diff options
Diffstat (limited to 'core/src/main/scala/org/apache')
85 files changed, 1287 insertions, 597 deletions
diff --git a/core/src/main/scala/org/apache/spark/Accumulators.scala b/core/src/main/scala/org/apache/spark/Accumulators.scala index 6e922a612a..5f73d234aa 100644 --- a/core/src/main/scala/org/apache/spark/Accumulators.scala +++ b/core/src/main/scala/org/apache/spark/Accumulators.scala @@ -41,7 +41,7 @@ class Accumulable[R, T] ( @transient initialValue: R, param: AccumulableParam[R, T]) extends Serializable { - + val id = Accumulators.newId @transient private var value_ = initialValue // Current value on master val zero = param.zero(initialValue) // Zero value to be passed to workers @@ -113,7 +113,7 @@ class Accumulable[R, T] ( def setValue(newValue: R) { this.value = newValue } - + // Called by Java when deserializing an object private def readObject(in: ObjectInputStream) { in.defaultReadObject() @@ -177,7 +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 JavaSerializer().newInstance() + val ser = new JavaSerializer(new SparkConf(false)).newInstance() val copy = ser.deserialize[R](ser.serialize(initialValue)) copy.clear() // In case it contained stuff copy @@ -215,7 +215,7 @@ private object Accumulators { val originals = Map[Long, Accumulable[_, _]]() val localAccums = Map[Thread, Map[Long, Accumulable[_, _]]]() var lastId: Long = 0 - + def newId: Long = synchronized { lastId += 1 return lastId diff --git a/core/src/main/scala/org/apache/spark/HttpServer.scala b/core/src/main/scala/org/apache/spark/HttpServer.scala index cdfc9dd54e..69a738dc44 100644 --- a/core/src/main/scala/org/apache/spark/HttpServer.scala +++ b/core/src/main/scala/org/apache/spark/HttpServer.scala @@ -46,6 +46,7 @@ private[spark] class HttpServer(resourceBase: File) extends Logging { if (server != null) { throw new ServerStateException("Server is already started") } else { + logInfo("Starting HTTP Server") server = new Server() val connector = new SocketConnector connector.setMaxIdleTime(60*1000) diff --git a/core/src/main/scala/org/apache/spark/Logging.scala b/core/src/main/scala/org/apache/spark/Logging.scala index 6a973ea495..d519fc5a29 100644 --- a/core/src/main/scala/org/apache/spark/Logging.scala +++ b/core/src/main/scala/org/apache/spark/Logging.scala @@ -17,8 +17,8 @@ package org.apache.spark -import org.slf4j.Logger -import org.slf4j.LoggerFactory +import org.apache.log4j.{LogManager, PropertyConfigurator} +import org.slf4j.{Logger, LoggerFactory} /** * Utility trait for classes that want to log data. Creates a SLF4J logger for the class and allows @@ -33,6 +33,7 @@ trait Logging { // Method to get or create the logger for this object protected def log: Logger = { if (log_ == null) { + initializeIfNecessary() var className = this.getClass.getName // Ignore trailing $'s in the class names for Scala objects if (className.endsWith("$")) { @@ -89,7 +90,37 @@ trait Logging { log.isTraceEnabled } - // Method for ensuring that logging is initialized, to avoid having multiple - // threads do it concurrently (as SLF4J initialization is not thread safe). - protected def initLogging() { log } + private def initializeIfNecessary() { + if (!Logging.initialized) { + Logging.initLock.synchronized { + if (!Logging.initialized) { + initializeLogging() + } + } + } + } + + private def initializeLogging() { + // If Log4j doesn't seem initialized, load a default properties file + val log4jInitialized = LogManager.getRootLogger.getAllAppenders.hasMoreElements + if (!log4jInitialized) { + val defaultLogProps = "org/apache/spark/default-log4j.properties" + val classLoader = this.getClass.getClassLoader + Option(classLoader.getResource(defaultLogProps)) match { + case Some(url) => PropertyConfigurator.configure(url) + case None => System.err.println(s"Spark was unable to load $defaultLogProps") + } + log.info(s"Using Spark's default log4j profile: $defaultLogProps") + } + Logging.initialized = true + + // Force a call into slf4j to initialize it. Avoids this happening from mutliple threads + // and triggering this: http://mailman.qos.ch/pipermail/slf4j-dev/2010-April/002956.html + log + } +} + +object Logging { + @volatile private var initialized = false + val initLock = new Object() } diff --git a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala index ccffcc356c..cdae167aef 100644 --- a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala +++ b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala @@ -50,9 +50,9 @@ private[spark] class MapOutputTrackerMasterActor(tracker: MapOutputTrackerMaster } } -private[spark] class MapOutputTracker extends Logging { +private[spark] class MapOutputTracker(conf: SparkConf) extends Logging { - private val timeout = AkkaUtils.askTimeout + private val timeout = AkkaUtils.askTimeout(conf) // Set to the MapOutputTrackerActor living on the driver var trackerActor: Either[ActorRef, ActorSelection] = _ @@ -65,7 +65,7 @@ private[spark] class MapOutputTracker extends Logging { protected val epochLock = new java.lang.Object private val metadataCleaner = - new MetadataCleaner(MetadataCleanerType.MAP_OUTPUT_TRACKER, this.cleanup) + new MetadataCleaner(MetadataCleanerType.MAP_OUTPUT_TRACKER, this.cleanup, conf) // Send a message to the trackerActor and get its result within a default timeout, or // throw a SparkException if this fails. @@ -129,7 +129,7 @@ private[spark] class MapOutputTracker extends Logging { if (fetchedStatuses == null) { // We won the race to fetch the output locs; do so logInfo("Doing the fetch; tracker actor = " + trackerActor) - val hostPort = Utils.localHostPort() + val hostPort = Utils.localHostPort(conf) // This try-finally prevents hangs due to timeouts: try { val fetchedBytes = @@ -192,7 +192,8 @@ private[spark] class MapOutputTracker extends Logging { } } -private[spark] class MapOutputTrackerMaster extends MapOutputTracker { +private[spark] class MapOutputTrackerMaster(conf: SparkConf) + extends MapOutputTracker(conf) { // Cache a serialized version of the output statuses for each shuffle to send them out faster private var cacheEpoch = epoch diff --git a/core/src/main/scala/org/apache/spark/Partitioner.scala b/core/src/main/scala/org/apache/spark/Partitioner.scala index bcec41c439..31b0773bfe 100644 --- a/core/src/main/scala/org/apache/spark/Partitioner.scala +++ b/core/src/main/scala/org/apache/spark/Partitioner.scala @@ -52,7 +52,7 @@ object Partitioner { for (r <- bySize if r.partitioner != None) { return r.partitioner.get } - if (System.getProperty("spark.default.parallelism") != null) { + if (rdd.context.conf.contains("spark.default.parallelism")) { return new HashPartitioner(rdd.context.defaultParallelism) } else { return new HashPartitioner(bySize.head.partitions.size) @@ -90,7 +90,7 @@ class HashPartitioner(partitions: Int) extends Partitioner { class RangePartitioner[K <% Ordered[K]: ClassTag, V]( partitions: Int, @transient rdd: RDD[_ <: Product2[K,V]], - private val ascending: Boolean = true) + 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/SparkConf.scala b/core/src/main/scala/org/apache/spark/SparkConf.scala new file mode 100644 index 0000000000..98343e9532 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/SparkConf.scala @@ -0,0 +1,189 @@ +package org.apache.spark + +import scala.collection.JavaConverters._ +import scala.collection.mutable.HashMap + +import com.typesafe.config.ConfigFactory + +/** + * Configuration for a Spark application. Used to set various Spark parameters as key-value pairs. + * + * Most of the time, you would create a SparkConf object with `new SparkConf()`, which will load + * values from both the `spark.*` Java system properties and any `spark.conf` on your application's + * classpath (if it has one). In this case, system properties take priority over `spark.conf`, and + * any parameters you set directly on the `SparkConf` object take priority over both of those. + * + * For unit tests, you can also call `new SparkConf(false)` to skip loading external settings and + * get the same configuration no matter what is on the classpath. + * + * All setter methods in this class support chaining. For example, you can write + * `new SparkConf().setMaster("local").setAppName("My app")`. + * + * Note that once a SparkConf object is passed to Spark, it is cloned and can no longer be modified + * by the user. Spark does not support modifying the configuration at runtime. + * + * @param loadDefaults whether to load values from the system properties and classpath + */ +class SparkConf(loadDefaults: Boolean) extends Serializable with Cloneable { + + /** Create a SparkConf that loads defaults from system properties and the classpath */ + def this() = this(true) + + private val settings = new HashMap[String, String]() + + if (loadDefaults) { + ConfigFactory.invalidateCaches() + val typesafeConfig = ConfigFactory.systemProperties() + .withFallback(ConfigFactory.parseResources("spark.conf")) + for (e <- typesafeConfig.entrySet().asScala if e.getKey.startsWith("spark.")) { + settings(e.getKey) = e.getValue.unwrapped.toString + } + } + + /** Set a configuration variable. */ + def set(key: String, value: String): SparkConf = { + if (key == null) { + throw new NullPointerException("null key") + } + if (value == null) { + throw new NullPointerException("null value") + } + settings(key) = value + this + } + + /** + * The master URL to connect to, such as "local" to run locally with one thread, "local[4]" to + * run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster. + */ + def setMaster(master: String): SparkConf = { + set("spark.master", master) + } + + /** Set a name for your application. Shown in the Spark web UI. */ + def setAppName(name: String): SparkConf = { + set("spark.app.name", name) + } + + /** Set JAR files to distribute to the cluster. */ + def setJars(jars: Seq[String]): SparkConf = { + set("spark.jars", jars.mkString(",")) + } + + /** Set JAR files to distribute to the cluster. (Java-friendly version.) */ + def setJars(jars: Array[String]): SparkConf = { + setJars(jars.toSeq) + } + + /** + * Set an environment variable to be used when launching executors for this application. + * These variables are stored as properties of the form spark.executorEnv.VAR_NAME + * (for example spark.executorEnv.PATH) but this method makes them easier to set. + */ + def setExecutorEnv(variable: String, value: String): SparkConf = { + set("spark.executorEnv." + variable, value) + } + + /** + * Set multiple environment variables to be used when launching executors. + * These variables are stored as properties of the form spark.executorEnv.VAR_NAME + * (for example spark.executorEnv.PATH) but this method makes them easier to set. + */ + def setExecutorEnv(variables: Seq[(String, String)]): SparkConf = { + for ((k, v) <- variables) { + setExecutorEnv(k, v) + } + this + } + + /** + * Set multiple environment variables to be used when launching executors. + * (Java-friendly version.) + */ + def setExecutorEnv(variables: Array[(String, String)]): SparkConf = { + setExecutorEnv(variables.toSeq) + } + + /** + * Set the location where Spark is installed on worker nodes. + */ + def setSparkHome(home: String): SparkConf = { + set("spark.home", home) + } + + /** Set multiple parameters together */ + def setAll(settings: Traversable[(String, String)]) = { + this.settings ++= settings + this + } + + /** Set a parameter if it isn't already configured */ + def setIfMissing(key: String, value: String): SparkConf = { + if (!settings.contains(key)) { + settings(key) = value + } + this + } + + /** Remove a parameter from the configuration */ + def remove(key: String): SparkConf = { + settings.remove(key) + this + } + + /** Get a parameter; throws a NoSuchElementException if it's not set */ + def get(key: String): String = { + settings.getOrElse(key, throw new NoSuchElementException(key)) + } + + /** Get a parameter, falling back to a default if not set */ + def get(key: String, defaultValue: String): String = { + settings.getOrElse(key, defaultValue) + } + + /** Get a parameter as an Option */ + def getOption(key: String): Option[String] = { + settings.get(key) + } + + /** Get all parameters as a list of pairs */ + def getAll: Array[(String, String)] = settings.clone().toArray + + /** Get a parameter as an integer, falling back to a default if not set */ + def getInt(key: String, defaultValue: Int): Int = { + getOption(key).map(_.toInt).getOrElse(defaultValue) + } + + /** Get a parameter as a long, falling back to a default if not set */ + def getLong(key: String, defaultValue: Long): Long = { + getOption(key).map(_.toLong).getOrElse(defaultValue) + } + + /** Get a parameter as a double, falling back to a default if not set */ + def getDouble(key: String, defaultValue: Double): Double = { + getOption(key).map(_.toDouble).getOrElse(defaultValue) + } + + /** Get all executor environment variables set on this SparkConf */ + def getExecutorEnv: Seq[(String, String)] = { + val prefix = "spark.executorEnv." + getAll.filter{case (k, v) => k.startsWith(prefix)} + .map{case (k, v) => (k.substring(prefix.length), v)} + } + + /** Does the configuration contain a given parameter? */ + def contains(key: String): Boolean = settings.contains(key) + + /** Copy this object */ + override def clone: SparkConf = { + new SparkConf(false).setAll(settings) + } + + /** + * Return a string listing all keys and values, one per line. This is useful to print the + * configuration out for debugging. + */ + def toDebugString: String = { + settings.toArray.sorted.map{case (k, v) => k + "=" + v}.mkString("\n") + } +} diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index ad3337d94c..e80e43af6d 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -19,36 +19,23 @@ package org.apache.spark import java.io._ import java.net.URI -import java.util.Properties +import java.util.{UUID, Properties} import java.util.concurrent.atomic.AtomicInteger -import scala.collection.Map +import scala.collection.{Map, Set} import scala.collection.generic.Growable -import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap + +import scala.collection.mutable.{ArrayBuffer, HashMap} import scala.reflect.