffledRDD(rdd.map(x => (x % 2, 1)), partitioner) + new ShuffledRDD[Int, Int, (Int, Int)](rdd.map(x => (x % 2, 1)), partitioner) }) } diff --git a/core/src/test/scala/spark/DistributedSuite.scala b/core/src/test/scala/org/apache/spark/DistributedSuite.scala index 0024ede828..7a856d4081 100644 --- a/core/src/test/scala/spark/DistributedSuite.scala +++ b/core/src/test/scala/org/apache/spark/DistributedSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import network.ConnectionManagerId import org.scalatest.FunSuite diff --git a/core/src/test/scala/spark/DriverSuite.scala b/core/src/test/scala/org/apache/spark/DriverSuite.scala index 31c3dd75fb..01a72d8401 100644 --- a/core/src/test/scala/spark/DriverSuite.scala +++ b/core/src/test/scala/org/apache/spark/DriverSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io.File @@ -9,6 +26,7 @@ import org.scalatest.FunSuite import org.scalatest.concurrent.Timeouts import org.scalatest.prop.TableDrivenPropertyChecks._ import org.scalatest.time.SpanSugar._ +import org.apache.spark.util.Utils class DriverSuite extends FunSuite with Timeouts { test("driver should exit after finishing") { @@ -17,7 +35,7 @@ class DriverSuite extends FunSuite with Timeouts { val masters = Table(("master"), ("local"), ("local-cluster[2,1,512]")) forAll(masters) { (master: String) => failAfter(30 seconds) { - Utils.execute(Seq("./run", "spark.DriverWithoutCleanup", master), + Utils.execute(Seq("./spark-class", "org.apache.spark.DriverWithoutCleanup", master), new File(System.getenv("SPARK_HOME"))) } } diff --git a/core/src/test/scala/spark/FailureSuite.scala b/core/src/test/scala/org/apache/spark/FailureSuite.scala index 8c1445a465..af448fcb37 100644 --- a/core/src/test/scala/spark/FailureSuite.scala +++ b/core/src/test/scala/org/apache/spark/FailureSuite.scala @@ -1,11 +1,26 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ -import org.scalatest.FunSuite -import org.scalatest.prop.Checkers +package org.apache.spark -import scala.collection.mutable.ArrayBuffer +import org.scalatest.FunSuite import SparkContext._ +import org.apache.spark.util.NonSerializable // Common state shared by FailureSuite-launched tasks. We use a global object // for this because any local variables used in the task closures will rightfully @@ -23,7 +38,7 @@ object FailureSuiteState { } class FailureSuite extends FunSuite with LocalSparkContext { - + // Run a 3-task map job in which task 1 deterministically fails once, and check // whether the job completes successfully and we ran 4 tasks in total. test("failure in a single-stage job") { @@ -49,7 +64,7 @@ class FailureSuite extends FunSuite with LocalSparkContext { test("failure in a two-stage job") { sc = new SparkContext("local[1,1]", "test") val results = sc.makeRDD(1 to 3).map(x => (x, x)).groupByKey(3).map { - case (k, v) => + case (k, v) => FailureSuiteState.synchronized { FailureSuiteState.tasksRun += 1 if (k == 1 && FailureSuiteState.tasksFailed == 0) { @@ -70,15 +85,43 @@ class FailureSuite extends FunSuite with LocalSparkContext { sc = new SparkContext("local[1,1]", "test") val results = sc.makeRDD(1 to 3).map(x => new NonSerializable) - val thrown = intercept[spark.SparkException] { + val thrown = intercept[SparkException] { results.collect() } - assert(thrown.getClass === classOf[spark.SparkException]) + assert(thrown.getClass === classOf[SparkException]) assert(thrown.getMessage.contains("NotSerializableException")) FailureSuiteState.clear() } + test("failure because task closure is not serializable") { + sc = new SparkContext("local[1,1]", "test") + val a = new NonSerializable + + // Non-serializable closure in the final result stage + val thrown = intercept[SparkException] { + sc.parallelize(1 to 10, 2).map(x => a).count() + } + assert(thrown.getClass === classOf[SparkException]) + assert(thrown.getMessage.contains("NotSerializableException")) + + // Non-serializable closure in an earlier stage + val thrown1 = intercept[SparkException] { + sc.parallelize(1 to 10, 2).map(x => (x, a)).partitionBy(new HashPartitioner(3)).count() + } + assert(thrown1.getClass === classOf[SparkException]) + assert(thrown1.getMessage.contains("NotSerializableException")) + + // Non-serializable closure in foreach function + val thrown2 = intercept[SparkException] { + sc.parallelize(1 to 10, 2).foreach(x => println(a)) + } + assert(thrown2.getClass === classOf[SparkException]) + assert(thrown2.getMessage.contains("NotSerializableException")) + + FailureSuiteState.clear() + } + // TODO: Need to add tests with shuffle fetch failures. } diff --git a/core/src/test/scala/spark/FileServerSuite.scala b/core/src/test/scala/org/apache/spark/FileServerSuite.scala index 9c24ca430d..35d1d41af1 100644 --- a/core/src/test/scala/spark/FileServerSuite.scala +++ b/core/src/test/scala/org/apache/spark/FileServerSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import com.google.common.io.Files import org.scalatest.FunSuite @@ -35,26 +52,26 @@ class FileServerSuite extends FunSuite with LocalSparkContext { val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { val path = SparkFiles.get("FileServerSuite.txt") - val in = new BufferedReader(new FileReader(path)) + val in = new BufferedReader(new FileReader(path)) val fileVal = in.readLine().toInt in.close() _ * fileVal + _ * fileVal - }.collect + }.collect() assert(result.toSet === Set((1,200), (2,300), (3,500))) } test("Distributing files locally using URL as input") { // addFile("file:///....") sc = new SparkContext("local[4]", "test") - sc.addFile((new File(tmpFile.toString)).toURL.toString) + sc.addFile(new File(tmpFile.toString).toURI.toString) val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { val path = SparkFiles.get("FileServerSuite.txt") - val in = new BufferedReader(new FileReader(path)) + val in = new BufferedReader(new FileReader(path)) val fileVal = in.readLine().toInt in.close() _ * fileVal + _ * fileVal - }.collect + }.collect() assert(result.toSet === Set((1,200), (2,300), (3,500))) } @@ -80,11 +97,11 @@ class FileServerSuite extends FunSuite with LocalSparkContext { val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { val path = SparkFiles.get("FileServerSuite.txt") - val in = new BufferedReader(new FileReader(path)) + val in = new BufferedReader(new FileReader(path)) val fileVal = in.readLine().toInt in.close() _ * fileVal + _ * fileVal - }.collect + }.collect() assert(result.toSet === Set((1,200), (2,300), (3,500))) } diff --git a/core/src/test/scala/spark/FileSuite.scala b/core/src/test/scala/org/apache/spark/FileSuite.scala index e61ff7793d..7b82a4cdd9 100644 --- a/core/src/test/scala/spark/FileSuite.scala +++ b/core/src/test/scala/org/apache/spark/FileSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.io.{FileWriter, PrintWriter, File} diff --git a/core/src/test/scala/spark/JavaAPISuite.java b/core/src/test/scala/org/apache/spark/JavaAPISuite.java index d306124fca..8a869c9005 100644 --- a/core/src/test/scala/spark/JavaAPISuite.java +++ b/core/src/test/scala/org/apache/spark/JavaAPISuite.java @@ -1,10 +1,28 @@ -package spark; +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark; import java.io.File; import java.io.IOException; import java.io.Serializable; import java.util.*; +import com.google.common.base.Optional; import scala.Tuple2; import com.google.common.base.Charsets; @@ -20,15 +38,15 @@ import org.junit.Assert; import org.junit.Before; import org.junit.Test; -import spark.api.java.JavaDoubleRDD; -import spark.api.java.JavaPairRDD; -import spark.api.java.JavaRDD; -import spark.api.java.JavaSparkContext; -import spark.api.java.function.*; -import spark.partial.BoundedDouble; -import spark.partial.PartialResult; -import spark.storage.StorageLevel; -import spark.util.StatCounter; +import org.apache.spark.api.java.JavaDoubleRDD; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.*; +import org.apache.spark.partial.BoundedDouble; +import org.apache.spark.partial.PartialResult; +import org.apache.spark.storage.StorageLevel; +import org.apache.spark.util.StatCounter; // The test suite itself is Serializable so that anonymous Function implementations can be @@ -181,6 +199,35 @@ public class JavaAPISuite implements Serializable { } @Test + public void leftOuterJoin() { + JavaPairRDD<Integer, Integer> rdd1 = sc.parallelizePairs(Arrays.asList( + new Tuple2<Integer, Integer>(1, 1), + new Tuple2<Integer, Integer>(1, 2), + new Tuple2<Integer, Integer>(2, 1), + new Tuple2<Integer, Integer>(3, 1) + )); + JavaPairRDD<Integer, Character> rdd2 = sc.parallelizePairs(Arrays.asList( + new Tuple2<Integer, Character>(1, 'x'), + new Tuple2<Integer, Character>(2, 'y'), + new Tuple2<Integer, Character>(2, 'z'), + new Tuple2<Integer, Character>(4, 'w') + )); + List<Tuple2<Integer,Tuple2<Integer,Optional<Character>>>> joined = + rdd1.leftOuterJoin(rdd2).collect(); + Assert.assertEquals(5, joined.size()); + Tuple2<Integer,Tuple2<Integer,Optional<Character>>> firstUnmatched = + rdd1.leftOuterJoin(rdd2).filter( + new Function<Tuple2<Integer, Tuple2<Integer, Optional<Character>>>, Boolean>() { + @Override + public Boolean call(Tuple2<Integer, Tuple2<Integer, Optional<Character>>> tup) + throws Exception { + return !tup._2()._2().isPresent(); + } + }).first(); + Assert.assertEquals(3, firstUnmatched._1().intValue()); + } + + @Test public void foldReduce() { JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 1, 2, 3, 5, 8, 13)); Function2<Integer, Integer, Integer> add = new Function2<Integer, Integer, Integer>() { @@ -309,7 +356,9 @@ public class JavaAPISuite implements Serializable { Assert.assertEquals(20/6.0, rdd.mean(), 0.01); Assert.assertEquals(20/6.0, rdd.mean(), 0.01); Assert.assertEquals(6.22222, rdd.variance(), 0.01); + Assert.assertEquals(7.46667, rdd.sampleVariance(), 0.01); Assert.assertEquals(2.49444, rdd.stdev(), 0.01); + Assert.assertEquals(2.73252, rdd.sampleStdev(), 0.01); Double first = rdd.first(); List<Double> take = rdd.take(5); @@ -699,7 +748,7 @@ public class JavaAPISuite implements Serializable { } }; - JavaRDD<Integer> sizes = rdd1.zipPartitions(sizesFn, rdd2); + JavaRDD<Integer> sizes = rdd1.zipPartitions(rdd2, sizesFn); Assert.assertEquals("[3, 2, 3, 2]", sizes.collect().toString()); } diff --git a/core/src/test/scala/spark/LocalSparkContext.scala b/core/src/test/scala/org/apache/spark/LocalSparkContext.scala index bd184222ed..6ec124da9c 100644 --- a/core/src/test/scala/spark/LocalSparkContext.scala +++ b/core/src/test/scala/org/apache/spark/LocalSparkContext.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.scalatest.Suite import org.scalatest.BeforeAndAfterEach diff --git a/core/src/test/scala/spark/MapOutputTrackerSuite.scala b/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala index 6e585e1c3a..6013320eaa 100644 --- a/core/src/test/scala/spark/MapOutputTrackerSuite.scala +++ b/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala @@ -1,11 +1,28 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.scalatest.FunSuite import akka.actor._ -import spark.scheduler.MapStatus -import spark.storage.BlockManagerId -import spark.util.AkkaUtils +import org.apache.spark.scheduler.MapStatus +import org.apache.spark.storage.BlockManagerId +import org.apache.spark.util.AkkaUtils class MapOutputTrackerSuite extends FunSuite with LocalSparkContext { @@ -95,22 +112,22 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext { "akka://spark@localhost:" + boundPort + "/user/MapOutputTracker") masterTracker.registerShuffle(10, 1) - masterTracker.incrementGeneration() - slaveTracker.updateGeneration(masterTracker.getGeneration) + masterTracker.incrementEpoch() + slaveTracker.updateEpoch(masterTracker.getEpoch) intercept[FetchFailedException] { slaveTracker.getServerStatuses(10, 0) } val compressedSize1000 = MapOutputTracker.compressSize(1000L) val size1000 = MapOutputTracker.decompressSize(compressedSize1000) masterTracker.registerMapOutput(10, 0, new MapStatus( BlockManagerId("a", "hostA", 1000, 0), Array(compressedSize1000))) - masterTracker.incrementGeneration() - slaveTracker.updateGeneration(masterTracker.getGeneration) + masterTracker.incrementEpoch() + slaveTracker.updateEpoch(masterTracker.getEpoch) assert(slaveTracker.getServerStatuses(10, 0).toSeq === Seq((BlockManagerId("a", "hostA", 1000, 0), size1000))) masterTracker.unregisterMapOutput(10, 0, BlockManagerId("a", "hostA", 1000, 0)) - masterTracker.incrementGeneration() - slaveTracker.updateGeneration(masterTracker.getGeneration) + masterTracker.incrementEpoch() + slaveTracker.updateEpoch(masterTracker.getEpoch) intercept[FetchFailedException] { slaveTracker.getServerStatuses(10, 0) } // failure should be cached diff --git a/core/src/test/scala/org/apache/spark/PartitionPruningRDDSuite.scala b/core/src/test/scala/org/apache/spark/PartitionPruningRDDSuite.scala new file mode 100644 index 0000000000..21f16ef2c6 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/PartitionPruningRDDSuite.scala @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.FunSuite +import org.apache.spark.SparkContext._ +import org.apache.spark.rdd.