diff options
5 files changed, 450 insertions, 709 deletions
diff --git a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index e56bc02897..e58a926b59 100644 --- a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -17,19 +17,10 @@ package org.apache.spark.deploy.yarn -import java.net.{InetAddress, UnknownHostException, URI} import java.nio.ByteBuffer -import scala.collection.JavaConversions._ -import scala.collection.mutable.HashMap -import scala.collection.mutable.Map - import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileContext, FileStatus, FileSystem, Path, FileUtil} -import org.apache.hadoop.fs.permission.FsPermission; import org.apache.hadoop.io.DataOutputBuffer -import org.apache.hadoop.mapred.Master -import org.apache.hadoop.net.NetUtils import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.api._ import org.apache.hadoop.yarn.api.ApplicationConstants.Environment @@ -41,29 +32,22 @@ import org.apache.hadoop.yarn.ipc.YarnRPC import org.apache.hadoop.yarn.util.{Apps, Records} import org.apache.spark.{Logging, SparkConf} -import org.apache.spark.util.Utils -import org.apache.spark.deploy.SparkHadoopUtil -class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) - extends YarnClientImpl with Logging { +class Client(clientArgs: ClientArguments, hadoopConf: Configuration, spConf: SparkConf) + extends YarnClientImpl with ClientBase with Logging { - def this(args: ClientArguments, sparkConf: SparkConf) = - this(args, new Configuration(), sparkConf) + def this(clientArgs: ClientArguments, spConf: SparkConf) = + this(clientArgs, new Configuration(), spConf) - def this(args: ClientArguments) = this(args, new SparkConf()) + def this(clientArgs: ClientArguments) = this(clientArgs, new SparkConf()) + val args = clientArgs + val conf = hadoopConf + val sparkConf = spConf var rpc: YarnRPC = YarnRPC.create(conf) val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - val credentials = UserGroupInformation.getCurrentUser().getCredentials() - private val SPARK_STAGING: String = ".sparkStaging" - private val distCacheMgr = new ClientDistributedCacheManager() - - // Staging directory is private! -> rwx-------- - val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700:Short) - // App files are world-wide readable and owner writable -> rw-r--r-- - val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644:Short) // for client user who want to monitor app status by itself. def runApp() = { @@ -83,6 +67,11 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) val env = setupLaunchEnv(localResources, appStagingDir) val amContainer = createContainerLaunchContext(newApp, localResources, env) + val capability = Records.newRecord(classOf[Resource]).asInstanceOf[Resource] + // Memory for the ApplicationMaster. + capability.setMemory(args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD) + amContainer.setResource(capability) + appContext.setQueue(args.amQueue) appContext.setAMContainerSpec(amContainer) appContext.setUser(UserGroupInformation.getCurrentUser().getShortUserName()) @@ -97,28 +86,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) System.exit(0) } - def validateArgs() = { - Map( - (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!", - (args.userJar == null) -> "Error: You must specify a user jar!", - (args.userClass == null) -> "Error: You must specify a user class!", - (args.numWorkers <= 0) -> "Error: You must specify at least 1 worker!", - (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be " + - "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD), - (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size " + - "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD) - ).foreach { case(cond, errStr) => - if (cond) { - logError(errStr) - args.printUsageAndExit(1) - } - } - } - - def getAppStagingDir(appId: ApplicationId): String = { - SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR - } - def logClusterResourceDetails() { val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics logInfo("Got Cluster metric info from ASM, numNodeManagers = " + @@ -134,24 +101,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) 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") @@ -161,263 +110,19 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) appContext } - /** See if two file systems are the same or not. */ - private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = { - val srcUri = srcFs.getUri() - val dstUri = destFs.getUri() - if (srcUri.getScheme() == null) { - return false - } - if (!srcUri.getScheme().equals(dstUri.getScheme())) { - return false - } - var srcHost = srcUri.getHost() - var dstHost = dstUri.getHost() - if ((srcHost != null) && (dstHost != null)) { - try { - srcHost = InetAddress.getByName(srcHost).getCanonicalHostName() - dstHost = InetAddress.getByName(dstHost).getCanonicalHostName() - } catch { - case e: UnknownHostException => - return false - } - if (!srcHost.equals(dstHost)) { - return false - } - } else if (srcHost == null && dstHost != null) { - return false - } else if (srcHost != null && dstHost == null) { - return