{ClassTag, classTag} import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.hadoop.io.ArrayWritable -import org.apache.hadoop.io.BooleanWritable -import org.apache.hadoop.io.BytesWritable -import org.apache.hadoop.io.DoubleWritable -import org.apache.hadoop.io.FloatWritable -import org.apache.hadoop.io.IntWritable -import org.apache.hadoop.io.LongWritable -import org.apache.hadoop.io.NullWritable -import org.apache.hadoop.io.Text -import org.apache.hadoop.io.Writable -import org.apache.hadoop.mapred.FileInputFormat -import org.apache.hadoop.mapred.InputFormat -import org.apache.hadoop.mapred.JobConf -import org.apache.hadoop.mapred.SequenceFileInputFormat -import org.apache.hadoop.mapred.TextInputFormat -import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} -import org.apache.hadoop.mapreduce.{Job => NewHadoopJob} +import org.apache.hadoop.io.{ArrayWritable, BooleanWritable, BytesWritable, DoubleWritable, +FloatWritable, IntWritable, LongWritable, NullWritable, Text, Writable} +import org.apache.hadoop.mapred.{FileInputFormat, InputFormat, JobConf, SequenceFileInputFormat, +TextInputFormat} +import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat, Job => NewHadoopJob} import org.apache.hadoop.mapreduce.lib.input.{FileInputFormat => NewFileInputFormat} - import org.apache.mesos.MesosNativeLibrary import org.apache.spark.deploy.{LocalSparkCluster, SparkHadoopUtil} @@ -61,53 +48,97 @@ import org.apache.spark.scheduler.cluster.mesos.{CoarseMesosSchedulerBackend, Me import org.apache.spark.scheduler.local.LocalBackend import org.apache.spark.storage.{BlockManagerSource, RDDInfo, StorageStatus, StorageUtils} import org.apache.spark.ui.SparkUI -import org.apache.spark.util.{ClosureCleaner, MetadataCleaner, MetadataCleanerType, - TimeStampedHashMap, Utils} +import org.apache.spark.util.{Utils, TimeStampedHashMap, MetadataCleaner, MetadataCleanerType, +ClosureCleaner} /** * Main entry point for Spark functionality. A SparkContext represents the connection to a Spark * cluster, and can be used to create RDDs, accumulators and broadcast variables on that cluster. * - * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). - * @param appName A name for your application, to display on the cluster web UI. - * @param sparkHome Location where Spark is installed on cluster nodes. - * @param jars Collection of JARs to send to the cluster. These can be paths on the local file - * system or HDFS, HTTP, HTTPS, or FTP URLs. - * @param environment Environment variables to set on worker nodes. + * @param config a Spark Config object describing the application configuration. Any settings in + * this config overrides the default configs as well as system properties. + * @param preferredNodeLocationData used in YARN mode to select nodes to launch containers on. Can + * be generated using [[org.apache.spark.scheduler.InputFormatInfo.computePreferredLocations]] + * from a list of input files or InputFormats for the application. */ class SparkContext( - val master: String, - val appName: String, - val sparkHome: String = null, - val jars: Seq[String] = Nil, - val environment: Map[String, String] = Map(), + config: SparkConf, // This is used only by YARN for now, but should be relevant to other cluster types (Mesos, etc) - // too. This is typically generated from InputFormatInfo.computePreferredLocations .. host, set - // of data-local splits on host - val preferredNodeLocationData: scala.collection.Map[String, scala.collection.Set[SplitInfo]] = - scala.collection.immutable.Map()) + // too. This is typically generated from InputFormatInfo.computePreferredLocations. It contains + // a map from hostname to a list of input format splits on the host. + val preferredNodeLocationData: Map[String, Set[SplitInfo]] = Map()) extends Logging { - // Ensure logging is initialized before we spawn any threads - initLogging() + /** + * Alternative constructor that allows setting common Spark properties directly + * + * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). + * @param appName A name for your application, to display on the cluster web UI + * @param conf a [[org.apache.spark.SparkConf]] object specifying other Spark parameters + */ + def this(master: String, appName: String, conf: SparkConf) = + this(SparkContext.updatedConf(conf, master, appName)) - // Set Spark driver host and port system properties - if (System.getProperty("spark.driver.host") == null) { - System.setProperty("spark.driver.host", Utils.localHostName()) + /** + * Alternative constructor that allows setting common Spark properties directly + * + * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). + * @param appName A name for your application, to display on the cluster web UI. + * @param sparkHome Location where Spark is installed on cluster nodes. + * @param jars Collection of JARs to send to the cluster. These can be paths on the local file + * system or HDFS, HTTP, HTTPS, or FTP URLs. + * @param environment Environment variables to set on worker nodes. + */ + def this( + master: String, + appName: String, + sparkHome: String = null, + jars: Seq[String] = Nil, + environment: Map[String, String] = Map(), + preferredNodeLocationData: Map[String, Set[SplitInfo]] = Map()) = + { + this(SparkContext.updatedConf(new SparkConf(), master, appName, sparkHome, jars, environment), + preferredNodeLocationData) } - if (System.getProperty("spark.driver.port") == null) { - System.setProperty("spark.driver.port", "0") + + private[spark] val conf = config.clone() + + /** + * Return a copy of this SparkContext's configuration. The configuration ''cannot'' be + * changed at runtime. + */ + def getConf: SparkConf = conf.clone() + + if (!conf.contains("spark.master")) { + throw new SparkException("A master URL must be set in your configuration") + } + if (!conf.contains("spark.app.name")) { + throw new SparkException("An application must be set in your configuration") + } + + // Set Spark driver host and port system properties + conf.setIfMissing("spark.driver.host", Utils.localHostName()) + conf.setIfMissing("spark.driver.port", "0") + + val jars: Seq[String] = if (conf.contains("spark.jars")) { + conf.get("spark.jars").split(",").filter(_.size != 0) + } else { + null } + val master = conf.get("spark.master") + val appName = conf.get("spark.app.name") + val isLocal = (master == "local" || master.startsWith("local[")) // Create the Spark execution environment (cache, map output tracker, etc) - private[spark] val env = SparkEnv.createFromSystemProperties( + private[spark] val env = SparkEnv.create( + conf, "<driver>", - System.getProperty("spark.driver.host"), - System.getProperty("spark.driver.port").toInt, - true, - isLocal) + conf.get("spark.driver.host"), + conf.get("spark.driver.port").toInt, + isDriver = true, + isLocal = isLocal) SparkEnv.set(env) // Used to store a URL for each static file/jar together with the file's local timestamp @@ -116,7 +147,8 @@ class SparkContext( // Keeps track of all persisted RDDs private[spark] val persistentRdds = new TimeStampedHashMap[Int, RDD[_]] - private[spark] val metadataCleaner = new MetadataCleaner(MetadataCleanerType.SPARK_CONTEXT, this.cleanup) + private[spark] val metadataCleaner = + new MetadataCleaner(MetadataCleanerType.SPARK_CONTEXT, this.cleanup, conf) // Initialize the Spark UI private[spark] val ui = new SparkUI(this) @@ -126,23 +158,30 @@ class SparkContext( // Add each JAR given through the constructor if (jars != null) { - jars.foreach { addJar(_) } + jars.foreach(addJar) } + private[spark] val executorMemory = conf.getOption("spark.executor.memory") + .orElse(Option(System.getenv("SPARK_MEM"))) + .map(Utils.memoryStringToMb) + .getOrElse(512) + // Environment variables to pass to our executors private[spark] val executorEnvs = HashMap[String, String]() // Note: SPARK_MEM is included for Mesos, but overwritten for standalone mode in ExecutorRunner - for (key <- Seq("SPARK_CLASSPATH", "SPARK_LIBRARY_PATH", "SPARK_JAVA_OPTS", "SPARK_TESTING")) { - val value = System.getenv(key) - if (value != null) { - executorEnvs(key) = value - } + for (key <- Seq("SPARK_CLASSPATH", "SPARK_LIBRARY_PATH", "SPARK_JAVA_OPTS"); + value <- Option(System.getenv(key))) { + executorEnvs(key) = value } - // Since memory can be set with a system property too, use that - executorEnvs("SPARK_MEM") = SparkContext.executorMemoryRequested + "m" - if (environment != null) { - executorEnvs ++= environment + // Convert java options to env vars as a work around + // since we can't set env vars directly in sbt. + for { (envKey, propKey) <- Seq(("SPARK_HOME", "spark.home"), ("SPARK_TESTING", "spark.testing")) + value <- Option(System.getenv(envKey)).orElse(Option(System.getProperty(propKey)))} { + executorEnvs(envKey) = value } + // Since memory can be set with a system property too, use that + executorEnvs("SPARK_MEM") = executorMemory + "m" + executorEnvs ++= conf.getExecutorEnv // Set SPARK_USER for user who is running SparkContext. val sparkUser = Option { @@ -164,24 +203,24 @@ class SparkContext( /** A default Hadoop Configuration for the Hadoop code (e.g. file systems) that we reuse. */ val hadoopConfiguration = { val env = SparkEnv.get - val conf = SparkHadoopUtil.get.newConfiguration() + val hadoopConf = SparkHadoopUtil.get.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")) - conf.set("fs.s3n.awsAccessKeyId", System.getenv("AWS_ACCESS_KEY_ID")) - conf.set("fs.s3.awsSecretAccessKey", System.getenv("AWS_SECRET_ACCESS_KEY")) - conf.set("fs.s3n.awsSecretAccessKey", System.getenv("AWS_SECRET_ACCESS_KEY")) + hadoopConf.set("fs.s3.awsAccessKeyId", System.getenv("AWS_ACCESS_KEY_ID")) + hadoopConf.set("fs.s3n.awsAccessKeyId", System.getenv("AWS_ACCESS_KEY_ID")) + hadoopConf.set("fs.s3.awsSecretAccessKey", System.getenv("AWS_SECRET_ACCESS_KEY")) + hadoopConf.set("fs.s3n.awsSecretAccessKey", System.getenv("AWS_SECRET_ACCESS_KEY")) } // Copy any "spark.hadoop.foo=bar" system properties into conf as "foo=bar" - Utils.getSystemProperties.foreach { case (key, value) => + conf.getAll.foreach { case (key, value) => if (key.startsWith("spark.hadoop.")) { - conf.set(key.substring("spark.hadoop.".length), value) + hadoopConf.set(key.substring("spark.hadoop.".length), value) } } - val bufferSize = System.getProperty("spark.buffer.size", "65536") - conf.set("io.file.buffer.size", bufferSize) - conf + val bufferSize = conf.get("spark.buffer.size", "65536") + hadoopConf.set("io.file.buffer.size", bufferSize) + hadoopConf } private[spark] var checkpointDir: Option[String] = None @@ -191,7 +230,7 @@ class SparkContext( override protected def childValue(parent: Properties): Properties = new Properties(parent) } - private[spark] def getLocalProperties(): Properties = localProperties.get() + private[spark] def getLocalProperties: Properties = localProperties.get() private[spark] def setLocalProperties(props: Properties) { localProperties.set(props) @@ -522,7 +561,7 @@ class SparkContext( addedFiles(key) = System.currentTimeMillis // Fetch the file locally in case a job is executed using DAGScheduler.runLocally(). - Utils.fetchFile(path, new File(SparkFiles.getRootDirectory)) + Utils.fetchFile(path, new File(SparkFiles.getRootDirectory), conf) logInfo("Added file " + path + " at " + key + " with timestamp " + addedFiles(key)) } @@ -692,15 +731,27 @@ class SparkContext( * (in that order of preference). If neither of these is set, return None. */ private[spark] def getSparkHome(): Option[String] = { - if (sparkHome != null) { - Some(sparkHome) - } else if (System.getProperty("spark.home") != null) { - Some(System.getProperty("spark.home")) - } else if (System.getenv("SPARK_HOME") != null) { - Some(System.getenv("SPARK_HOME")) - } else { - None - } + conf.getOption("spark.home").orElse(Option(System.getenv("SPARK_HOME"))) + } + + /** + * Support function for API backtraces. + */ + def setCallSite(site: String) { + setLocalProperty("externalCallSite", site) + } + + /** + * Support function for API backtraces. + */ + def clearCallSite() { + setLocalProperty("externalCallSite", null) + } + + private[spark] def getCallSite(): String = { + val callSite = getLocalProperty("externalCallSite") + if (callSite == null) return Utils.formatSparkCallSite + callSite } /** @@ -715,7 +766,7 @@ class SparkContext( partitions: Seq[Int], allowLocal: Boolean, resultHandler: (Int, U) => Unit) { - val callSite = Utils.formatSparkCallSite + val callSite = getCallSite val cleanedFunc = clean(func) logInfo("Starting job: " + callSite) val start = System.nanoTime @@ -799,7 +850,7 @@ class SparkContext( func: (TaskContext, Iterator[T]) => U, evaluator: ApproximateEvaluator[U, R], timeout: Long): PartialResult[R] = { - val callSite = Utils.formatSparkCallSite + val callSite = getCallSite logInfo("Starting job: " + callSite) val start = System.nanoTime val result = dagScheduler.runApproximateJob(rdd, func, evaluator, callSite, timeout, @@ -819,7 +870,7 @@ class SparkContext( resultFunc: => R): SimpleFutureAction[R] = { val cleanF = clean(processPartition) - val callSite = Utils.formatSparkCallSite + val callSite = getCallSite val waiter = dagScheduler.submitJob( rdd, (context: TaskContext, iter: Iterator[T]) => cleanF(iter), @@ -855,22 +906,15 @@ class SparkContext( /** * Set the directory under which RDDs are going to be checkpointed. The directory must - * be a HDFS path if running on a cluster. If the directory does not exist, it will - * be created. If the directory exists and useExisting is set to true, then the - * exisiting directory will be used. Otherwise an exception will be thrown to - * prevent accidental overriding of checkpoint files in the existing directory. + * be a HDFS path if running on a cluster. */ - def setCheckpointDir(dir: String, useExisting: Boolean = false) { - val path = new Path(dir) - val fs = path.getFileSystem(SparkHadoopUtil.get.newConfiguration()) - if (!useExisting) { - if (fs.exists(path)) { - throw new Exception("Checkpoint directory '" + path + "' already exists.") - } else { - fs.mkdirs(path) - } + def setCheckpointDir(directory: String) { + checkpointDir = Option(directory).map { dir => + val path = new Path(dir, UUID.randomUUID().toString) + val fs = path.getFileSystem(hadoopConfiguration) + fs.mkdirs(path) + fs.getFileStatus(path).getPath().toString } - checkpointDir = Some(dir) } /** Default level of parallelism to use when not given by user (e.g. parallelize and makeRDD). */ @@ -994,7 +1038,7 @@ object SparkContext { /** * Find the JAR from which a given class was loaded, to make it easy for users to pass - * their JARs to SparkContext + * their JARs to SparkContext. */ def jarOfClass(cls: Class[_]): Seq[String] = { val uri = cls.getResource("/" + cls.getName.replace('.', '/') + ".class") @@ -1011,21 +1055,44 @@ object SparkContext { } } - /** Find the JAR that contains the class of a particular object */ + /** + * Find