{RDD, PartitionPruningRDD} + + +class PartitionPruningRDDSuite extends FunSuite with SharedSparkContext { + + test("Pruned Partitions inherit locality prefs correctly") { + class TestPartition(i: Int) extends Partition { + def index = i + } + val rdd = new RDD[Int](sc, Nil) { + override protected def getPartitions = { + Array[Partition]( + new TestPartition(1), + new TestPartition(2), + new TestPartition(3)) + } + def compute(split: Partition, context: TaskContext) = {Iterator()} + } + val prunedRDD = PartitionPruningRDD.create(rdd, {x => if (x==2) true else false}) + val p = prunedRDD.partitions(0) + assert(p.index == 2) + assert(prunedRDD.partitions.length == 1) + } +} diff --git a/core/src/test/scala/spark/PartitioningSuite.scala b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala index 99e433e3bd..7d938917f2 100644 --- a/core/src/test/scala/spark/PartitioningSuite.scala +++ b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala @@ -1,10 +1,30 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark -import org.scalatest.FunSuite -import scala.collection.mutable.ArrayBuffer -import SparkContext._ -import spark.util.StatCounter import scala.math.abs +import scala.collection.mutable.ArrayBuffer + +import org.scalatest.FunSuite + +import org.apache.spark.SparkContext._ +import org.apache.spark.util.StatCounter +import org.apache.spark.rdd.RDD class PartitioningSuite extends FunSuite with SharedSparkContext { diff --git a/core/src/test/scala/spark/PipedRDDSuite.scala b/core/src/test/scala/org/apache/spark/PipedRDDSuite.scala index d263bb00e9..2e851d892d 100644 --- a/core/src/test/scala/spark/PipedRDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/PipedRDDSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.scalatest.FunSuite import SparkContext._ diff --git a/core/src/test/scala/org/apache/spark/SharedSparkContext.scala b/core/src/test/scala/org/apache/spark/SharedSparkContext.scala new file mode 100644 index 0000000000..97cbca09bf --- /dev/null +++ b/core/src/test/scala/org/apache/spark/SharedSparkContext.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.Suite +import org.scalatest.BeforeAndAfterAll + +/** Shares a local `SparkContext` between all tests in a suite and closes it at the end */ +trait SharedSparkContext extends BeforeAndAfterAll { self: Suite => + + @transient private var _sc: SparkContext = _ + + def sc: SparkContext = _sc + + override def beforeAll() { + _sc = new SparkContext("local", "test") + super.beforeAll() + } + + override def afterAll() { + if (_sc != null) { + LocalSparkContext.stop(_sc) + _sc = null + } + super.afterAll() + } +} diff --git a/core/src/test/scala/org/apache/spark/ShuffleNettySuite.scala b/core/src/test/scala/org/apache/spark/ShuffleNettySuite.scala new file mode 100644 index 0000000000..e121b162ad --- /dev/null +++ b/core/src/test/scala/org/apache/spark/ShuffleNettySuite.scala @@ -0,0 +1,34 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.BeforeAndAfterAll + + +class ShuffleNettySuite extends ShuffleSuite with BeforeAndAfterAll { + + // This test suite should run all tests in ShuffleSuite with Netty shuffle mode. + + override def beforeAll(configMap: Map[String, Any]) { + System.setProperty("spark.shuffle.use.netty", "true") + } + + override def afterAll(configMap: Map[String, Any]) { + System.setProperty("spark.shuffle.use.netty", "false") + } +} diff --git a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala new file mode 100644 index 0000000000..db717865db --- /dev/null +++ b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala @@ -0,0 +1,211 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.FunSuite +import org.scalatest.matchers.ShouldMatchers + +import org.apache.spark.SparkContext._ +import org.apache.spark.ShuffleSuite.NonJavaSerializableClass +import org.apache.spark.rdd.{RDD, SubtractedRDD, CoGroupedRDD, OrderedRDDFunctions, ShuffledRDD} +import org.apache.spark.util.MutablePair +import org.apache.spark.serializer.KryoSerializer + + +class ShuffleSuite extends FunSuite with ShouldMatchers with LocalSparkContext { + test("groupByKey without compression") { + try { + System.setProperty("spark.shuffle.compress", "false") + sc = new SparkContext("local", "test") + val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (2, 1)), 4) + val groups = pairs.groupByKey(4).collect() + assert(groups.size === 2) + val valuesFor1 = groups.find(_._1 == 1).get._2 + assert(valuesFor1.toList.sorted === List(1, 2, 3)) + val valuesFor2 = groups.find(_._1 == 2).get._2 + assert(valuesFor2.toList.sorted === List(1)) + } finally { + System.setProperty("spark.shuffle.compress", "true") + } + } + + test("shuffle non-zero block size") { + sc = new SparkContext("local-cluster[2,1,512]", "test") + val NUM_BLOCKS = 3 + + val a = sc.parallelize(1 to 10, 2) + val b = a.map { x => + (x, new NonJavaSerializableClass(x * 2)) + } + // If the Kryo serializer is not used correctly, the shuffle would fail because the + // default Java serializer cannot handle the non serializable class. + val c = new ShuffledRDD[Int, NonJavaSerializableClass, (Int, NonJavaSerializableClass)]( + b, new HashPartitioner(NUM_BLOCKS)).setSerializer(classOf[KryoSerializer].getName) + val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId + + assert(c.count === 10) + + // All blocks must have non-zero size + (0 until NUM_BLOCKS).foreach { id => + val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) + assert(statuses.forall(s => s._2 > 0)) + } + } + + test("shuffle serializer") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + val a = sc.parallelize(1 to 10, 2) + val b = a.map { x => + (x, new NonJavaSerializableClass(x * 2)) + } + // If the Kryo serializer is not used correctly, the shuffle would fail because the + // default Java serializer cannot handle the non serializable class. + val c = new ShuffledRDD[Int, NonJavaSerializableClass, (Int, NonJavaSerializableClass)]( + b, new HashPartitioner(3)).setSerializer(classOf[KryoSerializer].getName) + assert(c.count === 10) + } + + test("zero sized blocks") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + + // 10 partitions from 4 keys + val NUM_BLOCKS = 10 + val a = sc.parallelize(1 to 4, NUM_BLOCKS) + val b = a.map(x => (x, x*2)) + + // NOTE: The default Java serializer doesn't create zero-sized blocks. + // So, use Kryo + val c = new ShuffledRDD[Int, Int, (Int, Int)](b, new HashPartitioner(10)) + .setSerializer(classOf[KryoSerializer].getName) + + val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId + assert(c.count === 4) + + val blockSizes = (0 until NUM_BLOCKS).flatMap { id => + val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) + statuses.map(x => x._2) + } + val nonEmptyBlocks = blockSizes.filter(x => x > 0) + + // We should have at most 4 non-zero sized partitions + assert(nonEmptyBlocks.size <= 4) + } + + test("zero sized blocks without kryo") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + + // 10 partitions from 4 keys + val NUM_BLOCKS = 10 + val a = sc.parallelize(1 to 4, NUM_BLOCKS) + val b = a.map(x => (x, x*2)) + + // NOTE: The default Java serializer should create zero-sized blocks + val c = new ShuffledRDD[Int, Int, (Int, Int)](b, new HashPartitioner(10)) + + val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId + assert(c.count === 4) + + val blockSizes = (0 until NUM_BLOCKS).flatMap { id => + val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) + statuses.map(x => x._2) + } + val nonEmptyBlocks = blockSizes.filter(x => x > 0) + + // We should have at most 4 non-zero sized partitions + assert(nonEmptyBlocks.size <= 4) + } + + test("shuffle using mutable pairs") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2) + val data = Array(p(1, 1), p(1, 2), p(1, 3), p(2, 1)) + val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2) + val results = new ShuffledRDD[Int, Int, MutablePair[Int, Int]](pairs, new HashPartitioner(2)) + .collect() + + data.foreach { pair => results should contain (pair) } + } + + test("sorting using mutable pairs") { + // This is not in SortingSuite because of the local cluster setup. + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2) + val data = Array(p(1, 11), p(3, 33), p(100, 100), p(2, 22)) + val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2) + val results = new OrderedRDDFunctions[Int, Int, MutablePair[Int, Int]](pairs) + .sortByKey().collect() + results(0) should be (p(1, 11)) + results(1) should be (p(2, 22)) + results(2) should be (p(3, 33)) + results(3) should be (p(100, 100)) + } + + test("cogroup using mutable pairs") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2) + val data1 = Seq(p(1, 1), p(1, 2), p(1, 3), p(2, 1)) + val data2 = Seq(p(1, "11"), p(1, "12"), p(2, "22"), p(3, "3")) + val pairs1: RDD[MutablePair[Int, Int]] = sc.parallelize(data1, 2) + val pairs2: RDD[MutablePair[Int, String]] = sc.parallelize(data2, 2) + val results = new CoGroupedRDD[Int](Seq(pairs1, pairs2), new HashPartitioner(2)).collectAsMap() + + assert(results(1)(0).length === 3) + assert(results(1)(0).contains(1)) + assert(results(1)(0).contains(2)) + assert(results(1)(0).contains(3)) + assert(results(1)(1).length === 2) + assert(results(1)(1).contains("11")) + assert(results(1)(1).contains("12")) + assert(results(2)(0).length === 1) + assert(results(2)(0).contains(1)) + assert(results(2)(1).length === 1) + assert(results(2)(1).contains("22")) + assert(results(3)(0).length === 0) + assert(results(3)(1).contains("3")) + } + + test("subtract mutable pairs") { + // Use a local cluster with 2 processes to make sure there are both local and remote blocks + sc = new SparkContext("local-cluster[2,1,512]", "test") + def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2) + val data1 = Seq(p(1, 1), p(1, 2), p(1, 3), p(2, 1), p(3, 33)) + val data2 = Seq(p(1, "11"), p(1, "12"), p(2, "22")) + val pairs1: RDD[MutablePair[Int, Int]] = sc.parallelize(data1, 2) + val pairs2: RDD[MutablePair[Int, String]] = sc.parallelize(data2, 2) + val results = new SubtractedRDD(pairs1, pairs2, new HashPartitioner(2)).collect() + results should have length (1) + // substracted rdd return results as Tuple2 + results(0) should be ((3, 33)) + } +} + +object ShuffleSuite { + + def mergeCombineException(x: Int, y: Int): Int = { + throw new SparkException("Exception for map-side combine.") + x + y + } + + class NonJavaSerializableClass(val value: Int) +} diff --git a/core/src/test/scala/org/apache/spark/SparkContextInfoSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextInfoSuite.scala new file mode 100644 index 0000000000..939fe51801 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/SparkContextInfoSuite.scala @@ -0,0 +1,60 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.FunSuite +import org.apache.spark.SparkContext._ + +class SparkContextInfoSuite extends FunSuite with LocalSparkContext { + test("getPersistentRDDs only returns RDDs that are marked as cached") { + sc = new SparkContext("local", "test") + assert(sc.getPersistentRDDs.isEmpty === true) + + val rdd = sc.makeRDD(Array(1, 2, 3, 4), 2) + assert(sc.getPersistentRDDs.isEmpty === true) + + rdd.cache() + assert(sc.getPersistentRDDs.size === 1) + assert(sc.getPersistentRDDs.values.head === rdd) + } + + test("getPersistentRDDs returns an immutable map") { + sc = new SparkContext("local", "test") + val rdd1 = sc.makeRDD(Array(1, 2, 3, 4), 2).cache() + + val myRdds = sc.getPersistentRDDs + assert(myRdds.size === 1) + assert(myRdds.values.head === rdd1) + + val rdd2 = sc.makeRDD(Array(5, 6, 7, 8), 1).cache() + + // getPersistentRDDs should have 2 RDDs, but myRdds should not change + assert(sc.getPersistentRDDs.size === 2) + assert(myRdds.size === 1) + } + + test("getRDDStorageInfo only reports on RDDs that actually persist data") { + sc = new SparkContext("local", "test") + val rdd = sc.makeRDD(Array(1, 2, 3, 4), 2).cache() + + assert(sc.getRDDStorageInfo.size === 0) + + rdd.collect() + assert(sc.getRDDStorageInfo.size === 1) + } +} diff --git a/core/src/test/scala/spark/ThreadingSuite.scala b/core/src/test/scala/org/apache/spark/ThreadingSuite.scala index ff315b6693..69383ddfb8 100644 --- a/core/src/test/scala/spark/ThreadingSuite.scala +++ b/core/src/test/scala/org/apache/spark/ThreadingSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import java.util.concurrent.Semaphore import java.util.concurrent.atomic.AtomicBoolean diff --git a/core/src/test/scala/org/apache/spark/UnpersistSuite.scala b/core/src/test/scala/org/apache/spark/UnpersistSuite.scala new file mode 100644 index 0000000000..46a2da1724 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/UnpersistSuite.scala @@ -0,0 +1,47 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.scalatest.FunSuite +import org.scalatest.concurrent.Timeouts._ +import org.scalatest.time.