false - } - //check for ports - if (srcUri.getPort() != dstUri.getPort()) { - return false - } - - true - } - - /** Copy the file into HDFS if needed. */ - private def copyRemoteFile( - dstDir: Path, - originalPath: Path, - replication: Short, - setPerms: Boolean = false): Path = { - val fs = FileSystem.get(conf) - val remoteFs = originalPath.getFileSystem(conf) - var newPath = originalPath - if (! compareFs(remoteFs, fs)) { - newPath = new Path(dstDir, originalPath.getName()) - logInfo("Uploading " + originalPath + " to " + newPath) - FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf) - fs.setReplication(newPath, replication) - if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION)) - } - // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific - // version shows the specific version in the distributed cache configuration - val qualPath = fs.makeQualified(newPath) - val fc = FileContext.getFileContext(qualPath.toUri(), conf) - val destPath = fc.resolvePath(qualPath) - destPath - } - - def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - // Upload Spark and the application JAR to the remote file system if necessary. 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) - } - } - val dst = new Path(fs.getHomeDirectory(), appStagingDir) - val replication = sparkConf.getInt("spark.yarn.submit.file.replication", 3).toShort - - if (UserGroupInformation.isSecurityEnabled()) { - val dstFs = dst.getFileSystem(conf) - dstFs.addDelegationTokens(delegTokenRenewer, credentials) - } - val localResources = HashMap[String, LocalResource]() - FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION)) - - val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]() - - Map(Client.SPARK_JAR -> System.getenv("SPARK_JAR"), Client.APP_JAR -> args.userJar, - Client.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF")) - .foreach { case(destName, _localPath) => - val localPath: String = if (_localPath != null) _localPath.trim() else "" - if (! localPath.isEmpty()) { - var localURI = new URI(localPath) - // if not specified assume these are in the local filesystem to keep behavior like Hadoop - if (localURI.getScheme() == null) { - localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString) - } - val setPermissions = if (destName.equals(Client.APP_JAR)) true else false - val destPath = copyRemoteFile(dst, new Path(localURI), replication, setPermissions) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - destName, statCache) - } - } - - // handle any add jars - if ((args.addJars != null) && (!args.addJars.isEmpty())){ - args.addJars.split(',').foreach { case file: String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - linkname, statCache, true) - } - } - - // handle any distributed cache files - if ((args.files != null) && (!args.files.isEmpty())){ - args.files.split(',').foreach { case file: String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - linkname, statCache) - } - } - - // handle any distributed cache archives - if ((args.archives != null) && (!args.archives.isEmpty())) { - args.archives.split(',').foreach { case file:String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE, - linkname, statCache) - } - } - - UserGroupInformation.getCurrentUser().addCredentials(credentials) - localResources - } - - def setupLaunchEnv( - localResources: HashMap[String, LocalResource], - stagingDir: String): HashMap[String, String] = { - logInfo("Setting up the launch environment") - val log4jConfLocalRes = localResources.getOrElse(Client.LOG4J_PROP, null) - - val env = new HashMap[String, String]() - - Client.populateClasspath(yarnConf, sparkConf, log4jConfLocalRes != null, env) - env("SPARK_YARN_MODE") = "true" - env("SPARK_YARN_STAGING_DIR") = stagingDir - - // Set the environment variables to be passed on to the Workers. - distCacheMgr.setDistFilesEnv(env) - distCacheMgr.setDistArchivesEnv(env) - - // Allow users to specify some environment variables. - Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) - - // Add each SPARK-* key to the environment. - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - 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) - + def calculateAMMemory(newApp: GetNewApplicationResponse) :Int = { val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory() + val amMemory = ((args.amMemory / minResMemory) * minResMemory) + + ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) - + YarnAllocationHandler.MEMORY_OVERHEAD) + amMemory + } - // TODO(harvey): This can probably be a val. - var amMemory = ((args.amMemory / minResMemory) * minResMemory) + - ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) - - YarnAllocationHandler.MEMORY_OVERHEAD) - - // Extra options for the JVM - var JAVA_OPTS = "" - - // Add Xmx for am memory - JAVA_OPTS += "-Xmx" + amMemory + "m " - - JAVA_OPTS += " -Djava.io.tmpdir=" + - new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " " - - // Commenting it out for now - so that people can refer to the properties if required. Remove - // it once cpuset version is pushed out. The context is, default gc for server class