the JAR that contains the class of a particular object, to make it easy for users + * to pass their JARs to SparkContext. In most cases you can call jarOfObject(this) in + * your driver program. + */ def jarOfObject(obj: AnyRef): Seq[String] = jarOfClass(obj.getClass) - /** Get the amount of memory per executor requested through system properties or SPARK_MEM */ - private[spark] val executorMemoryRequested = { - // TODO: Might need to add some extra memory for the non-heap parts of the JVM - Option(System.getProperty("spark.executor.memory")) - .orElse(Option(System.getenv("SPARK_MEM"))) - .map(Utils.memoryStringToMb) - .getOrElse(512) + /** + * Creates a modified version of a SparkConf with the parameters that can be passed separately + * to SparkContext, to make it easier to write SparkContext's constructors. This ignores + * parameters that are passed as the default value of null, instead of throwing an exception + * like SparkConf would. + */ + private def updatedConf( + conf: SparkConf, + master: String, + appName: String, + sparkHome: String = null, + jars: Seq[String] = Nil, + environment: Map[String, String] = Map()): SparkConf = + { + val res = conf.clone() + res.setMaster(master) + res.setAppName(appName) + if (sparkHome != null) { + res.setSparkHome(sparkHome) + } + if (!jars.isEmpty) { + res.setJars(jars) + } + res.setExecutorEnv(environment.toSeq) + res } - // Creates a task scheduler based on a given master URL. Extracted for testing. - private - def createTaskScheduler(sc: SparkContext, master: String, appName: String): TaskScheduler = { + /** Creates a task scheduler based on a given master URL. Extracted for testing. */ + private def createTaskScheduler(sc: SparkContext, master: String, appName: String) + : TaskScheduler = + { // Regular expression used for local[N] master format val LOCAL_N_REGEX = """local\[([0-9]+)\]""".r // Regular expression for local[N, maxRetries], used in tests with failing tasks @@ -1071,10 +1138,10 @@ object SparkContext { case LOCAL_CLUSTER_REGEX(numSlaves, coresPerSlave, memoryPerSlave) => // Check to make sure memory requested <= memoryPerSlave. Otherwise Spark will just hang. val memoryPerSlaveInt = memoryPerSlave.toInt - if (SparkContext.executorMemoryRequested > memoryPerSlaveInt) { + if (sc.executorMemory > memoryPerSlaveInt) { throw new SparkException( "Asked to launch cluster with %d MB RAM / worker but requested %d MB/worker".format( - memoryPerSlaveInt, SparkContext.executorMemoryRequested)) + memoryPerSlaveInt, sc.executorMemory)) } val scheduler = new TaskSchedulerImpl(sc) @@ -1132,7 +1199,7 @@ object SparkContext { case mesosUrl @ MESOS_REGEX(_) => MesosNativeLibrary.load() val scheduler = new TaskSchedulerImpl(sc) - val coarseGrained = System.getProperty("spark.mesos.coarse", "false").toBoolean + val coarseGrained = sc.conf.get("spark.mesos.coarse", "false").toBoolean val url = mesosUrl.stripPrefix("mesos://") // strip scheme from raw Mesos URLs val backend = if (coarseGrained) { new CoarseMesosSchedulerBackend(scheduler, sc, url, appName) diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index 826f5c2d8c..634a94f0a7 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -40,7 +40,7 @@ import com.google.common.collect.MapMaker * objects needs to have the right SparkEnv set. You can get the current environment with * SparkEnv.get (e.g. after creating a SparkContext) and set it with SparkEnv.set. */ -class SparkEnv ( +class SparkEnv private[spark] ( val executorId: String, val actorSystem: ActorSystem, val serializerManager: SerializerManager, @@ -54,7 +54,8 @@ class SparkEnv ( val connectionManager: ConnectionManager, val httpFileServer: HttpFileServer, val sparkFilesDir: String, - val metricsSystem: MetricsSystem) { + val metricsSystem: MetricsSystem, + val conf: SparkConf) { private val pythonWorkers = mutable.HashMap[(String, Map[String, String]), PythonWorkerFactory]() @@ -62,7 +63,7 @@ class SparkEnv ( // (e.g., HadoopFileRDD uses this to cache JobConfs and InputFormats). private[spark] val hadoopJobMetadata = new MapMaker().softValues().makeMap[String, Any]() - def stop() { + private[spark] def stop() { pythonWorkers.foreach { case(key, worker) => worker.stop() } httpFileServer.stop() mapOutputTracker.stop() @@ -78,6 +79,7 @@ class SparkEnv ( //actorSystem.awaitTermination() } + private[spark] def createPythonWorker(pythonExec: String, envVars: Map[String, String]): java.net.Socket = { synchronized { val key = (pythonExec, envVars) @@ -106,33 +108,35 @@ object SparkEnv extends Logging { /** * Returns the ThreadLocal SparkEnv. */ - def getThreadLocal : SparkEnv = { + def getThreadLocal: SparkEnv = { env.get() } - def createFromSystemProperties( + private[spark] def create( + conf: SparkConf, executorId: String, hostname: String, port: Int, isDriver: Boolean, isLocal: Boolean): SparkEnv = { - val (actorSystem, boundPort) = AkkaUtils.createActorSystem("spark", hostname, port) + val (actorSystem, boundPort) = AkkaUtils.createActorSystem("spark", hostname, port, + conf = conf) // Bit of a hack: If this is the driver and our port was 0 (meaning bind to any free port), // figure out which port number Akka actually bound to and set spark.driver.port to it. if (isDriver && port == 0) { - System.setProperty("spark.driver.port", boundPort.toString) + conf.set("spark.driver.port", boundPort.toString) } // set only if unset until now. - if (System.getProperty("spark.hostPort", null) == null) { + if (!conf.contains("spark.hostPort")) { if (!isDriver){ // unexpected Utils.logErrorWithStack("Unexpected NOT to have spark.hostPort set") } Utils.checkHost(hostname) - System.setProperty("spark.hostPort", hostname + ":" + boundPort) + conf.set("spark.hostPort", hostname + ":" + boundPort) } val classLoader = Thread.currentThread.getContextClassLoader @@ -140,25 +144,26 @@ object SparkEnv extends Logging { // Create an instance of the class named by the given Java system property, or by // defaultClassName if the property is not set, and return it as a T def instantiateClass[T](propertyName: String, defaultClassName: String): T = { - val name = System.getProperty(propertyName, defaultClassName) + val name = conf.get(propertyName, defaultClassName) Class.forName(name, true, classLoader).newInstance().asInstanceOf[T] } val serializerManager = new SerializerManager val serializer = serializerManager.setDefault( - System.getProperty("spark.serializer", "org.apache.spark.serializer.JavaSerializer")) + conf.get("spark.serializer", "org.apache.spark.serializer.JavaSerializer"), conf) val closureSerializer = serializerManager.get( - System.getProperty("spark.closure.serializer", "org.apache.spark.serializer.JavaSerializer")) + conf.get("spark.closure.serializer", "org.apache.spark.serializer.JavaSerializer"), + conf) def registerOrLookup(name: String, newActor: => Actor): Either[ActorRef, ActorSelection] = { if (isDriver) { logInfo("Registering " + name) Left(actorSystem.actorOf(Props(newActor), name = name)) } else { - val driverHost: String = System.getProperty("spark.driver.host", "localhost") - val driverPort: Int = System.getProperty("spark.driver.port", "7077").toInt + val driverHost: String = conf.get("spark.driver.host", "localhost") + val driverPort: Int = conf.get("spark.driver.port", "7077").toInt Utils.checkHost(driverHost, "Expected hostname") val url = "akka.tcp://spark@%s:%s/user/%s".format(driverHost, driverPort, name) logInfo("Connecting to " + name + ": " + url) @@ -168,21 +173,21 @@ object SparkEnv extends Logging { val blockManagerMaster = new BlockManagerMaster(registerOrLookup( "BlockManagerMaster", - new BlockManagerMasterActor(isLocal))) - val blockManager = new BlockManager(executorId, actorSystem, blockManagerMaster, serializer) + new BlockManagerMasterActor(isLocal, conf)), conf) + val blockManager = new BlockManager(executorId, actorSystem, blockManagerMaster, serializer, conf) val connectionManager = blockManager.connectionManager - val broadcastManager = new BroadcastManager(isDriver) + val broadcastManager = new BroadcastManager(isDriver, conf) val cacheManager = new CacheManager(blockManager) // Have to assign trackerActor after initialization as MapOutputTrackerActor // requires the MapOutputTracker itself val mapOutputTracker = if (isDriver) { - new MapOutputTrackerMaster() + new MapOutputTrackerMaster(conf) } else { - new MapOutputTracker() + new MapOutputTracker(conf) } mapOutputTracker.trackerActor = registerOrLookup( "MapOutputTracker", @@ -193,12 +198,12 @@ object SparkEnv extends Logging { val httpFileServer = new HttpFileServer() httpFileServer.initialize() - System.setProperty("spark.fileserver.uri", httpFileServer.serverUri) + conf.set("spark.fileserver.uri", httpFileServer.serverUri) val metricsSystem = if (isDriver) { - MetricsSystem.createMetricsSystem("driver") + MetricsSystem.createMetricsSystem("driver", conf) } else { - MetricsSystem.createMetricsSystem("executor") + MetricsSystem.createMetricsSystem("executor", conf) } metricsSystem.start() @@ -212,7 +217,7 @@ object SparkEnv extends Logging { } // Warn about deprecated spark.cache.class property - if (System.getProperty("spark.cache.class") != null) { + if (conf.contains("spark.cache.class")) { logWarning("The spark.cache.class property is no longer being used! Specify storage " + "levels using the RDD.persist() method instead.") } @@ -231,6 +236,7 @@ object SparkEnv extends Logging { connectionManager, httpFileServer, sparkFilesDir, - metricsSystem) + metricsSystem, + conf) } } diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala index 363667fa86..55c87450ac 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala @@ -611,6 +611,42 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kClassTag: ClassTag[K * Return an RDD with the values of each tuple. */ def values(): JavaRDD[V] = JavaRDD.fromRDD[V](rdd.map(_._2)) + + /** + * Return approximate number of distinct values for each key in this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. Uses the provided + * Partitioner to partition the output RDD. + */ + def countApproxDistinctByKey(relativeSD: Double, partitioner: Partitioner): JavaRDD[(K, Long)] = { + rdd.countApproxDistinctByKey(relativeSD, partitioner) + } + + /** + * Return approximate number of distinct values for each key this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. The default value of + * relativeSD is 0.05. Hash-partitions the output RDD using the existing partitioner/parallelism + * level. + */ + def countApproxDistinctByKey(relativeSD: Double = 0.05): JavaRDD[(K, Long)] = { + rdd.countApproxDistinctByKey(relativeSD) + } + + + /** + * Return approximate number of distinct values for each key in this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. HashPartitions the + * output RDD into numPartitions. + * + */ + def countApproxDistinctByKey(relativeSD: Double, numPartitions: Int): JavaRDD[(K, Long)] = { + rdd.countApproxDistinctByKey(relativeSD, numPartitions) + } } object JavaPairRDD { diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala b/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala index f344804b4c..924d8af060 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala @@ -444,4 +444,15 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable { val comp = com.google.common.collect.Ordering.natural().asInstanceOf[Comparator[T]] takeOrdered(num, comp) } + + /** + * Return approximate number of distinct elements in the RDD. + * + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. The default value of + * relativeSD is 0.05. + */ + def countApproxDistinct(relativeSD: Double = 0.05): Long = rdd.countApproxDistinct(relativeSD) + } diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala index acf328aa6a..e93b10fd7e 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala @@ -29,17 +29,22 @@ import org.apache.hadoop.mapred.JobConf import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat} import com.google.common.base.Optional -import org.apache.spark.{Accumulable, AccumulableParam, Accumulator, AccumulatorParam, SparkContext} +import org.apache.spark._ import org.apache.spark.SparkContext.IntAccumulatorParam import org.apache.spark.SparkContext.DoubleAccumulatorParam import org.apache.spark.broadcast.Broadcast import org.apache.spark.rdd.RDD +import scala.Tuple2 /** * 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 { + /** + * @param conf a [[org.apache.spark.SparkConf]] object specifying Spark parameters + */ + def this(conf: SparkConf) = this(new SparkContext(conf)) /** * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). @@ -50,6 +55,14 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork /** * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). * @param appName A name for your application, to display on the cluster web UI + * @param conf a [[org.apache.spark.SparkConf]] object specifying other Spark parameters + */ + def this(master: String, appName: String, conf: SparkConf) = + this(conf.setMaster(master).setAppName(appName)) + + /** + * @param master Cluster URL to connect to (e.g. mesos://host:port, spark://host:port, local[4]). + * @param appName A name for your application, to display on the cluster web UI * @param sparkHome The SPARK_HOME directory on the slave nodes * @param jarFile JAR file to send to the cluster. This can be a path on the local file system * or an HDFS, HTTP, HTTPS, or FTP URL. @@ -381,20 +394,7 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork /** * Set the directory under which RDDs are going to be checkpointed. The directory must - * be a HDFS path if running on a cluster. If the directory does not exist, it will - * be created. If the directory exists and useExisting is set to true, then the - * exisiting directory will be used. Otherwise an exception will be thrown to - * prevent accidental overriding of checkpoint files in the existing directory. - */ - def setCheckpointDir(dir: String, useExisting: Boolean) { - sc.setCheckpointDir(dir, useExisting) - } - - /** - * Set the directory under which RDDs are going to be checkpointed. The directory must - * be a HDFS path if running on a cluster. If the directory does not exist, it will - * be created. If the directory exists, an exception will be thrown to prevent accidental - * overriding of checkpoint files. + * be a HDFS path if running on a cluster. */ def setCheckpointDir(dir: String) { sc.setCheckpointDir(dir) @@ -405,10 +405,36 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork implicitly[ClassTag[AnyRef]].asInstanceOf[ClassTag[T]] new