{Span, Millis} +import org.apache.spark.SparkContext._ + +class UnpersistSuite extends FunSuite with LocalSparkContext { + test("unpersist RDD") { + sc = new SparkContext("local", "test") + val rdd = sc.makeRDD(Array(1, 2, 3, 4), 2).cache() + rdd.count + assert(sc.persistentRdds.isEmpty === false) + rdd.unpersist() + assert(sc.persistentRdds.isEmpty === true) + + failAfter(Span(3000, Millis)) { + try { + while (! sc.getRDDStorageInfo.isEmpty) { + Thread.sleep(200) + } + } catch { + case _ => { Thread.sleep(10) } + // Do nothing. We might see exceptions because block manager + // is racing this thread to remove entries from the driver. + } + } + assert(sc.getRDDStorageInfo.isEmpty === true) + } +} diff --git a/core/src/test/scala/org/apache/spark/ZippedPartitionsSuite.scala b/core/src/test/scala/org/apache/spark/ZippedPartitionsSuite.scala new file mode 100644 index 0000000000..618b9c113b --- /dev/null +++ b/core/src/test/scala/org/apache/spark/ZippedPartitionsSuite.scala @@ -0,0 +1,50 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import scala.collection.immutable.NumericRange + +import org.scalatest.FunSuite +import org.scalatest.prop.Checkers +import org.scalacheck.Arbitrary._ +import org.scalacheck.Gen +import org.scalacheck.Prop._ + +import SparkContext._ + + +object ZippedPartitionsSuite { + def procZippedData(i: Iterator[Int], s: Iterator[String], d: Iterator[Double]) : Iterator[Int] = { + Iterator(i.toArray.size, s.toArray.size, d.toArray.size) + } +} + +class ZippedPartitionsSuite extends FunSuite with SharedSparkContext { + test("print sizes") { + val data1 = sc.makeRDD(Array(1, 2, 3, 4), 2) + val data2 = sc.makeRDD(Array("1", "2", "3", "4", "5", "6"), 2) + val data3 = sc.makeRDD(Array(1.0, 2.0), 2) + + val zippedRDD = data1.zipPartitions(data2, data3)(ZippedPartitionsSuite.procZippedData) + + val obtainedSizes = zippedRDD.collect() + val expectedSizes = Array(2, 3, 1, 2, 3, 1) + assert(obtainedSizes.size == 6) + assert(obtainedSizes.zip(expectedSizes).forall(x => x._1 == x._2)) + } +} diff --git a/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala new file mode 100644 index 0000000000..05f8545c7b --- /dev/null +++ b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala @@ -0,0 +1,92 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy + +import java.io.File +import java.util.Date + +import net.liftweb.json.{JsonAST, JsonParser} +import net.liftweb.json.JsonAST.JValue +import org.scalatest.FunSuite + +import org.apache.spark.deploy.DeployMessages.{MasterStateResponse, WorkerStateResponse} +import org.apache.spark.deploy.master.{ApplicationInfo, WorkerInfo} +import org.apache.spark.deploy.worker.ExecutorRunner + +class JsonProtocolSuite extends FunSuite { + test("writeApplicationInfo") { + val output = JsonProtocol.writeApplicationInfo(createAppInfo()) + assertValidJson(output) + } + + test("writeWorkerInfo") { + val output = JsonProtocol.writeWorkerInfo(createWorkerInfo()) + assertValidJson(output) + } + + test("writeApplicationDescription") { + val output = JsonProtocol.writeApplicationDescription(createAppDesc()) + assertValidJson(output) + } + + test("writeExecutorRunner") { + val output = JsonProtocol.writeExecutorRunner(createExecutorRunner()) + assertValidJson(output) + } + + test("writeMasterState") { + val workers = Array[WorkerInfo](createWorkerInfo(), createWorkerInfo()) + val activeApps = Array[ApplicationInfo](createAppInfo()) + val completedApps = Array[ApplicationInfo]() + val stateResponse = new MasterStateResponse("host", 8080, workers, activeApps, completedApps) + val output = JsonProtocol.writeMasterState(stateResponse) + assertValidJson(output) + } + + test("writeWorkerState") { + val executors = List[ExecutorRunner]() + val finishedExecutors = List[ExecutorRunner](createExecutorRunner(), createExecutorRunner()) + val stateResponse = new WorkerStateResponse("host", 8080, "workerId", executors, + finishedExecutors, "masterUrl", 4, 1234, 4, 1234, "masterWebUiUrl") + val output = JsonProtocol.writeWorkerState(stateResponse) + assertValidJson(output) + } + + def createAppDesc() : ApplicationDescription = { + val cmd = new Command("mainClass", List("arg1", "arg2"), Map()) + new ApplicationDescription("name", 4, 1234, cmd, "sparkHome", "appUiUrl") + } + def createAppInfo() : ApplicationInfo = { + new ApplicationInfo(3, "id", createAppDesc(), new Date(123456789), null, "appUriStr") + } + def createWorkerInfo() : WorkerInfo = { + new WorkerInfo("id", "host", 8080, 4, 1234, null, 80, "publicAddress") + } + def createExecutorRunner() : ExecutorRunner = { + new ExecutorRunner("appId", 123, createAppDesc(), 4, 1234, null, "workerId", "host", + new File("sparkHome"), new File("workDir")) + } + + def assertValidJson(json: JValue) { + try { + JsonParser.parse(JsonAST.compactRender(json)) + } catch { + case e: JsonParser.ParseException => fail("Invalid Json detected", e) + } + } +} diff --git a/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala b/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala new file mode 100644 index 0000000000..ab81bfbe55 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala @@ -0,0 +1,62 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.io + +import java.io.{ByteArrayInputStream, ByteArrayOutputStream} + +import org.scalatest.FunSuite + + +class CompressionCodecSuite extends FunSuite { + + def testCodec(codec: CompressionCodec) { + // Write 1000 integers to the output stream, compressed. + val outputStream = new ByteArrayOutputStream() + val out = codec.compressedOutputStream(outputStream) + for (i <- 1 until 1000) { + out.write(i % 256) + } + out.close() + + // Read the 1000 integers back. + val inputStream = new ByteArrayInputStream(outputStream.toByteArray) + val in = codec.compressedInputStream(inputStream) + for (i <- 1 until 1000) { + assert(in.read() === i % 256) + } + in.close() + } + + test("default compression codec") { + val codec = CompressionCodec.createCodec() + assert(codec.getClass === classOf[LZFCompressionCodec]) + testCodec(codec) + } + + test("lzf compression codec") { + val codec = CompressionCodec.createCodec(classOf[LZFCompressionCodec].getName) + assert(codec.getClass === classOf[LZFCompressionCodec]) + testCodec(codec) + } + + test("snappy compression codec") { + val codec = CompressionCodec.createCodec(classOf[SnappyCompressionCodec].getName) + assert(codec.getClass === classOf[SnappyCompressionCodec]) + testCodec(codec) + } +} diff --git a/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala b/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala new file mode 100644 index 0000000000..58c94a162d --- /dev/null +++ b/core/src/test/scala/org/apache/spark/metrics/MetricsConfigSuite.scala @@ -0,0 +1,89 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics + +import org.scalatest.{BeforeAndAfter, FunSuite} + +class MetricsConfigSuite extends FunSuite with BeforeAndAfter { + var filePath: String = _ + + before { + filePath = getClass.getClassLoader.getResource("test_metrics_config.properties").getFile() + } + + test("MetricsConfig with default properties") { + val conf = new MetricsConfig(Option("dummy-file")) + conf.initialize() + + assert(conf.properties.size() === 5) + assert(conf.properties.getProperty("test-for-dummy") === null) + + val property = conf.getInstance("random") + assert(property.size() === 3) + assert(property.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet") + assert(property.getProperty("sink.servlet.uri") === "/metrics/json") + assert(property.getProperty("sink.servlet.sample") === "false") + } + + test("MetricsConfig with properties set") { + val conf = new MetricsConfig(Option(filePath)) + conf.initialize() + + val masterProp = conf.getInstance("master") + assert(masterProp.size() === 6) + assert(masterProp.getProperty("sink.console.period") === "20") + assert(masterProp.getProperty("sink.console.unit") === "minutes") + assert(masterProp.getProperty("source.jvm.class") === "org.apache.spark.metrics.source.JvmSource") + assert(masterProp.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet") + assert(masterProp.getProperty("sink.servlet.uri") === "/metrics/master/json") + assert(masterProp.getProperty("sink.servlet.sample") === "false") + + val workerProp = conf.getInstance("worker") + assert(workerProp.size() === 6) + assert(workerProp.getProperty("sink.console.period") === "10") + assert(workerProp.getProperty("sink.console.unit") === "seconds") + assert(workerProp.getProperty("source.jvm.class") === "org.apache.spark.metrics.source.JvmSource") + assert(workerProp.getProperty("sink.servlet.class") === "org.apache.spark.metrics.sink.MetricsServlet") + assert(workerProp.getProperty("sink.servlet.uri") === "/metrics/json") + assert(workerProp.getProperty("sink.servlet.sample") === "false") + } + + test("MetricsConfig with subProperties") { + val conf = new MetricsConfig(Option(filePath)) + conf.initialize() + + val propCategories = conf.propertyCategories + assert(propCategories.size === 3) + + val masterProp = conf.getInstance("master") + val sourceProps = conf.subProperties(masterProp, MetricsSystem.SOURCE_REGEX) + assert(sourceProps.size === 1) + assert(sourceProps("jvm").getProperty("class") === "org.apache.spark.metrics.source.JvmSource") + + val sinkProps = conf.subProperties(masterProp, MetricsSystem.SINK_REGEX) + assert(sinkProps.size === 2) + assert(sinkProps.contains("console")) + assert(sinkProps.contains("servlet")) + + val consoleProps = sinkProps("console") + assert(consoleProps.size() === 2) + + val servletProps = sinkProps("servlet") + assert(servletProps.size() === 3) + } +} diff --git a/core/src/test/scala/org/apache/spark/metrics/MetricsSystemSuite.scala b/core/src/test/scala/org/apache/spark/metrics/MetricsSystemSuite.scala new file mode 100644 index 0000000000..7181333adf --- /dev/null +++ b/core/src/test/scala/org/apache/spark/metrics/MetricsSystemSuite.scala @@ -0,0 +1,54 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.metrics + +import org.scalatest.{BeforeAndAfter, FunSuite} +import org.apache.spark.deploy.master.MasterSource + +class MetricsSystemSuite extends FunSuite with BeforeAndAfter { + var filePath: String = _ + + before { + filePath = getClass.getClassLoader.getResource("test_metrics_system.properties").getFile() + System.setProperty("spark.metrics.conf", filePath) + } + + test("MetricsSystem with default config") { + val metricsSystem = MetricsSystem.createMetricsSystem("default") + val sources = metricsSystem.sources + val sinks = metricsSystem.sinks + + assert(sources.length === 0) + assert(sinks.length === 0) + assert(!metricsSystem.getServletHandlers.isEmpty) + } + + test("MetricsSystem with sources add") { + val metricsSystem = MetricsSystem.createMetricsSystem("test") + val sources = metricsSystem.sources + val sinks = metricsSystem.sinks + + assert(sources.length === 0) + assert(sinks.length === 1) + assert(!metricsSystem.getServletHandlers.isEmpty) + + val source = new MasterSource(null) + metricsSystem.registerSource(source) + assert(sources.length === 1) + } +} diff --git a/core/src/test/scala/spark/rdd/JdbcRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala index 6afb0fa9bc..3d39a31252 100644 --- a/core/src/test/scala/spark/rdd/JdbcRDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala @@ -1,8 +1,25 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark import org.scalatest.