machines - // end up using all cores to do gc - hence if there are multiple containers in same node, - // spark gc effects all other containers performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in - // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset - // of cores on a node. - val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") && - java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC")) - if (useConcurrentAndIncrementalGC) { - // In our expts, using (default) throughput collector has severe perf ramnifications in - // multi-tenant machines - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } - - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " - } - - // Command for the ApplicationMaster - var javaCommand = "java" - val javaHome = System.getenv("JAVA_HOME") - if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String](javaCommand + - " -server " + - JAVA_OPTS + - " " + args.amClass + - " --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) - + def setupSecurityToken(amContainer :ContainerLaunchContext) = { // Setup security tokens. val dob = new DataOutputBuffer() credentials.writeTokenStorageToStream(dob) amContainer.setContainerTokens(ByteBuffer.wrap(dob.getData())) - - amContainer } def submitApp(appContext: ApplicationSubmissionContext) = { @@ -461,9 +166,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) } object Client { - val SPARK_JAR: String = "spark.jar" - val APP_JAR: String = "app.jar" - val LOG4J_PROP: String = "log4j.properties" def main(argStrings: Array[String]) { // Set an env variable indicating we are running in YARN mode. @@ -475,36 +177,4 @@ object Client { new Client(args, sparkConf).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) - } - } - - def populateClasspath(conf: Configuration, sparkConf: SparkConf, addLog4j: Boolean, env: HashMap[String, String]) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$()) - // If log4j present, ensure ours overrides all others - if (addLog4j) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + LOG4J_PROP) - } - // Normally the users app.jar is last in case conflicts with spark jars - val userClasspathFirst = sparkConf.get("spark.yarn.user.classpath.first", "false").toBoolean - if (userClasspathFirst) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + APP_JAR) - } - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + SPARK_JAR) - Client.populateHadoopClasspath(conf, env) - - if (!userClasspathFirst) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + APP_JAR) - } - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + "*") - } } diff --git a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala index d32cdcc879..1c28d6c86d 100644 --- a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala +++ b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala @@ -201,7 +201,7 @@ class WorkerRunnable( def prepareEnvironment: HashMap[String, String] = { val env = new HashMap[String, String]() - Client.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) + ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) // Allow users to specify some environment variables Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) diff --git a/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala new file mode 100644 index 0000000000..96e998ab61 --- /dev/null +++ b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala @@ -0,0 +1,411 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF 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.yarn + +import java.net.{InetAddress, UnknownHostException, URI} +import java.nio.ByteBuffer + +import scala.collection.JavaConversions._ +import scala.collection.mutable.HashMap +import scala.collection.mutable.Map + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs._ +import org.apache.hadoop.fs.permission.FsPermission; +import org.apache.hadoop.io.DataOutputBuffer +import org.apache.hadoop.mapred.Master +import org.apache.hadoop.net.NetUtils +import org.apache.hadoop.security.UserGroupInformation +import org.apache.hadoop.yarn.api._ +import org.apache.hadoop.yarn.api.ApplicationConstants.Environment +import org.apache.hadoop.yarn.api.protocolrecords._ +import org.apache.hadoop.yarn.api.records._ +import org.apache.hadoop.yarn.conf.YarnConfiguration +import org.apache.hadoop.yarn.ipc.YarnRPC +import org.apache.hadoop.yarn.util.{Records, Apps} + +import org.apache.spark.