JavaRDD(sc.checkpointFile(path)) } + + /** + * Return a copy of this JavaSparkContext's configuration. The configuration ''cannot'' be + * changed at runtime. + */ + def getConf: SparkConf = sc.getConf + + /** + * Pass-through to SparkContext.setCallSite. For API support only. + */ + def setCallSite(site: String) { + sc.setCallSite(site) + } + + /** + * Pass-through to SparkContext.setCallSite. For API support only. + */ + def clearCallSite() { + sc.clearCallSite() + } } object JavaSparkContext { implicit def fromSparkContext(sc: SparkContext): JavaSparkContext = new JavaSparkContext(sc) implicit def toSparkContext(jsc: JavaSparkContext): SparkContext = jsc.sc + + /** + * Find the JAR from which a given class was loaded, to make it easy for users to pass + * their JARs to SparkContext. + */ + def jarOfClass(cls: Class[_]) = SparkContext.jarOfClass(cls).toArray } diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala index ca42c76928..32cc70e8c9 100644 --- a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala @@ -41,7 +41,7 @@ private[spark] class PythonRDD[T: ClassTag]( accumulator: Accumulator[JList[Array[Byte]]]) extends RDD[Array[Byte]](parent) { - val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt + val bufferSize = conf.get("spark.buffer.size", "65536").toInt override def getPartitions = parent.partitions @@ -250,7 +250,7 @@ private class PythonAccumulatorParam(@transient serverHost: String, serverPort: Utils.checkHost(serverHost, "Expected hostname") - val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt + val bufferSize = SparkEnv.get.conf.get("spark.buffer.size", "65536").toInt override def zero(value: JList[Array[Byte]]): JList[Array[Byte]] = new JArrayList diff --git a/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala index 43c18294c5..0fc478a419 100644 --- a/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/Broadcast.scala @@ -31,8 +31,8 @@ abstract class Broadcast[T](private[spark] val id: Long) extends Serializable { override def toString = "Broadcast(" + id + ")" } -private[spark] -class BroadcastManager(val _isDriver: Boolean) extends Logging with Serializable { +private[spark] +class BroadcastManager(val _isDriver: Boolean, conf: SparkConf) extends Logging with Serializable { private var initialized = false private var broadcastFactory: BroadcastFactory = null @@ -43,14 +43,14 @@ class BroadcastManager(val _isDriver: Boolean) extends Logging with Serializable private def initialize() { synchronized { if (!initialized) { - val broadcastFactoryClass = System.getProperty( + val broadcastFactoryClass = conf.get( "spark.broadcast.factory", "org.apache.spark.broadcast.HttpBroadcastFactory") broadcastFactory = Class.forName(broadcastFactoryClass).newInstance.asInstanceOf[BroadcastFactory] // Initialize appropriate BroadcastFactory and BroadcastObject - broadcastFactory.initialize(isDriver) + broadcastFactory.initialize(isDriver, conf) initialized = true } diff --git a/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala b/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala index 68bff75b90..fb161ce69d 100644 --- a/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/BroadcastFactory.scala @@ -17,6 +17,8 @@ package org.apache.spark.broadcast +import org.apache.spark.SparkConf + /** * An interface for all the broadcast implementations in Spark (to allow * multiple broadcast implementations). SparkContext uses a user-specified @@ -24,7 +26,7 @@ package org.apache.spark.broadcast * entire Spark job. */ private[spark] trait BroadcastFactory { - def initialize(isDriver: Boolean): Unit + def initialize(isDriver: Boolean, conf: SparkConf): Unit def newBroadcast[T](value: T, isLocal: Boolean, id: Long): Broadcast[T] def stop(): Unit } diff --git a/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala index 47db720416..db596d5fcc 100644 --- a/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala @@ -24,14 +24,14 @@ import java.util.concurrent.TimeUnit import it.unimi.dsi.fastutil.io.FastBufferedInputStream import it.unimi.dsi.fastutil.io.FastBufferedOutputStream -import org.apache.spark.{HttpServer, Logging, SparkEnv} +import org.apache.spark.{SparkConf, HttpServer, Logging, SparkEnv} import org.apache.spark.io.CompressionCodec import org.apache.spark.storage.{BroadcastBlockId, StorageLevel} import org.apache.spark.util.{MetadataCleaner, MetadataCleanerType, TimeStampedHashSet, Utils} private[spark] class HttpBroadcast[T](@transient var value_ : T, isLocal: Boolean, id: Long) extends Broadcast[T](id) with Logging with Serializable { - + def value = value_ def blockId = BroadcastBlockId(id) @@ -40,7 +40,7 @@ private[spark] class HttpBroadcast[T](@transient var value_ : T, isLocal: Boolea SparkEnv.get.blockManager.putSingle(blockId, value_, StorageLevel.MEMORY_AND_DISK, false) } - if (!isLocal) { + if (!isLocal) { HttpBroadcast.write(id, value_) } @@ -64,7 +64,7 @@ private[spark] class HttpBroadcast[T](@transient var value_ : T, isLocal: Boolea } private[spark] class HttpBroadcastFactory extends BroadcastFactory { - def initialize(isDriver: Boolean) { HttpBroadcast.initialize(isDriver) } + def initialize(isDriver: Boolean, conf: SparkConf) { HttpBroadcast.initialize(isDriver, conf) } def newBroadcast[T](value_ : T, isLocal: Boolean, id: Long) = new HttpBroadcast[T](value_, isLocal, id) @@ -81,44 +81,51 @@ private object HttpBroadcast extends Logging { private var serverUri: String = null private var server: HttpServer = null + // TODO: This shouldn't be a global variable so that multiple SparkContexts can coexist private val files = new TimeStampedHashSet[String] - private val cleaner = new MetadataCleaner(MetadataCleanerType.HTTP_BROADCAST, cleanup) + private var cleaner: MetadataCleaner = null - private val httpReadTimeout = TimeUnit.MILLISECONDS.convert(5,TimeUnit.MINUTES).toInt + private val httpReadTimeout = TimeUnit.MILLISECONDS.convert(5, TimeUnit.MINUTES).toInt - private lazy val compressionCodec = CompressionCodec.createCodec() + private var compressionCodec: CompressionCodec = null - def initialize(isDriver: Boolean) { + def initialize(isDriver: Boolean, conf: SparkConf) { synchronized { if (!initialized) { - bufferSize = System.getProperty("spark.buffer.size", "65536").toInt - compress = System.getProperty("spark.broadcast.compress", "true").toBoolean + bufferSize = conf.get("spark.buffer.size", "65536").toInt + compress = conf.get("spark.broadcast.compress", "true").toBoolean if (isDriver) { - createServer() + createServer(conf) + conf.set("spark.httpBroadcast.uri", serverUri) } - serverUri = System.getProperty("spark.httpBroadcast.uri") + serverUri = conf.get("spark.httpBroadcast.uri") + cleaner = new MetadataCleaner(MetadataCleanerType.HTTP_BROADCAST, cleanup, conf) + compressionCodec = CompressionCodec.createCodec(conf) initialized = true } } } - + def stop() { synchronized { if (server != null) { server.stop() server = null } + if (cleaner != null) { + cleaner.cancel() + cleaner = null + } + compressionCodec = null initialized = false - cleaner.cancel() } } - private def createServer() { - broadcastDir = Utils.createTempDir(Utils.getLocalDir) + private def createServer(conf: SparkConf) { + broadcastDir = Utils.createTempDir(Utils.getLocalDir(conf)) server = new HttpServer(broadcastDir) server.start() serverUri = server.uri - System.setProperty("spark.httpBroadcast.uri", serverUri) logInfo("Broadcast server started at " + serverUri) } @@ -143,7 +150,7 @@ private object HttpBroadcast extends Logging { val in = { val httpConnection = new URL(url).openConnection() httpConnection.setReadTimeout(httpReadTimeout) - val inputStream = httpConnection.getInputStream() + val inputStream = httpConnection.getInputStream if (compress) { compressionCodec.compressedInputStream(inputStream) } else { diff --git a/core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala index 073a0a5029..9530938278 100644 --- a/core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala @@ -83,13 +83,13 @@ extends Broadcast[T](id) with Logging with Serializable { case None => val start = System.nanoTime logInfo("Started reading broadcast variable " + id) - + // Initialize @transient variables that will receive garbage values from the master. resetWorkerVariables() if (receiveBroadcast(id)) { value_ = TorrentBroadcast.unBlockifyObject[T](arrayOfBlocks, totalBytes, totalBlocks) - + // Store the merged copy in cache so that the next worker doesn't need to rebuild it. // This creates a tradeoff between memory usage and latency. // Storing copy doubles the memory footprint; not storing doubles deserialization cost. @@ -122,14 +122,14 @@ extends Broadcast[T](id) with Logging with Serializable { while (attemptId > 0 && totalBlocks == -1) { TorrentBroadcast.synchronized { SparkEnv.get.blockManager.getSingle(metaId) match { - case Some(x) => + case Some(x) => val tInfo = x.asInstanceOf[TorrentInfo] totalBlocks = tInfo.totalBlocks totalBytes = tInfo.totalBytes arrayOfBlocks = new Array[TorrentBlock](totalBlocks) hasBlocks = 0 - - case None => + + case None => Thread.sleep(500) } } @@ -145,13 +145,13 @@ extends Broadcast[T](id) with Logging with Serializable { val pieceId = BroadcastHelperBlockId(broadcastId, "piece" + pid) TorrentBroadcast.synchronized { SparkEnv.get.blockManager.getSingle(pieceId) match { - case Some(x) => + case Some(x) => arrayOfBlocks(pid) = x.asInstanceOf[TorrentBlock] hasBlocks += 1 SparkEnv.get.blockManager.putSingle( pieceId, arrayOfBlocks(pid), StorageLevel.MEMORY_AND_DISK, true) - - case None => + + case None => throw new SparkException("Failed to get " + pieceId + " of " + broadcastId) } } @@ -166,21 +166,22 @@ private object TorrentBroadcast extends Logging { private var initialized = false - - def initialize(_isDriver: Boolean) { + private var conf: SparkConf = null + def initialize(_isDriver: Boolean, conf: SparkConf) { + TorrentBroadcast.conf = conf //TODO: we might have to fix it in tests synchronized { if (!initialized) { initialized = true } } } - + def stop() { initialized = false } - val BLOCK_SIZE = System.getProperty("spark.broadcast.blockSize", "4096").toInt * 1024 - + lazy val BLOCK_SIZE = conf.get("spark.broadcast.blockSize", "4096").toInt * 1024 + def blockifyObject[T](obj: T): TorrentInfo = { val byteArray = Utils.serialize[T](obj) val bais = new ByteArrayInputStream(byteArray) @@ -209,7 +210,7 @@ extends Logging { } def unBlockifyObject[T](arrayOfBlocks: Array[TorrentBlock], - totalBytes: Int, + totalBytes: Int, totalBlocks: Int): T = { var retByteArray = new Array[Byte](totalBytes) for (i <- 0 until totalBlocks) { @@ -222,23 +223,23 @@ extends Logging { } private[spark] case class TorrentBlock( - blockID: Int, - byteArray: Array[Byte]) + blockID: Int, + byteArray: Array[Byte]) extends Serializable private[spark] case class TorrentInfo( @transient arrayOfBlocks : Array[TorrentBlock], - totalBlocks: Int, - totalBytes: Int) + totalBlocks: Int, + totalBytes: Int) extends Serializable { - - @transient var hasBlocks = 0 + + @transient var hasBlocks = 0 } private[spark] class TorrentBroadcastFactory extends BroadcastFactory { - - def initialize(isDriver: Boolean) { TorrentBroadcast.initialize(isDriver) } + + def initialize(isDriver: Boolean, conf: SparkConf) { TorrentBroadcast.initialize(isDriver, conf) } def newBroadcast[T](value_ : T, isLocal: Boolean, id: Long) = new TorrentBroadcast[T](value_, isLocal, id) diff --git a/core/src/main/scala/org/apache/spark/deploy/FaultToleranceTest.scala b/core/src/main/scala/org/apache/spark/deploy/FaultToleranceTest.scala index 0aa8852649..4dfb19ed8a 100644 --- a/core/src/main/scala/org/apache/spark/deploy/FaultToleranceTest.scala +++ b/core/src/main/scala/org/apache/spark/deploy/FaultToleranceTest.scala @@ -190,7 +190,7 @@ private[spark] object FaultToleranceTest extends App with Logging { /** Creates a SparkContext, which constructs a Client to interact with our cluster. */ def createClient() = { if (sc != null) { sc.stop() } - // Counter-hack: Because of a hack in SparkEnv#createFromSystemProperties() that changes this + // Counter-hack: Because of a hack in SparkEnv#create() that changes this // property, we need to reset it. System.setProperty("spark.driver.port", "0") sc = new SparkContext(getMasterUrls(masters), "fault-tolerance", containerSparkHome) @@ -417,4 +417,4 @@ private[spark] object Docker extends Logging { "docker ps -l -q".!(ProcessLogger(line => id = line)) new DockerId(id) } -}