{ BeforeAndAfter, FunSuite } -import spark.SparkContext._ -import spark.rdd.JdbcRDD +import org.apache.spark.SparkContext._ +import org.apache.spark.rdd.JdbcRDD import java.sql._ class JdbcRDDSuite extends FunSuite with BeforeAndAfter with LocalSparkContext { diff --git a/core/src/test/scala/spark/PairRDDFunctionsSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala index 682d2745bf..31f97fc139 100644 --- a/core/src/test/scala/spark/PairRDDFunctionsSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/PairRDDFunctionsSuite.scala @@ -1,18 +1,31 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashSet import org.scalatest.FunSuite -import org.scalatest.prop.Checkers -import org.scalacheck.Arbitrary._ -import org.scalacheck.Gen -import org.scalacheck.Prop._ import com.google.common.io.Files +import org.apache.spark.SparkContext._ +import org.apache.spark.{Partitioner, SharedSparkContext} -import spark.rdd.ShuffledRDD -import spark.SparkContext._ class PairRDDFunctionsSuite extends FunSuite with SharedSparkContext { test("groupByKey") { diff --git a/core/src/test/scala/spark/rdd/ParallelCollectionSplitSuite.scala b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala index d27a2538e4..a80afdee7e 100644 --- a/core/src/test/scala/spark/rdd/ParallelCollectionSplitSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala @@ -1,4 +1,21 @@ -package spark.rdd +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.collection.immutable.NumericRange diff --git a/core/src/test/scala/spark/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala index aa3ee5f5ee..adc971050e 100644 --- a/core/src/test/scala/spark/RDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala @@ -1,11 +1,31 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import scala.collection.mutable.HashMap import org.scalatest.FunSuite import org.scalatest.concurrent.Timeouts._ import org.scalatest.time.{Span, Millis} -import spark.SparkContext._ -import spark.rdd.{CoalescedRDD, CoGroupedRDD, EmptyRDD, PartitionPruningRDD, ShuffledRDD} +import org.apache.spark.SparkContext._ +import org.apache.spark.rdd._ +import scala.collection.parallel.mutable +import org.apache.spark._ +import org.apache.spark.rdd.CoalescedRDDPartition class RDDSuite extends FunSuite with SharedSparkContext { @@ -153,9 +173,69 @@ class RDDSuite extends FunSuite with SharedSparkContext { // we can optionally shuffle to keep the upstream parallel val coalesced5 = data.coalesce(1, shuffle = true) - assert(coalesced5.dependencies.head.rdd.dependencies.head.rdd.asInstanceOf[ShuffledRDD[_, _]] != + assert(coalesced5.dependencies.head.rdd.dependencies.head.rdd.asInstanceOf[ShuffledRDD[_, _, _]] != null) } + test("cogrouped RDDs with locality") { + val data3 = sc.makeRDD(List((1,List("a","c")), (2,List("a","b","c")), (3,List("b")))) + val coal3 = data3.coalesce(3) + val list3 = coal3.partitions.map(p => p.asInstanceOf[CoalescedRDDPartition].preferredLocation) + assert(list3.sorted === Array("a","b","c"), "Locality preferences are dropped") + + // RDD with locality preferences spread (non-randomly) over 6 machines, m0 through m5 + val data = sc.makeRDD((1 to 9).map(i => (i, (i to (i+2)).map{ j => "m" + (j%6)}))) + val coalesced1 = data.coalesce(3) + assert(coalesced1.collect().toList.sorted === (1 to 9).toList, "Data got *lost* in coalescing") + + val splits = coalesced1.glom().collect().map(_.toList).toList + assert(splits.length === 3, "Supposed to coalesce to 3 but got " + splits.length) + + assert(splits.forall(_.length >= 1) === true, "Some partitions were empty") + + // If we try to coalesce into more partitions than the original RDD, it should just + // keep the original number of partitions. + val coalesced4 = data.coalesce(20) + val listOfLists = coalesced4.glom().collect().map(_.toList).toList + val sortedList = listOfLists.sortWith{ (x, y) => !x.isEmpty && (y.isEmpty || (x(0) < y(0))) } + assert( sortedList === (1 to 9). + map{x => List(x)}.toList, "Tried coalescing 9 partitions to 20 but didn't get 9 back") + } + + test("cogrouped RDDs with locality, large scale (10K partitions)") { + // large scale experiment + import collection.mutable + val rnd = scala.util.Random + val partitions = 10000 + val numMachines = 50 + val machines = mutable.ListBuffer[String]() + (1 to numMachines).foreach(machines += "m"+_) + + val blocks = (1 to partitions).map(i => + { (i, Array.fill(3)(machines(rnd.nextInt(machines.size))).toList) } ) + + val data2 = sc.makeRDD(blocks) + val coalesced2 = data2.coalesce(numMachines*2) + + // test that you get over 90% locality in each group + val minLocality = coalesced2.partitions + .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction) + .foldLeft(1.)((perc, loc) => math.min(perc,loc)) + assert(minLocality >= 0.90, "Expected 90% locality but got " + (minLocality*100.).toInt + "%") + + // test that the groups are load balanced with 100 +/- 20 elements in each + val maxImbalance = coalesced2.partitions + .map(part => part.asInstanceOf[CoalescedRDDPartition].parents.size) + .foldLeft(0)((dev, curr) => math.max(math.abs(100-curr),dev)) + assert(maxImbalance <= 20, "Expected 100 +/- 20 per partition, but got " + maxImbalance) + + val data3 = sc.makeRDD(blocks).map(i => i*2) // derived RDD to test *current* pref locs + val coalesced3 = data3.coalesce(numMachines*2) + val minLocality2 = coalesced3.partitions + .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction) + .foldLeft(1.)((perc, loc) => math.min(perc,loc)) + assert(minLocality2 >= 0.90, "Expected 90% locality for derived RDD but got " + + (minLocality2*100.).toInt + "%") + } test("zipped RDDs") { val nums = sc.makeRDD(Array(1, 2, 3, 4), 2) @@ -302,4 +382,10 @@ class RDDSuite extends FunSuite with SharedSparkContext { assert(sample.toSet.size < 100, "sampling with replacement returned all distinct elements") } } + + test("runJob on an invalid partition") { + intercept[IllegalArgumentException] { + sc.runJob(sc.parallelize(1 to 10, 2), {iter: Iterator[Int] => iter.size}, Seq(0, 1, 2), false) + } + } } diff --git a/core/src/test/scala/spark/SortingSuite.scala b/core/src/test/scala/org/apache/spark/rdd/SortingSuite.scala index f7bf207c68..2f7bd370fc 100644 --- a/core/src/test/scala/spark/SortingSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/SortingSuite.scala @@ -1,9 +1,28 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rdd import org.scalatest.FunSuite import org.scalatest.BeforeAndAfter import org.scalatest.matchers.ShouldMatchers -import SparkContext._ + +import org.apache.spark.{Logging, SharedSparkContext} +import org.apache.spark.SparkContext._ class SortingSuite extends FunSuite with SharedSparkContext with ShouldMatchers with Logging { diff --git a/core/src/test/scala/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala index 30e6fef950..94f66c94c6 100644 --- a/core/src/test/scala/spark/scheduler/DAGSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala @@ -1,26 +1,40 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import scala.collection.mutable.{Map, HashMap} import org.scalatest.FunSuite import org.scalatest.BeforeAndAfter -import spark.LocalSparkContext +import org.apache.spark.LocalSparkContext +import org.apache.spark.MapOutputTracker +import org.apache.spark.rdd.RDD +import org.apache.spark.SparkContext +import org.apache.spark.Partition +import org.apache.spark.TaskContext +import org.apache.spark.{Dependency, ShuffleDependency, OneToOneDependency} +import org.apache.spark.{FetchFailed, Success, TaskEndReason} +import org.apache.spark.storage.{BlockManagerId, BlockManagerMaster} -import spark.storage.BlockManager -import spark.storage.BlockManagerId -import spark.storage.BlockManagerMaster -import spark.{Dependency, ShuffleDependency, OneToOneDependency} -import spark.FetchFailedException -import spark.MapOutputTracker -import spark.RDD -import spark.SparkContext -import spark.SparkException -import spark.Partition -import spark.TaskContext -import spark.TaskEndReason - -import spark.{FetchFailed, Success} +import org.apache.spark.scheduler.cluster.Pool +import org.apache.spark.scheduler.cluster.SchedulingMode +import org.apache.spark.scheduler.cluster.SchedulingMode.SchedulingMode /** * Tests for DAGScheduler. These tests directly call the event processing functions in DAGScheduler @@ -39,11 +53,13 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont /** Set of TaskSets the DAGScheduler has requested executed. */ val taskSets = scala.collection.mutable.Buffer[TaskSet]() val taskScheduler = new TaskScheduler() { + override def rootPool: Pool = null + override def schedulingMode: SchedulingMode = SchedulingMode.NONE override def start() = {} override def stop() = {} override def submitTasks(taskSet: TaskSet) = { // normally done by TaskSetManager - taskSet.tasks.foreach(_.generation = mapOutputTracker.getGeneration) + taskSet.tasks.foreach(_.epoch = mapOutputTracker.getEpoch) taskSets += taskSet } override def setListener(listener: TaskSchedulerListener) = {} @@ -283,10 +299,10 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont val reduceRdd = makeRdd(2, List(shuffleDep)) submit(reduceRdd, Array(0, 1)) // pretend we were told hostA went away - val oldGeneration = mapOutputTracker.getGeneration + val oldEpoch = mapOutputTracker.getEpoch runEvent(ExecutorLost("exec-hostA")) - val newGeneration = mapOutputTracker.getGeneration - assert(newGeneration > oldGeneration) + val newEpoch = mapOutputTracker.getEpoch + assert(newEpoch > oldEpoch) val noAccum = Map[Long, Any]() val taskSet = taskSets(0) // should be ignored for being too old @@ -295,8 +311,8 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont runEvent(CompletionEvent(taskSet.tasks(0), Success, makeMapStatus("hostB", 1), noAccum, null, null)) // should be ignored for being too old runEvent(CompletionEvent(taskSet.tasks(0), Success, makeMapStatus("hostA", 1), noAccum, null, null)) - // should work because it's a new generation - taskSet.tasks(1).generation = newGeneration + // should work because it's a new epoch + taskSet.tasks(1).epoch = newEpoch runEvent(CompletionEvent(taskSet.tasks(1), Success, makeMapStatus("hostA", 1), noAccum, null, null)) assert(mapOutputTracker.getServerStatuses(shuffleId, 0).map(_._1) === Array(makeBlockManagerId("hostB"), makeBlockManagerId("hostA"))) @@ -385,12 +401,14 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont assert(results === Map(0 -> 42)) } - /** Assert that the supplied TaskSet has exactly the given preferredLocations. Note, converts taskSet's locations to host only. */ - private def assertLocations(taskSet: TaskSet, locations: Seq[Seq[String]]) { - assert(locations.size === taskSet.tasks.size) - for ((expectLocs, taskLocs) <- - taskSet.tasks.map(_.preferredLocations).zip(locations)) { - assert(expectLocs.map(loc => spark.Utils.parseHostPort(loc)._1) === taskLocs) + /** + * Assert that the supplied TaskSet has exactly the given hosts as its preferred locations. + * Note that this checks only the host and not the executor ID. + */ + private def assertLocations(taskSet: TaskSet, hosts: Seq[Seq[String]]) { + assert(hosts.size === taskSet.tasks.size) + for ((taskLocs, expectedLocs) <- taskSet.tasks.map(_.preferredLocations).zip(hosts)) { + assert(taskLocs.map(_.host) === expectedLocs) } } diff --git a/core/src/test/scala/spark/scheduler/JobLoggerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala index 699901f1a1..cece60dda7 100644 --- a/core/src/test/scala/spark/scheduler/JobLoggerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala @@ -1,12 +1,33 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import java.util.Properties import java.util.concurrent.LinkedBlockingQueue + +import scala.collection.mutable + import org.scalatest.FunSuite import org.scalatest.matchers.ShouldMatchers -import scala.collection.mutable -import spark._ -import spark.SparkContext._ + +import org.apache.spark._ +import org.apache.spark.SparkContext._ +import org.apache.spark.rdd.RDD class JobLoggerSuite extends FunSuite with LocalSparkContext with ShouldMatchers { @@ -37,10 +58,10 @@ class JobLoggerSuite extends FunSuite with LocalSparkContext with ShouldMatchers val parentRdd = makeRdd(4, Nil) val shuffleDep = new ShuffleDependency(parentRdd, null) val rootRdd = makeRdd(4, List(shuffleDep)) - val shuffleMapStage = new Stage(1, parentRdd, Some(shuffleDep), Nil, jobID) - val rootStage = new Stage(0, rootRdd, None, List(shuffleMapStage), jobID) + val shuffleMapStage = new Stage(1, parentRdd, Some(shuffleDep), Nil, jobID, None) + val rootStage = new Stage(0, rootRdd, None, List(shuffleMapStage), jobID, None) - joblogger.onStageSubmitted(SparkListenerStageSubmitted(rootStage, 4)) + joblogger.onStageSubmitted(SparkListenerStageSubmitted(rootStage, 4, null)) joblogger.getRddNameTest(parentRdd) should be (parentRdd.getClass.getName) parentRdd.setName("MyRDD") joblogger.getRddNameTest(parentRdd) should be ("MyRDD") diff --git a/core/src/test/scala/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala index 48aa67c543..aac7c207cb 100644 --- a/core/src/test/scala/spark/scheduler/SparkListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala @@ -1,10 +1,27 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler import org.scalatest.FunSuite -import spark.