{Logging, SparkConf} +import org.apache.spark.util.Utils +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.hadoop.yarn.api.ApplicationConstants.Environment + + +/** + * The entry point (starting in Client#main() and Client#run()) for launching Spark on YARN. The + * Client submits an application to the global ResourceManager to launch Spark's ApplicationMaster, + * which will launch a Spark master process and negotiate resources throughout its duration. + */ +trait ClientBase extends Logging { + val args: ClientArguments + val conf: Configuration + val sparkConf: SparkConf + + //var rpc: YarnRPC = YarnRPC.create(conf) + val yarnConf: YarnConfiguration + val credentials = UserGroupInformation.getCurrentUser().getCredentials() + private val SPARK_STAGING: String = ".sparkStaging" + private val distCacheMgr = new ClientDistributedCacheManager() + + // Staging directory is private! -> rwx-------- + val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700: Short) + // App files are world-wide readable and owner writable -> rw-r--r-- + val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644: Short) + + // TODO(harvey): This could just go in ClientArguments. + def validateArgs() = { + Map( + (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!", + (args.userJar == null) -> "Error: You must specify a user jar!", + (args.userClass == null) -> "Error: You must specify a user class!", + (args.numWorkers <= 0) -> "Error: You must specify at least 1 worker!", + (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be" + + "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD), + (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size" + + "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString) + ).foreach { case(cond, errStr) => + if (cond) { + logError(errStr) + args.printUsageAndExit(1) + } + } + } + + def getAppStagingDir(appId: ApplicationId): String = { + SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR + } + + 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("Required worker memory (%d MB), is above the max threshold (%d MB) of this cluster.". + format(args.workerMemory, maxMem)) + System.exit(1) + } + val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD + if (amMem > maxMem) { + logError("Required AM memory (%d) is above the max threshold (%d) of this cluster". + format(args.amMemory, maxMem)) + 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. + } + + /** See if two file systems are the same or not. */ + private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = { + val srcUri = srcFs.getUri() + val dstUri = destFs.getUri() + if (srcUri.getScheme() == null) { + return false + } + if (!srcUri.getScheme().equals(dstUri.getScheme())) { + return false + } + var srcHost = srcUri.getHost() + var dstHost = dstUri.getHost() + if ((srcHost != null) && (dstHost != null)) { + try { + srcHost = InetAddress.getByName(srcHost).getCanonicalHostName() + dstHost = InetAddress.getByName(dstHost).getCanonicalHostName() + } catch { + case e: UnknownHostException => + return false + } + if (!srcHost.equals(dstHost)) { + return false + } + } else if (srcHost == null && dstHost != null) { + return false + } else if (srcHost != null && dstHost == null) { + return false + } + //check for ports + if (srcUri.getPort() != dstUri.getPort()) { + return false + } + return true + } + + /** Copy the file into HDFS if needed. */ + private def copyRemoteFile( + dstDir: Path, + originalPath: Path, + replication: Short, + setPerms: Boolean = false): Path = { + val fs = FileSystem.get(conf) + val remoteFs = originalPath.getFileSystem(conf) + var newPath = originalPath + if (! compareFs(remoteFs, fs)) { + newPath = new Path(dstDir, originalPath.getName()) + logInfo("Uploading " + originalPath + " to " + newPath) + FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf) + fs.setReplication(newPath, replication) + if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION)) + } + // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific + // version shows the specific version in the distributed cache configuration + val qualPath = fs.makeQualified(newPath) + val fc = FileContext.getFileContext(qualPath.toUri(), conf) + val destPath = fc.resolvePath(qualPath) + destPath + } + + def qualifyForLocal(localURI : URI): Path = { + var qualifiedURI = localURI + // If not specified assume these are in the local filesystem to keep behavior like Hadoop + if (qualifiedURI.getScheme() == null) { + qualifiedURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(qualifiedURI)).toString) + } + val qualPath = new Path(qualifiedURI) + qualPath + } + + def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = { + logInfo("Preparing Local resources") + // Upload Spark and the application JAR to the remote file system if necessary. Add them as + // local resources to the application master. + 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) + } + } + val dst = new Path(fs.getHomeDirectory(), appStagingDir) + val replication = sparkConf.getInt("spark.yarn.submit.file.replication", 3).toShort + + if (UserGroupInformation.isSecurityEnabled()) { + val dstFs = dst.getFileSystem(conf) + dstFs.addDelegationTokens(delegTokenRenewer, credentials) + } + + val localResources = HashMap[String, LocalResource]() + FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION)) + + val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]() + + Map( + ClientBase.SPARK_JAR -> System.getenv("SPARK_JAR"), ClientBase.APP_JAR -> args.userJar, + ClientBase.