\ No newline at end of file +} diff --git a/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala index 59d12a3e6f..ffc0cb0903 100644 --- a/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala +++ b/core/src/main/scala/org/apache/spark/deploy/LocalSparkCluster.scala @@ -22,7 +22,7 @@ import akka.actor.ActorSystem import org.apache.spark.deploy.worker.Worker import org.apache.spark.deploy.master.Master import org.apache.spark.util.Utils -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} import scala.collection.mutable.ArrayBuffer @@ -43,7 +43,8 @@ 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 conf = new SparkConf(false) + val (masterSystem, masterPort, _) = Master.startSystemAndActor(localHostname, 0, 0, conf) masterActorSystems += masterSystem val masterUrl = "spark://" + localHostname + ":" + masterPort val masters = Array(masterUrl) @@ -55,7 +56,7 @@ class LocalSparkCluster(numWorkers: Int, coresPerWorker: Int, memoryPerWorker: I workerActorSystems += workerSystem } - return masters + masters } def stop() { diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala index fc1537f796..27dc42bf7e 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala @@ -34,10 +34,10 @@ class SparkHadoopUtil { UserGroupInformation.setConfiguration(conf) def runAsUser(user: String)(func: () => Unit) { - // if we are already running as the user intended there is no reason to do the doAs. It + // if we are already running as the user intended there is no reason to do the doAs. It // will actually break secure HDFS access as it doesn't fill in the credentials. Also if - // the user is UNKNOWN then we shouldn't be creating a remote unknown user - // (this is actually the path spark on yarn takes) since SPARK_USER is initialized only + // the user is UNKNOWN then we shouldn't be creating a remote unknown user + // (this is actually the path spark on yarn takes) since SPARK_USER is initialized only // in SparkContext. val currentUser = Option(System.getProperty("user.name")). getOrElse(SparkContext.SPARK_UNKNOWN_USER) @@ -67,11 +67,15 @@ class SparkHadoopUtil { } object SparkHadoopUtil { + private val hadoop = { - val yarnMode = java.lang.Boolean.valueOf(System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE"))) + 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] + Class.forName("org.apache.spark.deploy.yarn.YarnSparkHadoopUtil") + .newInstance() + .asInstanceOf[SparkHadoopUtil] } catch { case th: Throwable => throw new SparkException("Unable to load YARN support", th) } diff --git a/core/src/main/scala/org/apache/spark/deploy/client/Client.scala b/core/src/main/scala/org/apache/spark/deploy/client/Client.scala index 953755e40d..481026eaa2 100644 --- a/core/src/main/scala/org/apache/spark/deploy/client/Client.scala +++ b/core/src/main/scala/org/apache/spark/deploy/client/Client.scala @@ -19,20 +19,19 @@ package org.apache.spark.deploy.client import java.util.concurrent.TimeoutException -import scala.concurrent.duration._ import scala.concurrent.Await +import scala.concurrent.duration._ import akka.actor._ import akka.pattern.ask -import akka.remote.{RemotingLifecycleEvent, DisassociatedEvent} +import akka.remote.{AssociationErrorEvent, DisassociatedEvent, RemotingLifecycleEvent} -import org.apache.spark.{SparkException, Logging} +import org.apache.spark.{Logging, SparkConf, SparkException} import org.apache.spark.deploy.{ApplicationDescription, ExecutorState} import org.apache.spark.deploy.DeployMessages._ import org.apache.spark.deploy.master.Master import org.apache.spark.util.AkkaUtils - /** * The main class used to talk to a Spark deploy cluster. Takes a master URL, an app description, * and a listener for cluster events, and calls back the listener when various events occur. @@ -43,7 +42,8 @@ private[spark] class Client( actorSystem: ActorSystem, masterUrls: Array[String], appDescription: ApplicationDescription, - listener: ClientListener) + listener: ClientListener, + conf: SparkConf) extends Logging { val REGISTRATION_TIMEOUT = 20.seconds @@ -111,6 +111,12 @@ private[spark] class Client( } } + private def isPossibleMaster(remoteUrl: Address) = { + masterUrls.map(s => Master.toAkkaUrl(s)) + .map(u => AddressFromURIString(u).hostPort) + .contains(remoteUrl.hostPort) + } + override def receive = { case RegisteredApplication(appId_, masterUrl) => appId = appId_ @@ -146,6 +152,9 @@ private[spark] class Client( logWarning(s"Connection to $address failed; waiting for master to reconnect...") markDisconnected() + case AssociationErrorEvent(cause, _, address, _) if isPossibleMaster(address) => + logWarning(s"Could not connect to $address: $cause") + case StopClient => markDead() sender ! true @@ -178,7 +187,7 @@ private[spark] class Client( def stop() { if (actor != null) { try { - val timeout = AkkaUtils.askTimeout + val timeout = AkkaUtils.askTimeout(conf) val future = actor.ask(StopClient)(timeout) Await.result(future, timeout) } catch { 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 index 5b62d3ba6c..ef649fd80c 100644 --- a/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala +++ b/core/src/main/scala/org/apache/spark/deploy/client/TestClient.scala @@ -18,7 +18,7 @@ package org.apache.spark.deploy.client import org.apache.spark.util.{Utils, AkkaUtils} -import org.apache.spark.{Logging} +import org.apache.spark.{SparkConf, SparkContext, Logging} import org.apache.spark.deploy.{Command, ApplicationDescription} private[spark] object TestClient { @@ -45,11 +45,13 @@ private[spark] object TestClient { def main(args: Array[String]) { val url = args(0) - val (actorSystem, port) = AkkaUtils.createActorSystem("spark", Utils.localIpAddress, 0) + val (actorSystem, port) = AkkaUtils.createActorSystem("spark", Utils.localIpAddress, 0, + conf = new SparkConf) val desc = new ApplicationDescription( - "TestClient", 1, 512, Command("spark.deploy.client.TestExecutor", Seq(), Map()), "dummy-spark-home", "ignored") + "TestClient", 1, 512, Command("spark.deploy.client.TestExecutor", Seq(), Map()), + "dummy-spark-home", "ignored") val listener = new TestListener - val client = new Client(actorSystem, Array(url), desc, listener) + val client = new Client(actorSystem, Array(url), desc, listener, new SparkConf) client.start() actorSystem.awaitTermination() } diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index eebd0794b8..7b696cfcca 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -29,7 +29,7 @@ import akka.pattern.ask import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} import akka.serialization.SerializationExtension -import org.apache.spark.{Logging, SparkException} +import org.apache.spark.{SparkConf, SparkContext, Logging, SparkException} import org.apache.spark.deploy.{ApplicationDescription, ExecutorState} import org.apache.spark.deploy.DeployMessages._ import org.apache.spark.deploy.master.MasterMessages._ @@ -38,14 +38,16 @@ import org.apache.spark.metrics.MetricsSystem import org.apache.spark.util.{AkkaUtils, Utils} private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Actor with Logging { - import context.dispatcher + import context.dispatcher // to use Akka's scheduler.schedule() + + val conf = new SparkConf 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 - val RECOVERY_DIR = System.getProperty("spark.deploy.recoveryDirectory", "") - val RECOVERY_MODE = System.getProperty("spark.deploy.recoveryMode", "NONE") + val WORKER_TIMEOUT = conf.get("spark.worker.timeout", "60").toLong * 1000 + val RETAINED_APPLICATIONS = conf.get("spark.deploy.retainedApplications", "200").toInt + val REAPER_ITERATIONS = conf.get("spark.dead.worker.persistence", "15").toInt + val RECOVERY_DIR = conf.get("spark.deploy.recoveryDirectory", "") + val RECOVERY_MODE = conf.get("spark.deploy.recoveryMode", "NONE") var nextAppNumber = 0 val workers = new HashSet[WorkerInfo] @@ -63,8 +65,8 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act Utils.checkHost(host, "Expected hostname") - val masterMetricsSystem = MetricsSystem.createMetricsSystem("master") - val applicationMetricsSystem = MetricsSystem.createMetricsSystem("applications") + val masterMetricsSystem = MetricsSystem.createMetricsSystem("master", conf) + val applicationMetricsSystem = MetricsSystem.createMetricsSystem("applications", conf) val masterSource = new MasterSource(this) val webUi = new MasterWebUI(this, webUiPort) @@ -86,7 +88,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act // As a temporary workaround before better ways of configuring memory, we allow users to set // a flag that will perform round-robin scheduling across the nodes (spreading out each app // among all the nodes) instead of trying to consolidate each app onto a small # of nodes. - val spreadOutApps = System.getProperty("spark.deploy.spreadOut", "true").toBoolean + val spreadOutApps = conf.get("spark.deploy.spreadOut", "true").toBoolean override def preStart() { logInfo("Starting Spark master at " + masterUrl) @@ -103,7 +105,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act persistenceEngine = RECOVERY_MODE match { case "ZOOKEEPER" => logInfo("Persisting recovery state to ZooKeeper") - new ZooKeeperPersistenceEngine(SerializationExtension(context.system)) + new ZooKeeperPersistenceEngine(SerializationExtension(context.system), conf) case "FILESYSTEM" => logInfo("Persisting recovery state to directory: " + RECOVERY_DIR) new FileSystemPersistenceEngine(RECOVERY_DIR, SerializationExtension(context.system)) @@ -113,7 +115,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act leaderElectionAgent = RECOVERY_MODE match { case "ZOOKEEPER" => - context.actorOf(Props(classOf[ZooKeeperLeaderElectionAgent], self, masterUrl)) + context.actorOf(Props(classOf[ZooKeeperLeaderElectionAgent], self, masterUrl, conf)) case _ => context.actorOf(Props(classOf[MonarchyLeaderAgent], self)) } @@ -495,7 +497,7 @@ private[spark] class Master(host: String, port: Int, webUiPort: Int) extends Act 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 + workers -= worker // we've seen this DEAD worker in the UI, etc. for long enough; cull it } } } @@ -507,8 +509,9 @@ private[spark] object Master { val sparkUrlRegex = "spark://([^:]+):([0-9]+)".r def main(argStrings: Array[String]) { - val args = new MasterArguments(argStrings) - val (actorSystem, _, _) = startSystemAndActor(args.host, args.port, args.webUiPort) + val conf = new SparkConf + val args = new MasterArguments(argStrings, conf) + val (actorSystem, _, _) = startSystemAndActor(args.host, args.port, args.webUiPort, conf) actorSystem.awaitTermination() } @@ -522,10 +525,12 @@ private[spark] object Master { } } - def startSystemAndActor(host: String, port: Int, webUiPort: Int): (ActorSystem, Int, Int) = { - val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port) + def startSystemAndActor(host: String, port: Int, webUiPort: Int, conf: SparkConf) + : (ActorSystem, Int, Int) = + { + val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port, conf = conf) val actor = actorSystem.actorOf(Props(classOf[Master], host, boundPort, webUiPort), actorName) - val timeout = AkkaUtils.askTimeout + val timeout = AkkaUtils.askTimeout(conf) val respFuture = actor.ask(RequestWebUIPort)(timeout) val resp = Await.result(respFuture, timeout).asInstanceOf[WebUIPortResponse] (actorSystem, boundPort, resp.webUIBoundPort) diff --git a/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala b/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala index 9d89b455fb..e7f3224091 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/MasterArguments.scala @@ -18,16 +18,17 @@ package org.apache.spark.deploy.master import org.apache.spark.util.{Utils, IntParam} +import org.apache.spark.SparkConf /** * Command-line parser for the master. */ -private[spark] class MasterArguments(args: Array[String]) { +private[spark] class MasterArguments(args: Array[String], conf: SparkConf) { var host = Utils.localHostName() var port = 7077 var webUiPort = 8080 - - // Check for settings in environment variables + + // Check for settings in environment variables if (System.getenv("SPARK_MASTER_HOST") != null) { host = System.getenv("SPARK_MASTER_HOST") } @@ -37,8 +38,8 @@ 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 + if (conf.contains("master.ui.port")) { + webUiPort = conf.get("master.ui.port").toInt } parse(args.toList) diff --git a/core/src/main/scala/org/apache/spark/deploy/master/SparkZooKeeperSession.scala b/core/src/main/scala/org/apache/spark/deploy/master/SparkZooKeeperSession.scala index 6cc7fd2ff4..999090ad74 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/SparkZooKeeperSession.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/SparkZooKeeperSession.scala @@ -23,7 +23,7 @@ import org.apache.zookeeper._ import org.apache.zookeeper.Watcher.Event.KeeperState import org.apache.zookeeper.data.Stat -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} /** * Provides a Scala-side interface to the standard ZooKeeper client, with the addition of retry @@ -35,8 +35,9 @@ import org.apache.spark.Logging * Additionally, all commands sent to ZooKeeper will be retried until they either fail too many * times or a semantic exception is thrown (e.g., "node already exists"). */ -private[spark] class SparkZooKeeperSession(zkWatcher: SparkZooKeeperWatcher) extends Logging { - val ZK_URL = System.getProperty("spark.deploy.zookeeper.url", "") +private[spark] class SparkZooKeeperSession(zkWatcher: SparkZooKeeperWatcher, + conf: SparkConf) extends Logging { + val ZK_URL = conf.get("spark.deploy.zookeeper.url", "") val ZK_ACL = ZooDefs.Ids.OPEN_ACL_UNSAFE val ZK_TIMEOUT_MILLIS = 30000 diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperLeaderElectionAgent.scala b/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperLeaderElectionAgent.scala index 7d535b08de..77c23fb9fb 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperLeaderElectionAgent.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperLeaderElectionAgent.scala @@ -21,16 +21,17 @@ import akka.actor.ActorRef import org.apache.zookeeper._ import org.apache.zookeeper.Watcher.Event.EventType -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} import org.apache.spark.deploy.master.MasterMessages._ -private[spark] class ZooKeeperLeaderElectionAgent(val masterActor: ActorRef, masterUrl: String) +private[spark] class ZooKeeperLeaderElectionAgent(val masterActor: ActorRef, + masterUrl: String, conf: SparkConf) extends LeaderElectionAgent with SparkZooKeeperWatcher with Logging { - val WORKING_DIR = System.getProperty("spark.deploy.zookeeper.dir", "/spark") + "/leader_election" + val WORKING_DIR = conf.get("spark.deploy.zookeeper.dir", "/spark") + "/leader_election" private val watcher = new ZooKeeperWatcher() - private val zk = new SparkZooKeeperSession(this) + private val zk = new SparkZooKeeperSession(this, conf) private var status = LeadershipStatus.NOT_LEADER private var myLeaderFile: String = _ private var leaderUrl: String = _ diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperPersistenceEngine.scala b/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperPersistenceEngine.scala index 825344b3bb..52000d4f9c 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperPersistenceEngine.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ZooKeeperPersistenceEngine.scala @@ -17,19 +17,19 @@ package org.apache.spark.deploy.master -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} import org.apache.zookeeper._ import akka.serialization.Serialization -class ZooKeeperPersistenceEngine(serialization: Serialization) +class ZooKeeperPersistenceEngine(serialization: Serialization, conf: SparkConf) extends PersistenceEngine with SparkZooKeeperWatcher with Logging { - val WORKING_DIR = System.getProperty("spark.deploy.zookeeper.dir", "/spark") + "/master_status" + val WORKING_DIR = conf.get("spark.deploy.zookeeper.dir", "/spark") + "/master_status" - val zk = new SparkZooKeeperSession(this) + val zk = new SparkZooKeeperSession(this, conf) zk.connect() 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 index 9ab594b682..ead35662fc 100644 --- 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 @@ -31,7 +31,7 @@ import org.apache.spark.util.{AkkaUtils, Utils} */ private[spark] class MasterWebUI(val master: Master, requestedPort: Int) extends Logging { - val timeout = AkkaUtils.askTimeout + val timeout = AkkaUtils.askTimeout(master.conf) val host = Utils.localHostName() val port = requestedPort diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala index 87531b6719..fcaf4e92b1 100644 --- a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala @@ -25,23 +25,14 @@ import scala.collection.mutable.HashMap import scala.concurrent.duration._ import akka.actor._ -import akka.remote.