{SparkContext, LocalSparkContext} +import org.apache.spark.{SparkContext, LocalSparkContext} import scala.collection.mutable import org.scalatest.matchers.ShouldMatchers -import spark.SparkContext._ +import org.apache.spark.SparkContext._ /** * diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala new file mode 100644 index 0000000000..e31a116a75 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala @@ -0,0 +1,49 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.scalatest.FunSuite +import org.scalatest.BeforeAndAfter +import org.apache.spark.TaskContext +import org.apache.spark.rdd.RDD +import org.apache.spark.SparkContext +import org.apache.spark.Partition +import org.apache.spark.LocalSparkContext + +class TaskContextSuite extends FunSuite with BeforeAndAfter with LocalSparkContext { + + test("Calls executeOnCompleteCallbacks after failure") { + var completed = false + sc = new SparkContext("local", "test") + val rdd = new RDD[String](sc, List()) { + override def getPartitions = Array[Partition](StubPartition(0)) + override def compute(split: Partition, context: TaskContext) = { + context.addOnCompleteCallback(() => completed = true) + sys.error("failed") + } + } + val func = (c: TaskContext, i: Iterator[String]) => i.next + val task = new ResultTask[String, String](0, rdd, func, 0, Seq(), 0) + intercept[RuntimeException] { + task.run(0) + } + assert(completed === true) + } + + case class StubPartition(val index: Int) extends Partition +} diff --git a/core/src/test/scala/spark/scheduler/ClusterSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/cluster/ClusterSchedulerSuite.scala index 8e1ad27e14..92ad9f09b2 100644 --- a/core/src/test/scala/spark/scheduler/ClusterSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/cluster/ClusterSchedulerSuite.scala @@ -1,22 +1,39 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster import org.scalatest.FunSuite import org.scalatest.BeforeAndAfter -import spark._ -import spark.scheduler._ -import spark.scheduler.cluster._ +import org.apache.spark._ +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster._ import scala.collection.mutable.ArrayBuffer import java.util.Properties -class DummyTaskSetManager( +class FakeTaskSetManager( initPriority: Int, initStageId: Int, initNumTasks: Int, clusterScheduler: ClusterScheduler, taskSet: TaskSet) - extends ClusterTaskSetManager(clusterScheduler,taskSet) { + extends ClusterTaskSetManager(clusterScheduler, taskSet) { parent = null weight = 1 @@ -55,10 +72,16 @@ class DummyTaskSetManager( override def executorLost(executorId: String, host: String): Unit = { } - override def slaveOffer(execId: String, host: String, avaiableCpus: Double, overrideLocality: TaskLocality.TaskLocality = null): Option[TaskDescription] = { + override def resourceOffer( + execId: String, + host: String, + availableCpus: Int, + maxLocality: TaskLocality.TaskLocality) + : Option[TaskDescription] = + { if (tasksFinished + runningTasks < numTasks) { increaseRunningTasks(1) - return Some(new TaskDescription(0, execId, "task 0:0", null)) + return Some(new TaskDescription(0, execId, "task 0:0", 0, null)) } return None } @@ -81,17 +104,10 @@ class DummyTaskSetManager( } } -class DummyTask(stageId: Int) extends Task[Int](stageId) -{ - def run(attemptId: Long): Int = { - return 0 - } -} - class ClusterSchedulerSuite extends FunSuite with LocalSparkContext with Logging { - def createDummyTaskSetManager(priority: Int, stage: Int, numTasks: Int, cs: ClusterScheduler, taskSet: TaskSet): DummyTaskSetManager = { - new DummyTaskSetManager(priority, stage, numTasks, cs , taskSet) + def createDummyTaskSetManager(priority: Int, stage: Int, numTasks: Int, cs: ClusterScheduler, taskSet: TaskSet): FakeTaskSetManager = { + new FakeTaskSetManager(priority, stage, numTasks, cs , taskSet) } def resourceOffer(rootPool: Pool): Int = { @@ -101,7 +117,7 @@ class ClusterSchedulerSuite extends FunSuite with LocalSparkContext with Logging logInfo("parentName:%s, parent running tasks:%d, name:%s,runningTasks:%d".format(manager.parent.name, manager.parent.runningTasks, manager.name, manager.runningTasks)) } for (taskSet <- taskSetQueue) { - taskSet.slaveOffer("execId_1", "hostname_1", 1) match { + taskSet.resourceOffer("execId_1", "hostname_1", 1, TaskLocality.ANY) match { case Some(task) => return taskSet.stageId case None => {} @@ -118,7 +134,7 @@ class ClusterSchedulerSuite extends FunSuite with LocalSparkContext with Logging sc = new SparkContext("local", "ClusterSchedulerSuite") val clusterScheduler = new ClusterScheduler(sc) var tasks = ArrayBuffer[Task[_]]() - val task = new DummyTask(0) + val task = new FakeTask(0) tasks += task val taskSet = new TaskSet(tasks.toArray,0,0,0,null) @@ -145,7 +161,7 @@ class ClusterSchedulerSuite extends FunSuite with LocalSparkContext with Logging sc = new SparkContext("local", "ClusterSchedulerSuite") val clusterScheduler = new ClusterScheduler(sc) var tasks = ArrayBuffer[Task[_]]() - val task = new DummyTask(0) + val task = new FakeTask(0) tasks += task val taskSet = new TaskSet(tasks.toArray,0,0,0,null) @@ -202,7 +218,7 @@ class ClusterSchedulerSuite extends FunSuite with LocalSparkContext with Logging sc = new SparkContext("local", "ClusterSchedulerSuite") val clusterScheduler = new ClusterScheduler(sc) var tasks = ArrayBuffer[Task[_]]() - val task = new DummyTask(0) + val task = new FakeTask(0) tasks += task val taskSet = new TaskSet(tasks.toArray,0,0,0,null) diff --git a/core/src/test/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManagerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManagerSuite.scala new file mode 100644 index 0000000000..ff70a2cdf0 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManagerSuite.scala @@ -0,0 +1,273 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable + +import org.scalatest.FunSuite + +import org.apache.spark._ +import org.apache.spark.scheduler._ +import org.apache.spark.executor.TaskMetrics +import java.nio.ByteBuffer +import org.apache.spark.util.{Utils, FakeClock} + +/** + * A mock ClusterScheduler implementation that just remembers information about tasks started and + * feedback received from the TaskSetManagers. Note that it's important to initialize this with + * a list of "live" executors and their hostnames for isExecutorAlive and hasExecutorsAliveOnHost + * to work, and these are required for locality in ClusterTaskSetManager. + */ +class FakeClusterScheduler(sc: SparkContext, liveExecutors: (String, String)* /* execId, host */) + extends ClusterScheduler(sc) +{ + val startedTasks = new ArrayBuffer[Long] + val endedTasks = new mutable.HashMap[Long, TaskEndReason] + val finishedManagers = new ArrayBuffer[TaskSetManager] + + val executors = new mutable.HashMap[String, String] ++ liveExecutors + + listener = new TaskSchedulerListener { + def taskStarted(task: Task[_], taskInfo: TaskInfo) { + startedTasks += taskInfo.index + } + + def taskEnded( + task: Task[_], + reason: TaskEndReason, + result: Any, + accumUpdates: mutable.Map[Long, Any], + taskInfo: TaskInfo, + taskMetrics: TaskMetrics) + { + endedTasks(taskInfo.index) = reason + } + + def executorGained(execId: String, host: String) {} + + def executorLost(execId: String) {} + + def taskSetFailed(taskSet: TaskSet, reason: String) {} + } + + def removeExecutor(execId: String): Unit = executors -= execId + + override def taskSetFinished(manager: TaskSetManager): Unit = finishedManagers += manager + + override def isExecutorAlive(execId: String): Boolean = executors.contains(execId) + + override def hasExecutorsAliveOnHost(host: String): Boolean = executors.values.exists(_ == host) +} + +class ClusterTaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging { + import TaskLocality.{ANY, PROCESS_LOCAL, NODE_LOCAL, RACK_LOCAL} + + val LOCALITY_WAIT = System.getProperty("spark.locality.wait", "3000").toLong + + test("TaskSet with no preferences") { + sc = new SparkContext("local", "test") + val sched = new FakeClusterScheduler(sc, ("exec1", "host1")) + val taskSet = createTaskSet(1) + val manager = new ClusterTaskSetManager(sched, taskSet) + + // Offer a host with no CPUs + assert(manager.resourceOffer("exec1", "host1", 0, ANY) === None) + + // Offer a host with process-local as the constraint; this should work because the TaskSet + // above won't have any locality preferences + val taskOption = manager.resourceOffer("exec1", "host1", 2, TaskLocality.PROCESS_LOCAL) + assert(taskOption.isDefined) + val task = taskOption.get + assert(task.executorId === "exec1") + assert(sched.startedTasks.contains(0)) + + // Re-offer the host -- now we should get no more tasks + assert(manager.resourceOffer("exec1", "host1", 2, PROCESS_LOCAL) === None) + + // Tell it the task has finished + manager.statusUpdate(0, TaskState.FINISHED, createTaskResult(0)) + assert(sched.endedTasks(0) === Success) + assert(sched.finishedManagers.contains(manager)) + } + + test("multiple offers with no preferences") { + sc = new SparkContext("local", "test") + val sched = new FakeClusterScheduler(sc, ("exec1", "host1")) + val taskSet = createTaskSet(3) + val manager = new ClusterTaskSetManager(sched, taskSet) + + // First three offers should all find tasks + for (i <- 0 until 3) { + val taskOption = manager.resourceOffer("exec1", "host1", 1, PROCESS_LOCAL) + assert(taskOption.isDefined) + val task = taskOption.get + assert(task.executorId === "exec1") + } + assert(sched.startedTasks.toSet === Set(0, 1, 2)) + + // Re-offer the host -- now we should get no more tasks + assert(manager.resourceOffer("exec1", "host1", 1, PROCESS_LOCAL) === None) + + // Finish the first two tasks + manager.statusUpdate(0, TaskState.FINISHED, createTaskResult(0)) + manager.statusUpdate(1, TaskState.FINISHED, createTaskResult(1)) + assert(sched.endedTasks(0) === Success) + assert(sched.endedTasks(1) === Success) + assert(!sched.finishedManagers.contains(manager)) + + // Finish the last task + manager.statusUpdate(2, TaskState.FINISHED, createTaskResult(2)) + assert(sched.endedTasks(2) === Success) + assert(sched.finishedManagers.contains(manager)) + } + + test("basic delay scheduling") { + sc = new SparkContext("local", "test") + val sched = new FakeClusterScheduler(sc, ("exec1", "host1"), ("exec2", "host2")) + val taskSet = createTaskSet(4, + Seq(TaskLocation("host1", "exec1")), + Seq(TaskLocation("host2", "exec2")), + Seq(TaskLocation("host1"), TaskLocation("host2", "exec2")), + Seq() // Last task has no locality prefs + ) + val clock = new FakeClock + val manager = new ClusterTaskSetManager(sched, taskSet, clock) + + // First offer host1, exec1: first task should be chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 0) + + // Offer host1, exec1 again: the last task, which has no prefs, should be chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 3) + + // Offer host1, exec1 again, at PROCESS_LOCAL level: nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, PROCESS_LOCAL) === None) + + clock.advance(LOCALITY_WAIT) + + // Offer host1, exec1 again, at PROCESS_LOCAL level: nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, PROCESS_LOCAL) === None) + + // Offer host1, exec1 again, at NODE_LOCAL level: we should choose task 2 + assert(manager.resourceOffer("exec1", "host1", 1, NODE_LOCAL).get.index == 2) + + // Offer host1, exec1 again, at NODE_LOCAL level: nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, NODE_LOCAL) === None) + + // Offer host1, exec1 again, at ANY level: nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY) === None) + + clock.advance(LOCALITY_WAIT) + + // Offer host1, exec1 again, at ANY level: task 1 should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 1) + + // Offer host1, exec1 again, at ANY level: nothing should be chosen as we've launched all tasks + assert(manager.resourceOffer("exec1", "host1", 1, ANY) === None) + } + + test("delay scheduling with fallback") { + sc = new SparkContext("local", "test") + val sched = new FakeClusterScheduler(sc, + ("exec1", "host1"), ("exec2", "host2"), ("exec3", "host3")) + val taskSet = createTaskSet(5, + Seq(TaskLocation("host1")), + Seq(TaskLocation("host2")), + Seq(TaskLocation("host2")), + Seq(TaskLocation("host3")), + Seq(TaskLocation("host2")) + ) + val clock = new FakeClock + val manager = new ClusterTaskSetManager(sched, taskSet, clock) + + // First offer host1: first task should be chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 0) + + // Offer host1 again: nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY) === None) + + clock.advance(LOCALITY_WAIT) + + // Offer host1 again: second task (on host2) should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 1) + + // Offer host1 again: third task (on host2) should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 2) + + // Offer host2: fifth task (also on host2) should get chosen + assert(manager.resourceOffer("exec2", "host2", 1, ANY).get.index === 4) + + // Now that we've launched a local task, we should no longer launch the task for host3 + assert(manager.resourceOffer("exec2", "host2", 1, ANY) === None) + + clock.advance(LOCALITY_WAIT) + + // After another delay, we can go ahead and launch that task non-locally + assert(manager.resourceOffer("exec2", "host2", 1, ANY).get.index === 3) + } + + test("delay scheduling with failed hosts") { + sc = new SparkContext("local", "test") + val sched = new FakeClusterScheduler(sc, ("exec1", "host1"), ("exec2", "host2")) + val taskSet = createTaskSet(3, + Seq(TaskLocation("host1")), + Seq(TaskLocation("host2")), + Seq(TaskLocation("host3")) + ) + val clock = new FakeClock + val manager = new ClusterTaskSetManager(sched, taskSet, clock) + + // First offer host1: first task should be chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 0) + + // Offer host1 again: third task should be chosen immediately because host3 is not up + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 2) + + // After this, nothing should get chosen + assert(manager.resourceOffer("exec1", "host1", 1, ANY) === None) + + // Now mark host2 as dead + sched.removeExecutor("exec2") + manager.executorLost("exec2", "host2") + + // Task 1 should immediately be launched on host1 because its original host is gone + assert(manager.resourceOffer("exec1", "host1", 1, ANY).get.index === 1) + + // Now that all tasks have launched, nothing new should be launched anywhere else + assert(manager.resourceOffer("exec1", "host1", 1, ANY) === None) + assert(manager.resourceOffer("exec2", "host2", 1, ANY) === None) + } + + /** + * Utility method to create a TaskSet, potentially setting a particular sequence of preferred + * locations for each task (given as varargs) if this sequence is not empty. + */ + def createTaskSet(numTasks: Int, prefLocs: Seq[TaskLocation]*): TaskSet = { + if (prefLocs.size != 0 && prefLocs.size != numTasks) { + throw new IllegalArgumentException("Wrong number of task locations") + } + val tasks = Array.tabulate[Task[_]](numTasks) { i => + new FakeTask(i, if (prefLocs.size != 0) prefLocs(i) else Nil) + } + new TaskSet(tasks, 0, 0, 0, null) + } + + def createTaskResult(id: Int): ByteBuffer = { + ByteBuffer.wrap(Utils.serialize(new TaskResult[Int](id, mutable.Map.empty, new TaskMetrics))) + } +} diff --git a/core/src/test/scala/org/apache/spark/scheduler/cluster/FakeTask.scala b/core/src/test/scala/org/apache/spark/scheduler/cluster/FakeTask.scala new file mode 100644 index 0000000000..2f12aaed18 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/scheduler/cluster/FakeTask.scala @@ -0,0 +1,26 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster + +import org.apache.spark.scheduler.{TaskLocation, Task} + +class FakeTask(stageId: Int, prefLocs: Seq[TaskLocation] = Nil) extends Task[Int](stageId) { + override def run(attemptId: Long): Int = 0 + + override def preferredLocations: Seq[TaskLocation] = prefLocs +} diff --git a/core/src/test/scala/spark/scheduler/LocalSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/local/LocalSchedulerSuite.scala index 8bd813fd14..111340a65c 100644 --- a/core/src/test/scala/spark/scheduler/LocalSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/local/LocalSchedulerSuite.scala @@ -1,11 +1,28 @@ -package spark.scheduler +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.local import org.scalatest.FunSuite import org.scalatest.BeforeAndAfter -import spark._ -import spark.scheduler._ -import spark.scheduler.cluster._ +import org.apache.spark._ +import org.apache.spark.scheduler._ +import org.apache.spark.scheduler.cluster._ import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.{ConcurrentMap, HashMap} import java.util.concurrent.Semaphore @@ -40,23 +57,23 @@ object TaskThreadInfo { * 1. each thread contains one job. * 2. each job contains one stage. * 3. each stage only contains one task. - * 4. each task(launched) must be lanched orderly(using threadToStarted) to make sure - * it will get cpu core resource, and will wait to finished after user manually - * release "Lock" and then cluster will contain another free cpu cores. - * 5. each task(pending) must use "sleep" to make sure it has been added to taskSetManager queue, + * 4. each task(launched) must be lanched orderly(using threadToStarted) to make sure + * it will get cpu core resource, and will wait to finished after user manually + * release "Lock" and then cluster will contain another free cpu cores. + * 5. each task(pending) must use "sleep" to make sure it has been added to taskSetManager queue, * thus it will be scheduled later when cluster has free cpu cores. */ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { def createThread(threadIndex: Int, poolName: String, sc: SparkContext, sem: Semaphore) { - + TaskThreadInfo.threadToRunning(threadIndex) = false val nums = sc.parallelize(threadIndex to threadIndex, 1) TaskThreadInfo.threadToLock(threadIndex) = new Lock() TaskThreadInfo.threadToStarted(threadIndex) = new CountDownLatch(1) new Thread { if (poolName != null) { - sc.addLocalProperties("spark.scheduler.cluster.fair.pool",poolName) + sc.setLocalProperty("spark.scheduler.cluster.fair.pool", poolName) } override def run() { val ans = nums.map(number => { @@ -71,7 +88,7 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { } }.start() } - + test("Local FIFO scheduler end-to-end test") { System.setProperty("spark.cluster.schedulingmode", "FIFO") sc = new SparkContext("local[4]", "test") @@ -86,8 +103,8 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { createThread(4,null,sc,sem) TaskThreadInfo.threadToStarted(4).await() // thread 5 and 6 (stage pending)must meet following two points - // 1. stages (taskSetManager) of jobs in thread 5 and 6 should be add to taskSetManager - // queue before executing TaskThreadInfo.threadToLock(1).jobFinished() + // 1. stages (taskSetManager) of jobs in thread 5 and 6 should be add to taskSetManager + // queue before executing TaskThreadInfo.threadToLock(1).jobFinished() // 2. priority of stage in thread 5 should be prior to priority of stage in thread 6 // So I just use "sleep" 1s here for each thread. // TODO: any better solution? @@ -95,24 +112,24 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { Thread.sleep(1000) createThread(6,null,sc,sem) Thread.sleep(1000) - + assert(TaskThreadInfo.threadToRunning(1) === true) assert(TaskThreadInfo.threadToRunning(2) === true) assert(TaskThreadInfo.threadToRunning(3) === true) assert(TaskThreadInfo.threadToRunning(4) === true) assert(TaskThreadInfo.threadToRunning(5) === false) assert(TaskThreadInfo.threadToRunning(6) === false) - + TaskThreadInfo.threadToLock(1).jobFinished() TaskThreadInfo.threadToStarted(5).await() - + assert(TaskThreadInfo.threadToRunning(1) === false) assert(TaskThreadInfo.threadToRunning(2) === true) assert(TaskThreadInfo.threadToRunning(3) === true) assert(TaskThreadInfo.threadToRunning(4) === true) assert(TaskThreadInfo.threadToRunning(5) === true) assert(TaskThreadInfo.threadToRunning(6) === false) - + TaskThreadInfo.threadToLock(3).jobFinished() TaskThreadInfo.threadToStarted(6).await() @@ -122,7 +139,7 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { assert(TaskThreadInfo.threadToRunning(4) === true) assert(TaskThreadInfo.threadToRunning(5) === true) assert(TaskThreadInfo.threadToRunning(6) === true) - + TaskThreadInfo.threadToLock(2).jobFinished() TaskThreadInfo.threadToLock(4).jobFinished() TaskThreadInfo.threadToLock(5).jobFinished() @@ -143,18 +160,18 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { TaskThreadInfo.threadToStarted(20).await() createThread(30,"3",sc,sem) TaskThreadInfo.threadToStarted(30).await() - + assert(TaskThreadInfo.threadToRunning(10) === true) assert(TaskThreadInfo.threadToRunning(20) === true) assert(TaskThreadInfo.threadToRunning(30) === true) - + createThread(11,"1",sc,sem) TaskThreadInfo.threadToStarted(11).await() createThread(21,"2",sc,sem) TaskThreadInfo.threadToStarted(21).await() createThread(31,"3",sc,sem) TaskThreadInfo.threadToStarted(31).await() - + assert(TaskThreadInfo.threadToRunning(11) === true) assert(TaskThreadInfo.threadToRunning(21) === true) assert(TaskThreadInfo.threadToRunning(31) === true) @@ -168,19 +185,19 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { assert(TaskThreadInfo.threadToRunning(12) === true) assert(TaskThreadInfo.threadToRunning(22) === true) assert(TaskThreadInfo.threadToRunning(32) === false) - + TaskThreadInfo.threadToLock(10).jobFinished() TaskThreadInfo.threadToStarted(32).await() - + assert(TaskThreadInfo.threadToRunning(32) === true) - //1. Similar with above scenario, sleep 1s for stage of 23 and 33 to be added to taskSetManager + //1. Similar with above scenario, sleep 1s for stage of 23 and 33 to be added to taskSetManager // queue so that cluster will assign free cpu core to stage 23 after stage 11 finished. //2. priority of 23 and 33 will be meaningless as using fair scheduler here. createThread(23,"2",sc,sem) createThread(33,"3",sc,sem) Thread.sleep(1000) - + TaskThreadInfo.threadToLock(11).jobFinished() TaskThreadInfo.threadToStarted(23).await() @@ -189,7 +206,7 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { TaskThreadInfo.threadToLock(12).jobFinished() TaskThreadInfo.threadToStarted(33).await() - + assert(TaskThreadInfo.threadToRunning(33) === true) TaskThreadInfo.threadToLock(20).jobFinished() @@ -200,7 +217,7 @@ class LocalSchedulerSuite extends FunSuite with LocalSparkContext { TaskThreadInfo.threadToLock(31).jobFinished() TaskThreadInfo.threadToLock(32).jobFinished() TaskThreadInfo.threadToLock(33).jobFinished() - - sem.acquire(11) + + sem.acquire(11) } } diff --git a/core/src/test/scala/spark/KryoSerializerSuite.scala b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala index 327e2ff848..0164dda0ba 100644 --- a/core/src/test/scala/spark/KryoSerializerSuite.scala +++ b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala @@ -1,14 +1,31 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.serializer import scala.collection.mutable -import scala.collection.immutable -import org.scalatest.FunSuite -import com.esotericsoftware.kryo._ +import com.esotericsoftware.kryo.Kryo -import SparkContext._ +import org.scalatest.FunSuite +import org.apache.spark.SharedSparkContext +import org.apache.spark.serializer.KryoTest._ -class KryoSerializerSuite extends FunSuite { +class KryoSerializerSuite extends FunSuite with SharedSparkContext { test("basic types") { val ser = (new KryoSerializer).newInstance() def check[T](t: T) { @@ -36,6 +53,7 @@ class KryoSerializerSuite extends FunSuite { check(Array(true, false, true)) check(Array('a', 'b', 'c')) check(Array[Int]()) + check(Array(Array("1", "2"), Array("1", "2", "3", "4"))) } test("pairs") { @@ -86,7 +104,6 @@ class KryoSerializerSuite extends FunSuite { } test("custom registrator") { - import spark.test._ System.setProperty("spark.kryo.registrator", classOf[MyRegistrator].getName) val ser = (new KryoSerializer).newInstance() @@ -106,14 +123,65 @@ class KryoSerializerSuite extends FunSuite { val hashMap = new java.util.HashMap[String, String] hashMap.put("foo", "bar") check(hashMap) - + System.clearProperty("spark.kryo.registrator") } + + test("kryo with collect") { + val control = 1 :: 2 :: Nil + val result = sc.parallelize(control, 2).map(new ClassWithoutNoArgConstructor(_)).collect().map(_.x) + assert(control === result.toSeq) + } + + test("kryo with parallelize") { + val control = 1 :: 2 :: Nil + val result = sc.parallelize(control.map(new ClassWithoutNoArgConstructor(_))).map(_.x).collect() + assert (control === result.toSeq) + } + + test("kryo with parallelize for specialized tuples") { + assert (sc.parallelize( Array((1, 11), (2, 22), (3, 