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF") + ).foreach { case(destName, _localPath) => + val localPath: String = if (_localPath != null) _localPath.trim() else "" + if (! localPath.isEmpty()) { + val localURI = new URI(localPath) + val setPermissions = if (destName.equals(ClientBase.APP_JAR)) true else false + val destPath = copyRemoteFile(dst, qualifyForLocal(localURI), replication, setPermissions) + distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, + destName, statCache) + } + } + + // Handle jars local to the ApplicationMaster. + if ((args.addJars != null) && (!args.addJars.isEmpty())){ + args.addJars.split(',').foreach { case file: String => + val localURI = new URI(file.trim()) + val localPath = new Path(localURI) + val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) + val destPath = copyRemoteFile(dst, localPath, replication) + // Only add the resource to the Spark ApplicationMaster. + val appMasterOnly = true + distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, + linkname, statCache, appMasterOnly) + } + } + + // Handle any distributed cache files + if ((args.files != null) && (!args.files.isEmpty())){ + args.files.split(',').foreach { case file: String => + val localURI = new URI(file.trim()) + val localPath = new Path(localURI) + val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) + val destPath = copyRemoteFile(dst, localPath, replication) + distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, + linkname, statCache) + } + } + + // Handle any distributed cache archives + if ((args.archives != null) && (!args.archives.isEmpty())) { + args.archives.split(',').foreach { case file:String => + val localURI = new URI(file.trim()) + val localPath = new Path(localURI) + val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) + val destPath = copyRemoteFile(dst, localPath, replication) + distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE, + linkname, statCache) + } + } + + UserGroupInformation.getCurrentUser().addCredentials(credentials) + localResources + } + + def setupLaunchEnv( + localResources: HashMap[String, LocalResource], + stagingDir: String): HashMap[String, String] = { + logInfo("Setting up the launch environment") + val log4jConfLocalRes = localResources.getOrElse(ClientBase.LOG4J_PROP, null) + + val env = new HashMap[String, String]() + + ClientBase.populateClasspath(yarnConf, sparkConf, log4jConfLocalRes != null, env) + env("SPARK_YARN_MODE") = "true" + env("SPARK_YARN_STAGING_DIR") = stagingDir + + // Set the environment variables to be passed on to the Workers. + distCacheMgr.setDistFilesEnv(env) + distCacheMgr.setDistArchivesEnv(env) + + // Allow users to specify some environment variables. + Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) + + // Add each SPARK_* key to the environment. + System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } + + 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 calculateAMMemory(newApp: GetNewApplicationResponse) :Int + + def setupSecurityToken(amContainer :ContainerLaunchContext) + + 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 amMemory = calculateAMMemory(newApp) + + var JAVA_OPTS = "" + + // Add Xmx for AM memory + JAVA_OPTS += "-Xmx" + amMemory + "m" + + val tmpDir = new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + JAVA_OPTS += " -Djava.io.tmpdir=" + tmpDir + + // TODO: Remove once cpuset version is pushed out. + // The context is, default gc for server class machines ends up using all cores to do gc - + // hence if there are multiple containers in same node, Spark GC affects all other containers' + // performance (which can be that of other Spark containers) + // Instead of using this, rely on cpusets by YARN to enforce "proper" Spark behavior in + // multi-tenant environments. Not sure how default Java GC behaves if it is limited to subset + // of cores on a node. + val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") && + java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC")) + if (useConcurrentAndIncrementalGC) { + // In our expts, using (default) throughput collector has severe perf ramifications in + // multi-tenant machines + JAVA_OPTS += " -XX:+UseConcMarkSweepGC " + JAVA_OPTS += " -XX:+CMSIncrementalMode " + JAVA_OPTS += " -XX:+CMSIncrementalPacing " + JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " + JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " + } + + if (env.isDefinedAt("SPARK_JAVA_OPTS")) { + JAVA_OPTS += " " + env("SPARK_JAVA_OPTS") + } + + // Command for the ApplicationMaster + var javaCommand = "java" + val javaHome = System.getenv("JAVA_HOME") + if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { + javaCommand = Environment.JAVA_HOME.