{ DisassociatedEvent, RemotingLifecycleEvent} - -import org.apache.spark.{SparkException, Logging} +import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} +import org.apache.spark.{Logging, SparkConf, SparkException} import org.apache.spark.deploy.{ExecutorDescription, 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} -import org.apache.spark.deploy.DeployMessages.WorkerStateResponse -import org.apache.spark.deploy.DeployMessages.RegisterWorkerFailed -import org.apache.spark.deploy.DeployMessages.KillExecutor -import org.apache.spark.deploy.DeployMessages.ExecutorStateChanged -import org.apache.spark.deploy.DeployMessages.Heartbeat -import org.apache.spark.deploy.DeployMessages.RegisteredWorker -import org.apache.spark.deploy.DeployMessages.LaunchExecutor -import org.apache.spark.deploy.DeployMessages.RegisterWorker +import org.apache.spark.util.{AkkaUtils, Utils} /** * @param masterUrls Each url should look like spark://host:port. @@ -53,7 +44,8 @@ private[spark] class Worker( cores: Int, memory: Int, masterUrls: Array[String], - workDirPath: String = null) + workDirPath: String = null, + val conf: SparkConf) extends Actor with Logging { import context.dispatcher @@ -63,7 +55,7 @@ private[spark] class Worker( val DATE_FORMAT = new SimpleDateFormat("yyyyMMddHHmmss") // For worker and executor IDs // Send a heartbeat every (heartbeat timeout) / 4 milliseconds - val HEARTBEAT_MILLIS = System.getProperty("spark.worker.timeout", "60").toLong * 1000 / 4 + val HEARTBEAT_MILLIS = conf.get("spark.worker.timeout", "60").toLong * 1000 / 4 val REGISTRATION_TIMEOUT = 20.seconds val REGISTRATION_RETRIES = 3 @@ -92,7 +84,7 @@ private[spark] class Worker( var coresUsed = 0 var memoryUsed = 0 - val metricsSystem = MetricsSystem.createMetricsSystem("worker") + val metricsSystem = MetricsSystem.createMetricsSystem("worker", conf) val workerSource = new WorkerSource(this) def coresFree: Int = cores - coresUsed @@ -275,6 +267,7 @@ private[spark] class Worker( } private[spark] object Worker { + def main(argStrings: Array[String]) { val args = new WorkerArguments(argStrings) val (actorSystem, _) = startSystemAndActor(args.host, args.port, args.webUiPort, args.cores, @@ -283,13 +276,16 @@ private[spark] object Worker { } def startSystemAndActor(host: String, port: Int, webUiPort: Int, cores: Int, memory: Int, - masterUrls: Array[String], workDir: String, workerNumber: Option[Int] = None) - : (ActorSystem, Int) = { + masterUrls: Array[String], workDir: String, workerNumber: Option[Int] = None) + : (ActorSystem, Int) = + { // The LocalSparkCluster runs multiple local sparkWorkerX actor systems + val conf = new SparkConf val systemName = "sparkWorker" + workerNumber.map(_.toString).getOrElse("") - val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port) + val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port, + conf = conf) actorSystem.actorOf(Props(classOf[Worker], host, boundPort, webUiPort, cores, memory, - masterUrls, workDir), name = "Worker") + masterUrls, workDir, conf), name = "Worker") (actorSystem, boundPort) } diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala index 19aa800a95..c382034c99 100644 --- a/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala @@ -22,7 +22,7 @@ import java.io.File import javax.servlet.http.HttpServletRequest import org.eclipse.jetty.server.{Handler, Server} -import org.apache.spark.Logging +import org.apache.spark.{Logging, SparkConf} import org.apache.spark.deploy.worker.Worker import org.apache.spark.ui.{JettyUtils, UIUtils} import org.apache.spark.ui.JettyUtils._ @@ -34,10 +34,10 @@ import org.apache.spark.util.{AkkaUtils, Utils} private[spark] class WorkerWebUI(val worker: Worker, val workDir: File, requestedPort: Option[Int] = None) extends Logging { - val timeout = AkkaUtils.askTimeout + val timeout = AkkaUtils.askTimeout(worker.conf) val host = Utils.localHostName() val port = requestedPort.getOrElse( - System.getProperty("worker.ui.port", WorkerWebUI.DEFAULT_PORT).toInt) + worker.conf.get("worker.ui.port", WorkerWebUI.DEFAULT_PORT).toInt) var server: Option[Server] = None var boundPort: Option[Int] = None diff --git a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index debbdd4c44..53a2b94a52 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -22,7 +22,7 @@ import java.nio.ByteBuffer import akka.actor._ import akka.remote._ -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, SparkContext, Logging} import org.apache.spark.TaskState.TaskState import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ import org.apache.spark.util.{Utils, AkkaUtils} @@ -98,10 +98,10 @@ private[spark] object CoarseGrainedExecutorBackend { // Create a new ActorSystem to run the backend, because we can't create a SparkEnv / Executor // before getting started with all our system properties, etc val (actorSystem, boundPort) = AkkaUtils.createActorSystem("sparkExecutor", hostname, 0, - indestructible = true) + indestructible = true, conf = new SparkConf) // set it val sparkHostPort = hostname + ":" + boundPort - System.setProperty("spark.hostPort", sparkHostPort) +// conf.set("spark.hostPort", sparkHostPort) actorSystem.actorOf( Props(classOf[CoarseGrainedExecutorBackend], driverUrl, executorId, sparkHostPort, cores), name = "Executor") diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index 0f19d7a96b..e51d274d33 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -48,8 +48,6 @@ private[spark] class Executor( private val EMPTY_BYTE_BUFFER = ByteBuffer.wrap(new Array[Byte](0)) - initLogging() - // No ip or host:port - just hostname Utils.checkHost(slaveHostname, "Expected executed slave to be a hostname") // must not have port specified. @@ -58,16 +56,17 @@ private[spark] class Executor( // Make sure the local hostname we report matches the cluster scheduler's name for this host Utils.setCustomHostname(slaveHostname) - // Set spark.* system properties from executor arg - for ((key, value) <- properties) { - System.setProperty(key, value) - } + // Set spark.* properties from executor arg + val conf = new SparkConf(false) + conf.setAll(properties) // 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()) + if (java.lang.Boolean.valueOf( + System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE")))) + { + conf.set("spark.local.dir", getYarnLocalDirs()) } // Create our ClassLoader and set it on this thread @@ -108,7 +107,7 @@ private[spark] class Executor( // Initialize Spark environment (using system properties read above) private val env = { if (!isLocal) { - val _env = SparkEnv.createFromSystemProperties(executorId, slaveHostname, 0, + val _env = SparkEnv.create(conf, executorId, slaveHostname, 0, isDriver = false, isLocal = false) SparkEnv.set(_env) _env.metricsSystem.registerSource(executorSource) @@ -142,11 +141,6 @@ private[spark] class Executor( val tr = runningTasks.get(taskId) if (tr != null) { tr.kill() - // We remove the task also in the finally block in TaskRunner.run. - // The reason we need to remove it here is because killTask might be called before the task - // is even launched, and never reaching that finally block. ConcurrentHashMap's remove is - // idempotent. - runningTasks.remove(taskId) } } @@ -168,6 +162,8 @@ private[spark] class Executor( class TaskRunner(execBackend: ExecutorBackend, taskId: Long, serializedTask: ByteBuffer) extends Runnable { + object TaskKilledException extends Exception + @volatile private var killed = false @volatile private var task: Task[Any] = _ @@ -201,9 +197,11 @@ private[spark] class Executor( // If this task has been killed before we deserialized it, let's quit now. Otherwise, // continue executing the task. if (killed) { - logInfo("Executor killed task " + taskId) - execBackend.statusUpdate(taskId, TaskState.KILLED, ser.serialize(TaskKilled)) - return + // Throw an exception rather than returning, because returning within a try{} block + // causes a NonLocalReturnControl exception to be thrown. The NonLocalReturnControl + // exception will be caught by the catch block, leading to an incorrect ExceptionFailure + // for the task. + throw TaskKilledException } attemptedTask = Some(task) @@ -217,9 +215,7 @@ private[spark] class Executor( // If the task has been killed, let's fail it. if (task.killed) { - logInfo("Executor killed task " + taskId) - execBackend.statusUpdate(taskId, TaskState.KILLED, ser.serialize(TaskKilled)) - return + throw TaskKilledException } val resultSer = SparkEnv.get.serializer.newInstance() @@ -261,6 +257,11 @@ private[spark] class Executor( execBackend.statusUpdate(taskId, TaskState.FAILED, ser.serialize(reason)) } + case TaskKilledException => { + logInfo("Executor killed task " + taskId) + execBackend.statusUpdate(taskId, TaskState.KILLED, ser.serialize(TaskKilled)) + } + case t: Throwable => { val serviceTime = (System.currentTimeMillis() - taskStart).toInt val metrics = attemptedTask.flatMap(t => t.metrics) @@ -303,7 +304,7 @@ private[spark] class Executor( * new classes defined by the REPL as the user types code */ private def addReplClassLoaderIfNeeded(parent: ClassLoader): ClassLoader = { - val classUri = System.getProperty("spark.repl.class.uri") + val classUri = conf.get("spark.repl.class.uri", null) if (classUri != null) { logInfo("Using REPL class URI: " + classUri) try { @@ -331,12 +332,12 @@ private[spark] class Executor( // Fetch missing dependencies for ((name, timestamp) <- newFiles if currentFiles.getOrElse(name, -1L) < timestamp) { logInfo("Fetching " + name + " with timestamp " + timestamp) - Utils.fetchFile(name, new File(SparkFiles.getRootDirectory)) + Utils.fetchFile(name, new File(SparkFiles.getRootDirectory), conf) currentFiles(name) = timestamp } for ((name, timestamp) <- newJars if currentJars.getOrElse(name, -1L) < timestamp) { logInfo("Fetching " + name + " with timestamp " + timestamp) - Utils.fetchFile(name, new File(SparkFiles.getRootDirectory)) + Utils.fetchFile(name, new File(SparkFiles.getRootDirectory), conf) currentJars(name) = timestamp // Add it to our class loader val localName = name.split("/").last diff --git a/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala index 570a979b56..a1e98845f6 100644 --- a/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala +++ b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala @@ -22,6 +22,7 @@ import java.io.{InputStream, OutputStream} import com.ning.compress.lzf.{LZFInputStream, LZFOutputStream} import org.xerial.snappy.{SnappyInputStream, SnappyOutputStream} +import org.apache.spark.{SparkEnv, SparkConf} /** @@ -37,15 +38,15 @@ trait CompressionCodec { private[spark] object CompressionCodec { - - def createCodec(): CompressionCodec = { - createCodec(System.getProperty( + def createCodec(conf: SparkConf): CompressionCodec = { + createCodec(conf, conf.get( "spark.io.compression.codec", classOf[LZFCompressionCodec].getName)) } - def createCodec(codecName: String): CompressionCodec = { - Class.forName(codecName, true, Thread.currentThread.getContextClassLoader) - .newInstance().asInstanceOf[CompressionCodec] + def createCodec(conf: SparkConf, codecName: String): CompressionCodec = { + val ctor = Class.forName(codecName, true, Thread.currentThread.getContextClassLoader) + .getConstructor(classOf[SparkConf]) + ctor.newInstance(conf).asInstanceOf[CompressionCodec] } } @@ -53,7 +54,7 @@ private[spark] object CompressionCodec { /** * LZF implementation of [[org.apache.spark.io.CompressionCodec]]. */ -class LZFCompressionCodec extends CompressionCodec { +class LZFCompressionCodec(conf: SparkConf) extends CompressionCodec { override def compressedOutputStream(s: OutputStream): OutputStream = { new LZFOutputStream(s).setFinishBlockOnFlush(true) @@ -67,10 +68,10 @@ class LZFCompressionCodec extends CompressionCodec { * Snappy implementation of [[org.apache.spark.io.CompressionCodec]]. * Block size can be configured by spark.io.compression.snappy.block.size. */ -class SnappyCompressionCodec extends CompressionCodec { +class SnappyCompressionCodec(conf: SparkConf) extends CompressionCodec { override def compressedOutputStream(s: OutputStream): OutputStream = { - val blockSize = System.getProperty("spark.io.compression.snappy.block.size", "32768").toInt + val blockSize = conf.get("spark.io.compression.snappy.block.size", "32768").toInt new SnappyOutputStream(s, blockSize) } diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala index caab748d60..6f9f29969e 100644 --- a/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala +++ b/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala @@ -26,7 +26,6 @@ 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 diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala index bec0c83be8..9930537b34 100644 --- a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala +++ b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala @@ -24,7 +24,7 @@ import java.util.concurrent.TimeUnit import scala.collection.mutable -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} import org.apache.spark.metrics.sink.