33)) ).count === 3) + } + + test("kryo with parallelize for primitive arrays") { + assert (sc.parallelize( Array(1, 2, 3) ).count === 3) + } + + test("kryo with collect for specialized tuples") { + assert (sc.parallelize( Array((1, 11), (2, 22), (3, 33)) ).collect().head === (1, 11)) + } + + test("kryo with reduce") { + val control = 1 :: 2 :: Nil + val result = sc.parallelize(control, 2).map(new ClassWithoutNoArgConstructor(_)) + .reduce((t1, t2) => new ClassWithoutNoArgConstructor(t1.x + t2.x)).x + assert(control.sum === result) + } + + // TODO: this still doesn't work + ignore("kryo with fold") { + val control = 1 :: 2 :: Nil + val result = sc.parallelize(control, 2).map(new ClassWithoutNoArgConstructor(_)) + .fold(new ClassWithoutNoArgConstructor(10))((t1, t2) => new ClassWithoutNoArgConstructor(t1.x + t2.x)).x + assert(10 + control.sum === result) + } + + override def beforeAll() { + System.setProperty("spark.serializer", "org.apache.spark.serializer.KryoSerializer") + System.setProperty("spark.kryo.registrator", classOf[MyRegistrator].getName) + super.beforeAll() + } + + override def afterAll() { + super.afterAll() + System.clearProperty("spark.kryo.registrator") + System.clearProperty("spark.serializer") + } } -package test { +object KryoTest { case class CaseClass(i: Int, s: String) {} - + class ClassWithNoArgConstructor { var x: Int = 0 override def equals(other: Any) = other match { diff --git a/core/src/test/scala/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala index b9d5f9668e..038a9acb85 100644 --- a/core/src/test/scala/spark/storage/BlockManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala @@ -1,4 +1,21 @@ -package spark.storage +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage import java.nio.ByteBuffer @@ -12,11 +29,8 @@ import org.scalatest.concurrent.Timeouts._ import org.scalatest.matchers.ShouldMatchers._ import org.scalatest.time.SpanSugar._ -import spark.JavaSerializer -import spark.KryoSerializer -import spark.SizeEstimator -import spark.util.AkkaUtils -import spark.util.ByteBufferInputStream +import org.apache.spark.util.{SizeEstimator, Utils, AkkaUtils, ByteBufferInputStream} +import org.apache.spark.serializer.{JavaSerializer, KryoSerializer} class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodTester { @@ -39,7 +53,7 @@ class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodT System.setProperty("spark.hostPort", "localhost:" + boundPort) master = new BlockManagerMaster( - actorSystem.actorOf(Props(new spark.storage.BlockManagerMasterActor(true)))) + actorSystem.actorOf(Props(new BlockManagerMasterActor(true)))) // Set the arch to 64-bit and compressedOops to true to get a deterministic test-case oldArch = System.setProperty("os.arch", "amd64") @@ -48,7 +62,7 @@ class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodT val initialize = PrivateMethod[Unit]('initialize) SizeEstimator invokePrivate initialize() // Set some value ... - System.setProperty("spark.hostPort", spark.Utils.localHostName() + ":" + 1111) + System.setProperty("spark.hostPort", Utils.localHostName() + ":" + 1111) } after { @@ -88,10 +102,10 @@ class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodT assert(level2 === level1, "level2 is not same as level1") assert(level2.eq(level1), "level2 is not the same object as level1") assert(level3 != level1, "level3 is same as level1") - val bytes1 = spark.Utils.serialize(level1) - val level1_ = spark.Utils.deserialize[StorageLevel](bytes1) - val bytes2 = spark.Utils.serialize(level2) - val level2_ = spark.Utils.deserialize[StorageLevel](bytes2) + val bytes1 = Utils.serialize(level1) + val level1_ = Utils.deserialize[StorageLevel](bytes1) + val bytes2 = Utils.serialize(level2) + val level2_ = Utils.deserialize[StorageLevel](bytes2) assert(level1_ === level1, "Deserialized level1 not same as original level1") assert(level1_.eq(level1), "Deserialized level1 not the same object as original level2") assert(level2_ === level2, "Deserialized level2 not same as original level2") @@ -105,10 +119,10 @@ class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodT assert(id2 === id1, "id2 is not same as id1") assert(id2.eq(id1), "id2 is not the same object as id1") assert(id3 != id1, "id3 is same as id1") - val bytes1 = spark.Utils.serialize(id1) - val id1_ = spark.Utils.deserialize[BlockManagerId](bytes1) - val bytes2 = spark.Utils.serialize(id2) - val id2_ = spark.Utils.deserialize[BlockManagerId](bytes2) + val bytes1 = Utils.serialize(id1) + val id1_ = Utils.deserialize[BlockManagerId](bytes1) + val bytes2 = Utils.serialize(id2) + val id2_ = Utils.deserialize[BlockManagerId](bytes2) assert(id1_ === id1, "Deserialized id1 is not same as original id1") assert(id1_.eq(id1), "Deserialized id1 is not the same object as original id1") assert(id2_ === id2, "Deserialized id2 is not same as original id2") diff --git a/core/src/test/scala/org/apache/spark/ui/UISuite.scala b/core/src/test/scala/org/apache/spark/ui/UISuite.scala new file mode 100644 index 0000000000..3321fb5eb7 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/ui/UISuite.scala @@ -0,0 +1,47 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ui + +import scala.util.{Failure, Success, Try} +import java.net.ServerSocket +import org.scalatest.FunSuite +import org.eclipse.jetty.server.Server + +class UISuite extends FunSuite { + test("jetty port increases under contention") { + val startPort = 3030 + val server = new Server(startPort) + server.start() + val (jettyServer1, boundPort1) = JettyUtils.startJettyServer("localhost", startPort, Seq()) + val (jettyServer2, boundPort2) = JettyUtils.startJettyServer("localhost", startPort, Seq()) + + // Allow some wiggle room in case ports on the machine are under contention + assert(boundPort1 > startPort && boundPort1 < startPort + 10) + assert(boundPort2 > boundPort1 && boundPort2 < boundPort1 + 10) + } + + test("jetty binds to port 0 correctly") { + val (jettyServer, boundPort) = JettyUtils.startJettyServer("localhost", 0, Seq()) + assert(jettyServer.getState === "STARTED") + assert(boundPort != 0) + Try {new ServerSocket(boundPort)} match { + case Success(s) => fail("Port %s doesn't seem used by jetty server".format(boundPort)) + case Failure (e) => + } + } +} diff --git a/core/src/test/scala/spark/ClosureCleanerSuite.scala b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala index b2d0dd4627..0ed366fb70 100644 --- a/core/src/test/scala/spark/ClosureCleanerSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala @@ -1,10 +1,28 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import java.io.NotSerializableException import org.scalatest.FunSuite -import spark.LocalSparkContext._ -import SparkContext._ + +import org.apache.spark.SparkContext +import org.apache.spark.LocalSparkContext._ class ClosureCleanerSuite extends FunSuite { test("closures inside an object") { diff --git a/core/src/test/scala/org/apache/spark/util/DistributionSuite.scala b/core/src/test/scala/org/apache/spark/util/DistributionSuite.scala new file mode 100644 index 0000000000..63642461e4 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/DistributionSuite.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +import org.scalatest.FunSuite +import org.scalatest.matchers.ShouldMatchers + +/** + * + */ + +class DistributionSuite extends FunSuite with ShouldMatchers { + test("summary") { + val d = new Distribution((1 to 100).toArray.map{_.toDouble}) + val stats = d.statCounter + stats.count should be (100) + stats.mean should be (50.5) + stats.sum should be (50 * 101) + + val quantiles = d.getQuantiles() + quantiles(0) should be (1) + quantiles(1) should be (26) + quantiles(2) should be (51) + quantiles(3) should be (76) + quantiles(4) should be (100) + } +} diff --git a/core/src/test/scala/org/apache/spark/util/FakeClock.scala b/core/src/test/scala/org/apache/spark/util/FakeClock.scala new file mode 100644 index 0000000000..0a45917b08 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/FakeClock.scala @@ -0,0 +1,26 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +class FakeClock extends Clock { + private var time = 0L + + def advance(millis: Long): Unit = time += millis + + def getTime(): Long = time +} diff --git a/core/src/test/scala/spark/util/NextIteratorSuite.scala b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala index ed5b36da73..45867463a5 100644 --- a/core/src/test/scala/spark/util/NextIteratorSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala @@ -1,4 +1,21 @@ -package spark.util +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import org.scalatest.FunSuite import org.scalatest.matchers.ShouldMatchers diff --git a/core/src/test/scala/org/apache/spark/util/RateLimitedOutputStreamSuite.scala b/core/src/test/scala/org/apache/spark/util/RateLimitedOutputStreamSuite.scala new file mode 100644 index 0000000000..a9dd0b1a5b --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/RateLimitedOutputStreamSuite.scala @@ -0,0 +1,40 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +import org.scalatest.FunSuite +import java.io.ByteArrayOutputStream +import java.util.concurrent.TimeUnit._ + +class RateLimitedOutputStreamSuite extends FunSuite { + + private def benchmark[U](f: => U): Long = { + val start = System.nanoTime + f + System.nanoTime - start + } + + test("write") { + val underlying = new ByteArrayOutputStream + val data = "X" * 41000 + val stream = new RateLimitedOutputStream(underlying, 10000) + val elapsedNs = benchmark { stream.write(data.getBytes("UTF-8")) } + assert(SECONDS.convert(elapsedNs, NANOSECONDS) == 4) + assert(underlying.toString("UTF-8") == data) + } +} diff --git a/core/src/test/scala/spark/SizeEstimatorSuite.scala b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala index c385965c35..5aff26f9fc 100644 --- a/core/src/test/scala/spark/SizeEstimatorSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import org.scalatest.FunSuite import org.scalatest.BeforeAndAfterAll diff --git a/core/src/test/scala/spark/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala index 1e1260f606..e2859caf58 100644 --- a/core/src/test/scala/spark/UtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala @@ -1,4 +1,21 @@ -package spark +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util import com.google.common.base.Charsets import com.google.common.io.Files @@ -9,14 +26,14 @@ import scala.util.Random class UtilsSuite extends FunSuite { - test("memoryBytesToString") { - assert(Utils.memoryBytesToString(10) === "10.0 B") - assert(Utils.memoryBytesToString(1500) === "1500.0 B") - assert(Utils.memoryBytesToString(2000000) === "1953.1 KB") - assert(Utils.memoryBytesToString(2097152) === "2.0 MB") - assert(Utils.memoryBytesToString(2306867) === "2.2 MB") - assert(Utils.memoryBytesToString(5368709120L) === "5.0 GB") - assert(Utils.memoryBytesToString(5L * 1024L * 1024L * 1024L * 1024L) === "5.0 TB") + test("bytesToString") { + assert(Utils.bytesToString(10) === "10.0 B") + assert(Utils.bytesToString(1500) === "1500.0 B") + assert(Utils.bytesToString(2000000) === "1953.1 KB") + assert(Utils.bytesToString(2097152) === "2.0 MB") + assert(Utils.bytesToString(2306867) === "2.2 MB") + assert(Utils.bytesToString(5368709120L) === "5.0 GB") + assert(Utils.bytesToString(5L * 1024L * 1024L * 1024L * 1024L) === "5.0 TB") } test("copyStream") { diff --git a/core/src/test/scala/spark/BroadcastSuite.scala b/core/src/test/scala/spark/BroadcastSuite.scala deleted file mode 100644 index 362a31fb0d..0000000000 --- a/core/src/test/scala/spark/BroadcastSuite.scala +++ /dev/null @@ -1,22 +0,0 @@ -package spark - -import org.scalatest.FunSuite - -class BroadcastSuite extends FunSuite with LocalSparkContext { - - test("basic broadcast") { - sc = new SparkContext("local", "test") - val list = List(1, 2, 3, 4) - val listBroadcast = sc.broadcast(list) - val results = sc.parallelize(1 to 2).map(x => (x, listBroadcast.value.sum)) - assert(results.collect.toSet === Set((1, 10), (2, 10))) - } - - test("broadcast variables accessed in multiple threads") { - sc = new SparkContext("local[10]", "test") - val list = List(1, 2, 3, 4) - val listBroadcast = sc.broadcast(list) - val results = sc.parallelize(1 to 10).map(x => (x, listBroadcast.value.sum)) - assert(results.collect.toSet === (1 to 10).map(x => (x, 10)).toSet) - } -} diff --git a/core/src/test/scala/spark/SharedSparkContext.scala b/core/src/test/scala/spark/SharedSparkContext.scala deleted file mode 100644 index 1da79f9824..0000000000 --- a/core/src/test/scala/spark/SharedSparkContext.