$() + "/bin/java" + } + + val commands = List[String]( + javaCommand + + " -server " + + JAVA_OPTS + + " " + args.amClass + + " --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 starting the Spark ApplicationMaster: " + commands(0)) + amContainer.setCommands(commands) + + setupSecurityToken(amContainer) + amContainer + } +} + +object ClientBase { + val SPARK_JAR: String = "spark.jar" + val APP_JAR: String = "app.jar" + val LOG4J_PROP: String = "log4j.properties" + + // 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) + } + } + + def populateClasspath(conf: Configuration, sparkConf: SparkConf, addLog4j: Boolean, env: HashMap[String, String]) { + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$()) + // If log4j present, ensure ours overrides all others + if (addLog4j) { + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + + Path.SEPARATOR + LOG4J_PROP) + } + // Normally the users app.jar is last in case conflicts with spark jars + val userClasspathFirst = sparkConf.get("spark.yarn.user.classpath.first", "false") + .toBoolean + if (userClasspathFirst) { + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + + Path.SEPARATOR + APP_JAR) + } + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + + Path.SEPARATOR + SPARK_JAR) + ClientBase.populateHadoopClasspath(conf, env) + + if (!userClasspathFirst) { + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + + Path.SEPARATOR + APP_JAR) + } + Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + + Path.SEPARATOR + "*") + } +} diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index 51d9adb9d4..fef4702c66 100644 --- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -17,20 +17,10 @@ package org.apache.spark.deploy.yarn -import java.net.{InetAddress, UnknownHostException, URI} import java.nio.ByteBuffer -import scala.collection.JavaConversions._ -import scala.collection.mutable.HashMap -import scala.collection.mutable.Map - import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileContext, FileStatus, FileSystem, Path, FileUtil} -import org.apache.hadoop.fs.permission.FsPermission; import org.apache.hadoop.io.DataOutputBuffer -import org.apache.hadoop.mapred.Master -import org.apache.hadoop.net.NetUtils -import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.api._ import org.apache.hadoop.yarn.api.ApplicationConstants.Environment import org.apache.hadoop.yarn.api.protocolrecords._ @@ -41,8 +31,6 @@ import org.apache.hadoop.yarn.ipc.YarnRPC import org.apache.hadoop.yarn.util.{Apps, Records} import org.apache.spark.{Logging, SparkConf} -import org.apache.spark.util.Utils -import org.apache.spark.deploy.SparkHadoopUtil /** @@ -50,24 +38,19 @@ import org.apache.spark.deploy.SparkHadoopUtil * Client submits an application to the global ResourceManager to launch Spark's ApplicationMaster, * which will launch a Spark master process and negotiate resources throughout its duration. */ -class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) - extends YarnClientImpl with Logging { +class Client(clientArgs: ClientArguments, hadoopConf: Configuration, spConf: SparkConf) + extends YarnClientImpl with ClientBase with Logging { - def this(args: ClientArguments, sparkConf: SparkConf) = - this(args, new Configuration(), sparkConf) + def this(clientArgs: ClientArguments, spConf: SparkConf) = + this(clientArgs, new Configuration(), spConf) - def this(args: ClientArguments) = this(args, new SparkConf()) + def this(clientArgs: ClientArguments) = this(clientArgs, new SparkConf()) + val args = clientArgs + val conf = hadoopConf + val sparkConf = spConf var rpc: YarnRPC = YarnRPC.create(conf) val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - val credentials = UserGroupInformation.getCurrentUser().getCredentials() - private val SPARK_STAGING: String = ".sparkStaging" - private val distCacheMgr = new ClientDistributedCacheManager() - - // Staging directory is private! -> rwx-------- - val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700: Short) - // App files are world-wide readable and owner writable -> rw-r--r-- - val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644: Short) def runApp(): ApplicationId = { validateArgs() @@ -117,29 +100,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) System.exit(0) } - // TODO(harvey): This could just go in ClientArguments. - def validateArgs() = { - Map( - (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!", - (args.userJar == null) -> "Error: You must specify a user jar!", - (args.userClass == null) -> "Error: You must specify a user class!", - (args.numWorkers <= 0) -> "Error: You must specify at least 1 worker!", - (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be" + - "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD), - (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size" + - "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString) - ).foreach { case(cond, errStr) => - if (cond) { - logError(errStr) - args.printUsageAndExit(1) - } - } - } - - def getAppStagingDir(appId: ApplicationId): String = { - SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR - } - def logClusterResourceDetails() { val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics logInfo("Got Cluster metric info from ApplicationsManager (ASM), number of NodeManagers: " + @@ -148,292 +108,27 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) val queueInfo: QueueInfo = super.getQueueInfo(args.amQueue) logInfo( """Queue info ... queueName: %s, queueCurrentCapacity: %s, queueMaxCapacity: %s, queueApplicationCount = %s, queueChildQueueCount = %s""".format( - queueInfo.getQueueName, - queueInfo.getCurrentCapacity, - queueInfo.getMaximumCapacity, - queueInfo.getApplications.size, - 