{MetricsServlet, Sink} import org.apache.spark.metrics.source.Source @@ -62,10 +62,10 @@ import org.apache.spark.metrics.source.Source * * [options] is the specific property of this source or sink. */ -private[spark] class MetricsSystem private (val instance: String) extends Logging { - initLogging() +private[spark] class MetricsSystem private (val instance: String, + conf: SparkConf) extends Logging { - val confFile = System.getProperty("spark.metrics.conf") + val confFile = conf.get("spark.metrics.conf", null) val metricsConfig = new MetricsConfig(Option(confFile)) val sinks = new mutable.ArrayBuffer[Sink] @@ -159,5 +159,6 @@ private[spark] object MetricsSystem { } } - def createMetricsSystem(instance: String): MetricsSystem = new MetricsSystem(instance) + def createMetricsSystem(instance: String, conf: SparkConf): MetricsSystem = + new MetricsSystem(instance, conf) } diff --git a/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala index 703bc6a9ca..46c40d0a2a 100644 --- a/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/ConnectionManager.scala @@ -37,7 +37,7 @@ import scala.concurrent.duration._ import org.apache.spark.util.Utils -private[spark] class ConnectionManager(port: Int) extends Logging { +private[spark] class ConnectionManager(port: Int, conf: SparkConf) extends Logging { class MessageStatus( val message: Message, @@ -54,22 +54,22 @@ private[spark] class ConnectionManager(port: Int) extends Logging { private val selector = SelectorProvider.provider.openSelector() private val handleMessageExecutor = new ThreadPoolExecutor( - System.getProperty("spark.core.connection.handler.threads.min","20").toInt, - System.getProperty("spark.core.connection.handler.threads.max","60").toInt, - System.getProperty("spark.core.connection.handler.threads.keepalive","60").toInt, TimeUnit.SECONDS, + conf.get("spark.core.connection.handler.threads.min", "20").toInt, + conf.get("spark.core.connection.handler.threads.max", "60").toInt, + conf.get("spark.core.connection.handler.threads.keepalive", "60").toInt, TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable]()) private val handleReadWriteExecutor = new ThreadPoolExecutor( - System.getProperty("spark.core.connection.io.threads.min","4").toInt, - System.getProperty("spark.core.connection.io.threads.max","32").toInt, - System.getProperty("spark.core.connection.io.threads.keepalive","60").toInt, TimeUnit.SECONDS, + conf.get("spark.core.connection.io.threads.min", "4").toInt, + conf.get("spark.core.connection.io.threads.max", "32").toInt, + conf.get("spark.core.connection.io.threads.keepalive", "60").toInt, TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable]()) // Use a different, yet smaller, thread pool - infrequently used with very short lived tasks : which should be executed asap private val handleConnectExecutor = new ThreadPoolExecutor( - System.getProperty("spark.core.connection.connect.threads.min","1").toInt, - System.getProperty("spark.core.connection.connect.threads.max","8").toInt, - System.getProperty("spark.core.connection.connect.threads.keepalive","60").toInt, TimeUnit.SECONDS, + conf.get("spark.core.connection.connect.threads.min", "1").toInt, + conf.get("spark.core.connection.connect.threads.max", "8").toInt, + conf.get("spark.core.connection.connect.threads.keepalive", "60").toInt, TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable]()) private val serverChannel = ServerSocketChannel.open() @@ -594,7 +594,7 @@ private[spark] class ConnectionManager(port: Int) extends Logging { private[spark] object ConnectionManager { def main(args: Array[String]) { - val manager = new ConnectionManager(9999) + val manager = new ConnectionManager(9999, new SparkConf) manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { println("Received [" + msg + "] from [" + id + "]") None diff --git a/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala b/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala index 781715108b..1c9d6030d6 100644 --- a/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala +++ b/core/src/main/scala/org/apache/spark/network/ReceiverTest.scala @@ -19,19 +19,19 @@ package org.apache.spark.network import java.nio.ByteBuffer import java.net.InetAddress +import org.apache.spark.SparkConf private[spark] object ReceiverTest { - def main(args: Array[String]) { - val manager = new ConnectionManager(9999) + val manager = new ConnectionManager(9999, new SparkConf) println("Started connection manager with id = " + manager.id) - - manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { + + manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { /*println("Received [" + msg + "] from [" + id + "] at " + System.currentTimeMillis)*/ - val buffer = ByteBuffer.wrap("response".getBytes()) + val buffer = ByteBuffer.wrap("response".getBytes) Some(Message.createBufferMessage(buffer, msg.id)) }) - Thread.currentThread.join() + Thread.currentThread.join() } } diff --git a/core/src/main/scala/org/apache/spark/network/SenderTest.scala b/core/src/main/scala/org/apache/spark/network/SenderTest.scala index 777574980f..dcbd183c88 100644 --- a/core/src/main/scala/org/apache/spark/network/SenderTest.scala +++ b/core/src/main/scala/org/apache/spark/network/SenderTest.scala @@ -19,29 +19,29 @@ package org.apache.spark.network import java.nio.ByteBuffer import java.net.InetAddress +import org.apache.spark.SparkConf private[spark] object SenderTest { - def main(args: Array[String]) { - + if (args.length < 2) { println("Usage: SenderTest <target host> <target port>") System.exit(1) } - + val targetHost = args(0) val targetPort = args(1).toInt val targetConnectionManagerId = new ConnectionManagerId(targetHost, targetPort) - val manager = new ConnectionManager(0) + val manager = new ConnectionManager(0, new SparkConf) println("Started connection manager with id = " + manager.id) - manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { + manager.onReceiveMessage((msg: Message, id: ConnectionManagerId) => { println("Received [" + msg + "] from [" + id + "]") None }) - - val size = 100 * 1024 * 1024 + + val size = 100 * 1024 * 1024 val buffer = ByteBuffer.allocate(size).put(Array.tabulate[Byte](size)(x => x.toByte)) buffer.flip @@ -50,7 +50,7 @@ private[spark] object SenderTest { val count = 100 (0 until count).foreach(i => { val dataMessage = Message.createBufferMessage(buffer.duplicate) - val startTime = System.currentTimeMillis + val startTime = System.currentTimeMillis /*println("Started timer at " + startTime)*/ val responseStr = manager.sendMessageReliablySync(targetConnectionManagerId, dataMessage) match { case Some(response) => diff --git a/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala b/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala index b1e1576dad..b729eb11c5 100644 --- a/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/ShuffleCopier.scala @@ -23,20 +23,20 @@ import io.netty.buffer.ByteBuf import io.netty.channel.ChannelHandlerContext import io.netty.util.CharsetUtil -import org.apache.spark.Logging +import org.apache.spark.{SparkContext, SparkConf, Logging} import org.apache.spark.network.ConnectionManagerId import scala.collection.JavaConverters._ import org.apache.spark.storage.BlockId -private[spark] class ShuffleCopier extends Logging { +private[spark] class ShuffleCopier(conf: SparkConf) extends Logging { def getBlock(host: String, port: Int, blockId: BlockId, resultCollectCallback: (BlockId, Long, ByteBuf) => Unit) { val handler = new ShuffleCopier.ShuffleClientHandler(resultCollectCallback) - val connectTimeout = System.getProperty("spark.shuffle.netty.connect.timeout", "60000").toInt + val connectTimeout = conf.get("spark.shuffle.netty.connect.timeout", "60000").toInt val fc = new FileClient(handler, connectTimeout) try { @@ -104,10 +104,10 @@ private[spark] object ShuffleCopier extends Logging { val threads = if (args.length > 3) args(3).toInt else 10 val copiers = Executors.newFixedThreadPool(80) - val tasks = (for (i <- Range(0, threads)) yield { + val tasks = (for (i <- Range(0, threads)) yield { Executors.callable(new Runnable() { def run() { - val copier = new ShuffleCopier() + val copier = new ShuffleCopier(new SparkConf) copier.getBlock(host, port, blockId, echoResultCollectCallBack) } }) diff --git a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala index a712ef1c27..6d4f46125f 100644 --- a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala @@ -18,12 +18,12 @@ package org.apache.spark.rdd import java.io.IOException - import scala.reflect.ClassTag - -import org.apache.hadoop.fs.Path import org.apache.spark._ +import org.apache.spark.broadcast.Broadcast import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.Path private[spark] class CheckpointRDDPartition(val index: Int) extends Partition {} @@ -34,6 +34,8 @@ private[spark] class CheckpointRDD[T: ClassTag](sc: SparkContext, val checkpointPath: String) extends RDD[T](sc, Nil) { + val broadcastedConf = sc.broadcast(new SerializableWritable(sc.hadoopConfiguration)) + @transient val fs = new Path(checkpointPath).getFileSystem(sc.hadoopConfiguration) override def getPartitions: Array[Partition] = { @@ -65,7 +67,7 @@ class CheckpointRDD[T: ClassTag](sc: SparkContext, val checkpointPath: String) override def compute(split: Partition, context: TaskContext): Iterator[T] = { val file = new Path(checkpointPath, CheckpointRDD.splitIdToFile(split.index)) - CheckpointRDD.readFromFile(file, context) + CheckpointRDD.readFromFile(file, broadcastedConf, context) } override def checkpoint() { @@ -74,15 +76,18 @@ class CheckpointRDD[T: ClassTag](sc: SparkContext, val checkpointPath: String) } private[spark] object CheckpointRDD extends Logging { - def splitIdToFile(splitId: Int): String = { "part-%05d".format(splitId) } - def writeToFile[T](path: String, blockSize: Int = -1)(ctx: TaskContext, iterator: Iterator[T]) { + def writeToFile[T]( + path: String, + broadcastedConf: Broadcast[SerializableWritable[Configuration]], + blockSize: Int = -1 + )(ctx: TaskContext, iterator: Iterator[T]) { val env = SparkEnv.get val outputDir = new Path(path) - val fs = outputDir.getFileSystem(SparkHadoopUtil.get.newConfiguration()) + val fs = outputDir.getFileSystem(broadcastedConf.value.value) val finalOutputName = splitIdToFile(ctx.partitionId) val finalOutputPath = new Path(outputDir, finalOutputName) @@ -92,7 +97,7 @@ private[spark] object CheckpointRDD extends Logging { throw new IOException("Checkpoint failed: temporary path " + tempOutputPath + " already exists") } - val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt + val bufferSize = env.conf.get("spark.buffer.size", "65536").toInt val fileOutputStream = if (blockSize < 0) { fs.create(tempOutputPath, false, bufferSize) @@ -119,10 +124,14 @@ private[spark] object CheckpointRDD extends Logging { } } - def readFromFile[T](path: Path, context: TaskContext): Iterator[T] = { + def readFromFile[T]( + path: Path, + broadcastedConf: Broadcast[SerializableWritable[Configuration]], + context: TaskContext + ): Iterator[T] = { val env = SparkEnv.get - val fs = path.getFileSystem(SparkHadoopUtil.get.newConfiguration()) - val bufferSize = System.getProperty("spark.buffer.size", "65536").toInt + val fs = path.getFileSystem(broadcastedConf.value.value) + val bufferSize = env.conf.get("spark.buffer.size", "65536").toInt val fileInputStream = fs.open(path, bufferSize) val serializer = env.serializer.newInstance() val deserializeStream = serializer.deserializeStream(fileInputStream) @@ -144,8 +153,10 @@ private[spark] object CheckpointRDD extends Logging { 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.get.newConfiguration()) - sc.runJob(rdd, CheckpointRDD.writeToFile(path.toString, 1024) _) + val conf = SparkHadoopUtil.get.newConfiguration() + val fs = path.getFileSystem(conf) + val broadcastedConf = sc.broadcast(new SerializableWritable(conf)) + sc.runJob(rdd, CheckpointRDD.writeToFile(path.toString, broadcastedConf, 1024) _) val cpRDD = new CheckpointRDD[Int](sc, path.toString) assert(cpRDD.partitions.length == rdd.partitions.length, "Number of partitions is not the same") assert(cpRDD.collect.toList == rdd.collect.toList, "Data of partitions not the same") diff --git a/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala index 911a002884..4ba4696fef 100644 --- a/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CoGroupedRDD.scala @@ -114,7 +114,7 @@ class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part: map.changeValue(k, update) } - val ser = SparkEnv.get.serializerManager.get(serializerClass) + val ser = SparkEnv.get.serializerManager.get(serializerClass, SparkEnv.get.conf) for ((dep, depNum) <- split.deps.zipWithIndex) dep match { case NarrowCoGroupSplitDep(rdd, _, itsSplit) => { // Read them from the parent diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index 48168e152e..04a8d05988 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -40,12 +40,15 @@ import org.apache.hadoop.mapreduce.SparkHadoopMapReduceUtil import org.apache.hadoop.mapreduce.{Job => NewAPIHadoopJob} import org.apache.hadoop.mapreduce.{RecordWriter => NewRecordWriter} +import com.clearspring.analytics.stream.cardinality.HyperLogLog + 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 +import org.apache.spark.util.SerializableHyperLogLog /** * Extra functions available on RDDs of (key, value) pairs through an implicit conversion. @@ -208,6 +211,45 @@ class PairRDDFunctions[K: ClassTag, V: ClassTag](self: RDD[(K, V)]) } /** + * Return approximate number of distinct values for each key in this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. Uses the provided + * Partitioner to partition the output RDD. + */ + def countApproxDistinctByKey(relativeSD: Double, partitioner: Partitioner): RDD[(K, Long)] = { + val createHLL = (v: V) => new SerializableHyperLogLog(new HyperLogLog(relativeSD)).add(v) + val mergeValueHLL = (hll: SerializableHyperLogLog, v: V) => hll.add(v) + val mergeHLL = (h1: SerializableHyperLogLog, h2: SerializableHyperLogLog) => h1.merge(h2) + + combineByKey(createHLL, mergeValueHLL, mergeHLL, partitioner).mapValues(_.value.cardinality()) + } + + /** + * Return approximate number of distinct values for each key in this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. HashPartitions the + * output RDD into numPartitions. + * + */ + def countApproxDistinctByKey(relativeSD: Double, numPartitions: Int): RDD[(K, Long)] = { + countApproxDistinctByKey(relativeSD, new HashPartitioner(numPartitions)) + } + + /** + * Return approximate number of distinct values for each key this RDD. + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. The default value of + * relativeSD is 0.05. Hash-partitions the output RDD using the existing partitioner/parallelism + * level. + */ + def countApproxDistinctByKey(relativeSD: Double = 0.05): RDD[(K, Long)] = { + countApproxDistinctByKey(relativeSD, defaultPartitioner(self)) + } + + /** * Merge the values for each key using an associative reduce function. This will also perform * the merging locally on each mapper before sending results to a reducer, similarly to a * "combiner" in MapReduce. Output will be hash-partitioned with numPartitions partitions. diff --git a/core/src/main/scala/org/apache/spark/rdd/PartitionerAwareUnionRDD.scala b/core/src/main/scala/org/apache/spark/rdd/PartitionerAwareUnionRDD.scala new file mode 100644 index 0000000000..4c625d062e --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rdd/PartitionerAwareUnionRDD.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.rdd + +import scala.reflect.ClassTag +import java.io.{ObjectOutputStream, IOException} +import org.apache.spark.