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark - -import org.scalatest.Suite -import org.scalatest.BeforeAndAfterAll - -/** Shares a local `SparkContext` between all tests in a suite and closes it at the end */ -trait SharedSparkContext extends BeforeAndAfterAll { self: Suite => - - @transient private var _sc: SparkContext = _ - - def sc: SparkContext = _sc - - override def beforeAll() { - _sc = new SparkContext("local", "test") - super.beforeAll() - } - - override def afterAll() { - if (_sc != null) { - LocalSparkContext.stop(_sc) - _sc = null - } - super.afterAll() - } -} diff --git a/core/src/test/scala/spark/ShuffleNettySuite.scala b/core/src/test/scala/spark/ShuffleNettySuite.scala deleted file mode 100644 index bfaffa953e..0000000000 --- a/core/src/test/scala/spark/ShuffleNettySuite.scala +++ /dev/null @@ -1,17 +0,0 @@ -package spark - -import org.scalatest.BeforeAndAfterAll - - -class ShuffleNettySuite extends ShuffleSuite with BeforeAndAfterAll { - - // This test suite should run all tests in ShuffleSuite with Netty shuffle mode. - - override def beforeAll(configMap: Map[String, Any]) { - System.setProperty("spark.shuffle.use.netty", "true") - } - - override def afterAll(configMap: Map[String, Any]) { - System.setProperty("spark.shuffle.use.netty", "false") - } -} diff --git a/core/src/test/scala/spark/ShuffleSuite.scala b/core/src/test/scala/spark/ShuffleSuite.scala deleted file mode 100644 index 950218fa28..0000000000 --- a/core/src/test/scala/spark/ShuffleSuite.scala +++ /dev/null @@ -1,131 +0,0 @@ -package spark - -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashSet - -import org.scalatest.FunSuite -import org.scalatest.matchers.ShouldMatchers -import org.scalatest.prop.Checkers -import org.scalacheck.Arbitrary._ -import org.scalacheck.Gen -import org.scalacheck.Prop._ - -import com.google.common.io.Files - -import spark.rdd.ShuffledRDD -import spark.SparkContext._ - -class ShuffleSuite extends FunSuite with ShouldMatchers with LocalSparkContext { - test("groupByKey with compression") { - try { - System.setProperty("spark.shuffle.compress", "true") - sc = new SparkContext("local", "test") - val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (2, 1)), 4) - val groups = pairs.groupByKey(4).collect() - assert(groups.size === 2) - val valuesFor1 = groups.find(_._1 == 1).get._2 - assert(valuesFor1.toList.sorted === List(1, 2, 3)) - val valuesFor2 = groups.find(_._1 == 2).get._2 - assert(valuesFor2.toList.sorted === List(1)) - } finally { - System.setProperty("spark.blockManager.compress", "false") - } - } - - test("shuffle non-zero block size") { - sc = new SparkContext("local-cluster[2,1,512]", "test") - val NUM_BLOCKS = 3 - - val a = sc.parallelize(1 to 10, 2) - val b = a.map { x => - (x, new ShuffleSuite.NonJavaSerializableClass(x * 2)) - } - // If the Kryo serializer is not used correctly, the shuffle would fail because the - // default Java serializer cannot handle the non serializable class. - val c = new ShuffledRDD(b, new HashPartitioner(NUM_BLOCKS), - classOf[spark.KryoSerializer].getName) - val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId - - assert(c.count === 10) - - // All blocks must have non-zero size - (0 until NUM_BLOCKS).foreach { id => - val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) - assert(statuses.forall(s => s._2 > 0)) - } - } - - test("shuffle serializer") { - // Use a local cluster with 2 processes to make sure there are both local and remote blocks - sc = new SparkContext("local-cluster[2,1,512]", "test") - val a = sc.parallelize(1 to 10, 2) - val b = a.map { x => - (x, new ShuffleSuite.NonJavaSerializableClass(x * 2)) - } - // If the Kryo serializer is not used correctly, the shuffle would fail because the - // default Java serializer cannot handle the non serializable class. - val c = new ShuffledRDD(b, new HashPartitioner(3), classOf[spark.KryoSerializer].getName) - assert(c.count === 10) - } - - test("zero sized blocks") { - // Use a local cluster with 2 processes to make sure there are both local and remote blocks - sc = new SparkContext("local-cluster[2,1,512]", "test") - - // 10 partitions from 4 keys - val NUM_BLOCKS = 10 - val a = sc.parallelize(1 to 4, NUM_BLOCKS) - val b = a.map(x => (x, x*2)) - - // NOTE: The default Java serializer doesn't create zero-sized blocks. - // So, use Kryo - val c = new ShuffledRDD(b, new HashPartitioner(10), classOf[spark.KryoSerializer].getName) - - val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId - assert(c.count === 4) - - val blockSizes = (0 until NUM_BLOCKS).flatMap { id => - val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) - statuses.map(x => x._2) - } - val nonEmptyBlocks = blockSizes.filter(x => x > 0) - - // We should have at most 4 non-zero sized partitions - assert(nonEmptyBlocks.size <= 4) - } - - test("zero sized blocks without kryo") { - // Use a local cluster with 2 processes to make sure there are both local and remote blocks - sc = new SparkContext("local-cluster[2,1,512]", "test") - - // 10 partitions from 4 keys - val NUM_BLOCKS = 10 - val a = sc.parallelize(1 to 4, NUM_BLOCKS) - val b = a.map(x => (x, x*2)) - - // NOTE: The default Java serializer should create zero-sized blocks - val c = new ShuffledRDD(b, new HashPartitioner(10)) - - val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[Int, Int]].shuffleId - assert(c.count === 4) - - val blockSizes = (0 until NUM_BLOCKS).flatMap { id => - val statuses = SparkEnv.get.mapOutputTracker.getServerStatuses(shuffleId, id) - statuses.map(x => x._2) - } - val nonEmptyBlocks = blockSizes.filter(x => x > 0) - - // We should have at most 4 non-zero sized partitions - assert(nonEmptyBlocks.size <= 4) - } -} - -object ShuffleSuite { - - def mergeCombineException(x: Int, y: Int): Int = { - throw new SparkException("Exception for map-side combine.") - x + y - } - - class NonJavaSerializableClass(val value: Int) -} diff --git a/core/src/test/scala/spark/UnpersistSuite.scala b/core/src/test/scala/spark/UnpersistSuite.scala deleted file mode 100644 index 94776e7572..0000000000 --- a/core/src/test/scala/spark/UnpersistSuite.scala +++ /dev/null @@ -1,30 +0,0 @@ -package spark - -import org.scalatest.FunSuite -import org.scalatest.concurrent.Timeouts._ -import org.scalatest.time.{Span, Millis} -import spark.SparkContext._ - -class UnpersistSuite extends FunSuite with LocalSparkContext { - test("unpersist RDD") { - sc = new SparkContext("local", "test") - val rdd = sc.makeRDD(Array(1, 2, 3, 4), 2).cache() - rdd.count - assert(sc.persistentRdds.isEmpty === false) - rdd.unpersist() - assert(sc.persistentRdds.isEmpty === true) - - failAfter(Span(3000, Millis)) { - try { - while (! sc.getRDDStorageInfo.isEmpty) { - Thread.sleep(200) - } - } catch { - case _ => { Thread.sleep(10) } - // Do nothing. We might see exceptions because block manager - // is racing this thread to remove entries from the driver. - } - } - assert(sc.getRDDStorageInfo.isEmpty === true) - } -} diff --git a/core/src/test/scala/spark/ZippedPartitionsSuite.scala b/core/src/test/scala/spark/ZippedPartitionsSuite.scala deleted file mode 100644 index 96cb295f45..0000000000 --- a/core/src/test/scala/spark/ZippedPartitionsSuite.scala +++ /dev/null @@ -1,33 +0,0 @@ -package spark - -import scala.collection.immutable.NumericRange - -import org.scalatest.FunSuite -import org.scalatest.prop.Checkers -import org.scalacheck.Arbitrary._ -import org.scalacheck.Gen -import org.scalacheck.Prop._ - -import SparkContext._ - - -object ZippedPartitionsSuite { - def procZippedData(i: Iterator[Int], s: Iterator[String], d: Iterator[Double]) : Iterator[Int] = { - Iterator(i.toArray.size, s.toArray.size, d.toArray.size) - } -} - -class ZippedPartitionsSuite extends FunSuite with SharedSparkContext { - test("print sizes") { - val data1 = sc.makeRDD(Array(1, 2, 3, 4), 2) - val data2 = sc.makeRDD(Array("1", "2", "3", "4", "5", "6"), 2) - val data3 = sc.makeRDD(Array(1.0, 2.0), 2) - - val zippedRDD = data1.zipPartitions(ZippedPartitionsSuite.procZippedData, data2, data3) - - val obtainedSizes = zippedRDD.collect() - val expectedSizes = Array(2, 3, 1, 2, 3, 1) - assert(obtainedSizes.size == 6) - assert(obtainedSizes.zip(expectedSizes).forall(x => x._1 == x._2)) - } -} diff --git a/core/src/test/scala/spark/scheduler/TaskContextSuite.scala b/core/src/test/scala/spark/scheduler/TaskContextSuite.scala deleted file mode 100644 index 647bcaf860..0000000000 --- a/core/src/test/scala/spark/scheduler/TaskContextSuite.scala +++ /dev/null @@ -1,32 +0,0 @@ -package spark.scheduler - -import org.scalatest.FunSuite -import org.scalatest.BeforeAndAfter -import spark.TaskContext -import spark.RDD -import spark.SparkContext -import spark.Partition -import spark.LocalSparkContext - -class TaskContextSuite extends FunSuite with BeforeAndAfter with LocalSparkContext { - - test("Calls executeOnCompleteCallbacks after failure") { - var completed = false - sc = new SparkContext("local", "test") - val rdd = new RDD[String](sc, List()) { - override def getPartitions = Array[Partition](StubPartition(0)) - override def compute(split: Partition, context: TaskContext) = { - context.addOnCompleteCallback(() => completed = true) - sys.error("failed") - } - } - val func = (c: TaskContext, i: Iterator[String]) => i.next - val task = new ResultTask[String, String](0, rdd, func, 0, Seq(), 0) - intercept[RuntimeException] { - task.run(0) - } - assert(completed === true) - } - - case class StubPartition(val index: Int) extends Partition -} diff --git a/core/src/test/scala/spark/ui/UISuite.scala b/core/src/test/scala/spark/ui/UISuite.scala deleted file mode 100644 index fc0c160720..0000000000 --- a/core/src/test/scala/spark/ui/UISuite.scala +++ /dev/null @@ -1,29 +0,0 @@ -package spark.ui - -import scala.util.{Failure, Success, Try} -import java.net.ServerSocket -import org.scalatest.FunSuite -import org.eclipse.jetty.server.Server - -class UISuite extends FunSuite { - test("jetty port increases under contention") { - val startPort = 33333 - val server = new Server(startPort) - server.start() - val (jettyServer1, boundPort1) = JettyUtils.startJettyServer("localhost", startPort, Seq()) - val (jettyServer2, boundPort2) = JettyUtils.startJettyServer("localhost", startPort, Seq()) - - assert(boundPort1 === startPort + 1) - assert(boundPort2 === startPort + 2) - } - - test("jetty binds to port 0 correctly") { - val (jettyServer, boundPort) = JettyUtils.startJettyServer("localhost", 0, Seq()) - assert(jettyServer.getState === "STARTED") - assert(boundPort != 0) - Try {new ServerSocket(boundPort)} match { - case Success(s) => fail("Port %s doesn't seem used by jetty server".format(boundPort)) - case Failure (e) => - } - } -} diff --git a/core/src/test/scala/spark/util/DistributionSuite.scala b/core/src/test/scala/spark/util/DistributionSuite.scala deleted file mode 100644 index cc6249b1dd..0000000000 --- a/core/src/test/scala/spark/util/DistributionSuite.scala +++ /dev/null @@ -1,25 +0,0 @@ -package spark.util - -import org.scalatest.FunSuite -import org.scalatest.matchers.ShouldMatchers - -/** - * - */ - -class DistributionSuite extends FunSuite with ShouldMatchers { - test("summary") { - val d = new Distribution((1 to 100).toArray.map{_.toDouble}) - val stats = d.statCounter - stats.count should be (100) - stats.mean should be (50.5) - stats.sum should be (50 * 101) - - val quantiles = d.getQuantiles() - quantiles(0) should be (1) - quantiles(1) should be (26) - quantiles(2) should be (51) - quantiles(3) should be (76) - quantiles(4) should be (100) - } -} diff --git a/core/src/test/scala/spark/util/RateLimitedOutputStreamSuite.scala b/core/src/test/scala/spark/util/RateLimitedOutputStreamSuite.scala deleted file mode 100644 index 794063fb6d..0000000000 --- a/core/src/test/scala/spark/util/RateLimitedOutputStreamSuite.scala +++ /dev/null @@ -1,23 +0,0 @@ -package spark.util - -import org.scalatest.FunSuite -import java.io.ByteArrayOutputStream -import java.util.concurrent.TimeUnit._ - -class RateLimitedOutputStreamSuite extends FunSuite { - - private def benchmark[U](f: => U): Long = { - val start = System.nanoTime - f - System.nanoTime - start - } - - test("write") { - val underlying = new ByteArrayOutputStream - val data = "X" * 41000 - val stream = new RateLimitedOutputStream(underlying, 10000) - val elapsedNs = benchmark { stream.write(data.getBytes("UTF-8")) } - assert(SECONDS.convert(elapsedNs, NANOSECONDS) == 4) - assert(underlying.toString("UTF-8") == data) - } -} |