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("Required worker memory (%d MB), is above the max threshold (%d MB) of this cluster.". - format(args.workerMemory, maxMem)) - System.exit(1) - } - val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD - if (amMem > maxMem) { - logError("Required AM memory (%d) is above the max threshold (%d) of this cluster". - format(args.amMemory, maxMem)) - 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. - } - - /** See if two file systems are the same or not. */ - private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = { - val srcUri = srcFs.getUri() - val dstUri = destFs.getUri() - if (srcUri.getScheme() == null) { - return false - } - if (!srcUri.getScheme().equals(dstUri.getScheme())) { - return false - } - var srcHost = srcUri.getHost() - var dstHost = dstUri.getHost() - if ((srcHost != null) && (dstHost != null)) { - try { - srcHost = InetAddress.getByName(srcHost).getCanonicalHostName() - dstHost = InetAddress.getByName(dstHost).getCanonicalHostName() - } catch { - case e: UnknownHostException => - return false - } - if (!srcHost.equals(dstHost)) { - return false - } - } else if (srcHost == null && dstHost != null) { - return false - } else if (srcHost != null && dstHost == null) { - return false - } - //check for ports - if (srcUri.getPort() != dstUri.getPort()) { - return false - } - - true + queueInfo.getQueueName, + queueInfo.getCurrentCapacity, + queueInfo.getMaximumCapacity, + queueInfo.getApplications.size, + queueInfo.getChildQueues.size)) } - /** Copy the file into HDFS if needed. */ - private def copyRemoteFile( - dstDir: Path, - originalPath: Path, - replication: Short, - setPerms: Boolean = false): Path = { - val fs = FileSystem.get(conf) - val remoteFs = originalPath.getFileSystem(conf) - var newPath = originalPath - if (! compareFs(remoteFs, fs)) { - newPath = new Path(dstDir, originalPath.getName()) - logInfo("Uploading " + originalPath + " to " + newPath) - FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf) - fs.setReplication(newPath, replication) - if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION)) - } - // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific - // version shows the specific version in the distributed cache configuration - val qualPath = fs.makeQualified(newPath) - val fc = FileContext.getFileContext(qualPath.toUri(), conf) - val destPath = fc.resolvePath(qualPath) - destPath - } - - def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - // Upload Spark and the application JAR to the remote file system if necessary. Add them as - // local resources to the application master. - 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) - } - } - val dst = new Path(fs.getHomeDirectory(), appStagingDir) - val replication = sparkConf.getInt("spark.yarn.submit.file.replication", 3).toShort - - if (UserGroupInformation.isSecurityEnabled()) { - val dstFs = dst.getFileSystem(conf) - dstFs.addDelegationTokens(delegTokenRenewer, credentials) - } - - val localResources = HashMap[String, LocalResource]() - FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION)) - - val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]() - - Map( - Client.SPARK_JAR -> System.getenv("SPARK_JAR"), Client.APP_JAR -> args.userJar, - Client.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF") - ).foreach { case(destName, _localPath) => - val localPath: String = if (_localPath != null) _localPath.trim() else "" - if (! localPath.isEmpty()) { - var localURI = new URI(localPath) - // If not specified assume these are in the local filesystem to keep behavior like Hadoop - if (localURI.getScheme() == null) { - localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString) - } - val setPermissions = if (destName.equals(Client.APP_JAR)) true else false - val destPath = copyRemoteFile(dst, new Path(localURI), replication, setPermissions) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - destName, statCache) - } - } - - // Handle jars local to the ApplicationMaster. - if ((args.addJars != null) && (!args.addJars.isEmpty())){ - args.addJars.split(',').foreach { case file: String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - // Only add the resource to the Spark ApplicationMaster. - val appMasterOnly = true - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - linkname, statCache, appMasterOnly) - } - } - - // Handle any distributed cache files - if ((args.files != null) && (!args.files.isEmpty())){ - args.files.split(',').foreach { case file: String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, - linkname, statCache) - } - } - - // Handle any distributed cache archives - if ((args.archives != null) && (!args.archives.isEmpty())) { - args.archives.split(',').foreach { case file:String => - val localURI = new URI(file.trim()) - val localPath = new Path(localURI) - val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName()) - val destPath = copyRemoteFile(dst, localPath, replication) - distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE, - linkname, statCache) - } - } - - UserGroupInformation.getCurrentUser().addCredentials(credentials) - localResources - } - - def setupLaunchEnv( - localResources: HashMap[String, LocalResource], - stagingDir: String): HashMap[String, String] = { - logInfo("Setting up the launch environment") - val log4jConfLocalRes = localResources.getOrElse(Client.LOG4J_PROP, null) - - val env = new HashMap[String, String]() - - Client.populateClasspath(yarnConf, sparkConf, log4jConfLocalRes != null, env) - env("SPARK_YARN_MODE") = "true" - env("SPARK_YARN_STAGING_DIR") = stagingDir - - // Set the environment variables to be passed on to the Workers. - distCacheMgr.setDistFilesEnv(env) - distCacheMgr.setDistArchivesEnv(env) - - // Allow users to specify some environment variables. - Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) - - // Add each SPARK_* key to the environment. - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - - 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) - + def calculateAMMemory(newApp: GetNewApplicationResponse) :Int = { // TODO: Need a replacement for the following code to fix -Xmx? // val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory() // var amMemory = ((args.amMemory / minResMemory) * minResMemory) + // ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) - // YarnAllocationHandler.MEMORY_OVERHEAD) + args.amMemory + } - // Extra options for the JVM - var JAVA_OPTS = "" - - // Add Xmx for AM memory - JAVA_OPTS += "-Xmx" + args.amMemory + "m" - - val tmpDir = new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) - JAVA_OPTS += " -Djava.io.tmpdir=" + tmpDir - - // TODO: Remove once cpuset version is pushed out. - // The context is, default gc for server class machines ends up using all cores to do gc - - // hence if there are multiple containers in same node, Spark GC affects all other containers' - // performance (which can be that of other Spark containers) - // Instead of using this, rely on cpusets by YARN to enforce "proper" Spark behavior in - // multi-tenant environments. Not sure how default Java GC behaves if it is limited to subset - // of cores on a node. - val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") && - java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC")) - if (useConcurrentAndIncrementalGC) { - // In our expts, using (default) throughput collector has severe perf ramifications in - // multi-tenant machines - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } - - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += " " + env("SPARK_JAVA_OPTS") - } - - // Command for the ApplicationMaster - var javaCommand = "java" - val javaHome = System.getenv("JAVA_HOME") - if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String]( - javaCommand + - " -server " + - JAVA_OPTS + - " " + args.amClass + - " --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 starting the Spark ApplicationMaster: " + commands(0)) - amContainer.setCommands(commands) - + def setupSecurityToken(amContainer :ContainerLaunchContext) = { // Setup security tokens. val dob = new DataOutputBuffer() credentials.writeTokenStorageToStream(dob) amContainer.setTokens(ByteBuffer.wrap(dob.getData())) - - amContainer } def submitApp(appContext: ApplicationSubmissionContext) = { @@ -477,9 +172,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf) } object Client { - val SPARK_JAR: String = "spark.jar" - val APP_JAR: String = "app.jar" - val LOG4J_PROP: String = "log4j.properties" def main(argStrings: Array[String]) { // Set an env variable indicating we are running in YARN mode. @@ -492,36 +184,4 @@ object Client { new Client(args, sparkConf).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) - } - } - - def populateClasspath(conf: Configuration, sparkConf: SparkConf, addLog4j: Boolean, env: HashMap[String, String]) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$()) - // If log4j present, ensure ours overrides all others - if (addLog4j) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + LOG4J_PROP) - } - // Normally the users app.jar is last in case conflicts with spark jars - val userClasspathFirst = sparkConf.get("spark.yarn.user.classpath.first", "false") - .toBoolean - if (userClasspathFirst) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + APP_JAR) - } - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + SPARK_JAR) - Client.populateHadoopClasspath(conf, env) - - if (!userClasspathFirst) { - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + APP_JAR) - } - Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() + - Path.SEPARATOR + "*") - } } diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala index b7699050bb..06d40dfe7f 100644 --- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala +++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala @@ -198,7 +198,7 @@ class WorkerRunnable( def prepareEnvironment: HashMap[String, String] = { val env = new HashMap[String, String]() - Client.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) + ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) // Allow users to specify some environment variables Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) |