{TaskContext, OneToOneDependency, SparkContext, Partition} + + +/** + * Class representing partitions of PartitionerAwareUnionRDD, which maintains the list of corresponding partitions + * of parent RDDs. + */ +private[spark] +class PartitionerAwareUnionRDDPartition( + @transient val rdds: Seq[RDD[_]], + val idx: Int + ) extends Partition { + var parents = rdds.map(_.partitions(idx)).toArray + + override val index = idx + override def hashCode(): Int = idx + + @throws(classOf[IOException]) + private def writeObject(oos: ObjectOutputStream) { + // Update the reference to parent partition at the time of task serialization + parents = rdds.map(_.partitions(index)).toArray + oos.defaultWriteObject() + } +} + +/** + * Class representing an RDD that can take multiple RDDs partitioned by the same partitioner and + * unify them into a single RDD while preserving the partitioner. So m RDDs with p partitions each + * will be unified to a single RDD with p partitions and the same partitioner. The preferred + * location for each partition of the unified RDD will be the most common preferred location + * of the corresponding partitions of the parent RDDs. For example, location of partition 0 + * of the unified RDD will be where most of partition 0 of the parent RDDs are located. + */ +private[spark] +class PartitionerAwareUnionRDD[T: ClassTag]( + sc: SparkContext, + var rdds: Seq[RDD[T]] + ) extends RDD[T](sc, rdds.map(x => new OneToOneDependency(x))) { + require(rdds.length > 0) + require(rdds.flatMap(_.partitioner).toSet.size == 1, + "Parent RDDs have different partitioners: " + rdds.flatMap(_.partitioner)) + + override val partitioner = rdds.head.partitioner + + override def getPartitions: Array[Partition] = { + val numPartitions = partitioner.get.numPartitions + (0 until numPartitions).map(index => { + new PartitionerAwareUnionRDDPartition(rdds, index) + }).toArray + } + + // Get the location where most of the partitions of parent RDDs are located + override def getPreferredLocations(s: Partition): Seq[String] = { + logDebug("Finding preferred location for " + this + ", partition " + s.index) + val parentPartitions = s.asInstanceOf[PartitionerAwareUnionRDDPartition].parents + val locations = rdds.zip(parentPartitions).flatMap { + case (rdd, part) => { + val parentLocations = currPrefLocs(rdd, part) + logDebug("Location of " + rdd + " partition " + part.index + " = " + parentLocations) + parentLocations + } + } + val location = if (locations.isEmpty) { + None + } else { + // Find the location that maximum number of parent partitions prefer + Some(locations.groupBy(x => x).maxBy(_._2.length)._1) + } + logDebug("Selected location for " + this + ", partition " + s.index + " = " + location) + location.toSeq + } + + override def compute(s: Partition, context: TaskContext): Iterator[T] = { + val parentPartitions = s.asInstanceOf[PartitionerAwareUnionRDDPartition].parents + rdds.zip(parentPartitions).iterator.flatMap { + case (rdd, p) => rdd.iterator(p, context) + } + } + + override def clearDependencies() { + super.clearDependencies() + rdds = null + } + + // Get the *current* preferred locations from the DAGScheduler (as opposed to the static ones) + private def currPrefLocs(rdd: RDD[_], part: Partition): Seq[String] = { + rdd.context.getPreferredLocs(rdd, part.index).map(tl => tl.host) + } +} diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index ea45566ad1..3f41b66279 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -33,6 +33,7 @@ import org.apache.hadoop.io.Text import org.apache.hadoop.mapred.TextOutputFormat import it.unimi.dsi.fastutil.objects.{Object2LongOpenHashMap => OLMap} +import com.clearspring.analytics.stream.cardinality.HyperLogLog import org.apache.spark.Partitioner._ import org.apache.spark.api.java.JavaRDD @@ -41,7 +42,7 @@ 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.util.{Utils, BoundedPriorityQueue, SerializableHyperLogLog} import org.apache.spark.SparkContext._ import org.apache.spark._ @@ -81,6 +82,7 @@ abstract class RDD[T: ClassTag]( def this(@transient oneParent: RDD[_]) = this(oneParent.context , List(new OneToOneDependency(oneParent))) + private[spark] def conf = sc.conf // ======================================================================= // Methods that should be implemented by subclasses of RDD // ======================================================================= @@ -789,6 +791,19 @@ abstract class RDD[T: ClassTag]( } /** + * Return approximate number of distinct elements in the RDD. + * + * The accuracy of approximation can be controlled through the relative standard deviation + * (relativeSD) parameter, which also controls the amount of memory used. Lower values result in + * more accurate counts but increase the memory footprint and vise versa. The default value of + * relativeSD is 0.05. + */ + def countApproxDistinct(relativeSD: Double = 0.05): Long = { + val zeroCounter = new SerializableHyperLogLog(new HyperLogLog(relativeSD)) + aggregate(zeroCounter)(_.add(_), _.merge(_)).value.cardinality() + } + + /** * Take the first num elements of the RDD. It works by first scanning one partition, and use the * results from that partition to estimate the number of additional partitions needed to satisfy * the limit. @@ -938,7 +953,7 @@ abstract class RDD[T: ClassTag]( private var storageLevel: StorageLevel = StorageLevel.NONE /** Record user function generating this RDD. */ - @transient private[spark] val origin = Utils.formatSparkCallSite + @transient private[spark] val origin = sc.getCallSite private[spark] def elementClassTag: ClassTag[T] = classTag[T] diff --git a/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala index 3b56e45aa9..bc688110f4 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDDCheckpointData.scala @@ -22,7 +22,7 @@ import scala.reflect.ClassTag import org.apache.hadoop.fs.Path import org.apache.hadoop.conf.Configuration -import org.apache.spark.{Partition, SparkException, Logging} +import org.apache.spark.{SerializableWritable, Partition, SparkException, Logging} import org.apache.spark.scheduler.{ResultTask, ShuffleMapTask} /** @@ -40,7 +40,7 @@ private[spark] object CheckpointState extends Enumeration { * manages the post-checkpoint state by providing the updated partitions, iterator and preferred locations * of the checkpointed RDD. */ -private[spark] class RDDCheckpointData[T: ClassTag](rdd: RDD[T]) +private[spark] class RDDCheckpointData[T: ClassTag](@transient rdd: RDD[T]) extends Logging with Serializable { import CheckpointState._ @@ -85,14 +85,21 @@ private[spark] class RDDCheckpointData[T: ClassTag](rdd: RDD[T]) // Create the output path for the checkpoint val path = new Path(rdd.context.checkpointDir.get, "rdd-" + rdd.id) - val fs = path.getFileSystem(new Configuration()) + val fs = path.getFileSystem(rdd.context.hadoopConfiguration) if (!fs.mkdirs(path)) { throw new SparkException("Failed to create checkpoint path " + path) } // Save to file, and reload it as an RDD - rdd.context.runJob(rdd, CheckpointRDD.writeToFile(path.toString) _) + val broadcastedConf = rdd.context.broadcast( + new SerializableWritable(rdd.context.hadoopConfiguration)) + rdd.context.runJob(rdd, CheckpointRDD.writeToFile(path.toString, broadcastedConf) _) val newRDD = new CheckpointRDD[T](rdd.context, path.toString) + if (newRDD.partitions.size != rdd.partitions.size) { + throw new SparkException( + "Checkpoint RDD " + newRDD + "("+ newRDD.partitions.size + ") has different " + + "number of partitions than original RDD " + rdd + "(" + rdd.partitions.size + ")") + } // Change the dependencies and partitions of the RDD RDDCheckpointData.synchronized { @@ -101,8 +108,8 @@ private[spark] class RDDCheckpointData[T: ClassTag](rdd: RDD[T]) rdd.markCheckpointed(newRDD) // Update the RDD's dependencies and partitions cpState = Checkpointed RDDCheckpointData.clearTaskCaches() - logInfo("Done checkpointing RDD " + rdd.id + ", new parent is RDD " + newRDD.id) } + logInfo("Done checkpointing RDD " + rdd.id + " to " + path + ", new parent is RDD " + newRDD.id) } // Get preferred location of a split after checkpointing diff --git a/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala index 3682c84598..0ccb309d0d 100644 --- a/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/ShuffledRDD.scala @@ -59,7 +59,7 @@ class ShuffledRDD[K, V, P <: Product2[K, V] : ClassTag]( 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, - SparkEnv.get.serializerManager.get(serializerClass)) + SparkEnv.get.serializerManager.get(serializerClass, SparkEnv.get.conf)) } override def clearDependencies() { diff --git a/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala index aab30b1bb4..4f90c7d3d6 100644 --- a/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala @@ -93,7 +93,7 @@ private[spark] class SubtractedRDD[K: ClassTag, V: ClassTag, W: ClassTag]( override def compute(p: Partition, context: TaskContext): Iterator[(K, V)] = { val partition = p.asInstanceOf[CoGroupPartition] - val serializer = SparkEnv.get.serializerManager.get(serializerClass) + val serializer = SparkEnv.get.serializerManager.get(serializerClass, SparkEnv.get.conf) val map = new JHashMap[K, ArrayBuffer[V]] def getSeq(k: K): ArrayBuffer[V] = { val seq = map.get(k) diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 7603eb292f..043e01dbfb 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -159,7 +159,8 @@ class DAGScheduler( val activeJobs = new HashSet[ActiveJob] val resultStageToJob = new HashMap[Stage, ActiveJob] - val metadataCleaner = new MetadataCleaner(MetadataCleanerType.DAG_SCHEDULER, this.cleanup) + val metadataCleaner = new MetadataCleaner( + MetadataCleanerType.DAG_SCHEDULER, this.cleanup, env.conf) /** * Starts the event processing actor. The actor has two responsibilities: diff --git a/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala index 1791ee660d..90eb8a747f 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/InputFormatInfo.scala @@ -32,7 +32,7 @@ import scala.collection.JavaConversions._ /** * Parses and holds information about inputFormat (and files) specified as a parameter. */ -class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Class[_], +class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Class[_], val path: String) extends Logging { var mapreduceInputFormat: Boolean = false @@ -40,7 +40,7 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl validate() - override def toString(): String = { + override def toString: String = { "InputFormatInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz + ", path : " + path } @@ -125,7 +125,7 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl } private def findPreferredLocations(): Set[SplitInfo] = { - logDebug("mapreduceInputFormat : " + mapreduceInputFormat + ", mapredInputFormat : " + mapredInputFormat + + logDebug("mapreduceInputFormat : " + mapreduceInputFormat + ", mapredInputFormat : " + mapredInputFormat + ", inputFormatClazz : " + inputFormatClazz) if (mapreduceInputFormat) { return prefLocsFromMapreduceInputFormat() @@ -143,14 +143,14 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl object InputFormatInfo { /** Computes the preferred locations based on input(s) and returned a location to block map. - Typical use of this method for allocation would follow some algo like this - (which is what we currently do in YARN branch) : + Typical use of this method for allocation would follow some algo like this: + a) For each host, count number of splits hosted on that host. b) Decrement the currently allocated containers on that host. c) Compute rack info for each host and update rack -> count map based on (b). d) Allocate nodes based on (c) - e) On the allocation result, ensure that we dont allocate "too many" jobs on a single node - (even if data locality on that is very high) : this is to prevent fragility of job if a single + e) On the allocation result, ensure that we dont allocate "too many" jobs on a single node + (even if data locality on that is very high) : this is to prevent fragility of job if a single (or small set of) hosts go down. go to (a) until required nodes are allocated. diff --git a/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala index 310ec62ca8..28f3ba53b8 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala @@ -32,7 +32,9 @@ private[spark] object ResultTask { // expensive on the master node if it needs to launch thousands of tasks. val serializedInfoCache = new TimeStampedHashMap[Int, Array[Byte]] - val metadataCleaner = new MetadataCleaner(MetadataCleanerType.RESULT_TASK, serializedInfoCache.clearOldValues) + // TODO: This object shouldn't have global variables + val metadataCleaner = new MetadataCleaner( + MetadataCleanerType.RESULT_TASK, serializedInfoCache.clearOldValues, new SparkConf) def serializeInfo(stageId: Int, rdd: RDD[_], func: (TaskContext, Iterator[_]) => _): Array[Byte] = { synchronized { diff --git a/core/src/main/scala/org/apache/spark/scheduler/SchedulableBuilder.scala b/core/src/main/scala/org/apache/spark/scheduler/SchedulableBuilder.scala index 356fe56bf3..3cf995ea74 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SchedulableBuilder.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SchedulableBuilder.scala @@ -20,7 +20,7 @@ package org.apache.spark.scheduler import java.io.{FileInputStream, InputStream} import java.util.{NoSuchElementException, Properties} -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, Logging} import scala.xml.XML @@ -49,10 +49,10 @@ private[spark] class FIFOSchedulableBuilder(val rootPool: Pool) } } -private[spark] class FairSchedulableBuilder(val rootPool: Pool) +private[spark] class FairSchedulableBuilder(val rootPool: Pool, conf: SparkConf) extends SchedulableBuilder with Logging { - val schedulerAllocFile = Option(System.getProperty("spark.scheduler.allocation.file")) + val schedulerAllocFile = conf.getOption("spark.scheduler.allocation.file") val DEFAULT_SCHEDULER_FILE = "fairscheduler.xml" val FAIR_SCHEDULER_PROPERTIES = "spark.scheduler.pool" val DEFAULT_POOL_NAME = "default" diff --git a/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala index 89aa098664..02bdbba825 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala @@ -31,7 +31,4 @@ private[spark] trait SchedulerBackend { def defaultParallelism(): Int def killTask(taskId: Long, executorId: String): Unit = throw new UnsupportedOperationException - - // Memory used by each executor (in megabytes) - protected val executorMemory: Int = SparkContext.executorMemoryRequested } diff --git a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala index 0f2deb4bcb..a37ead5632 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala @@ -37,7 +37,9 @@ private[spark] object ShuffleMapTask { // expensive on the master node if it needs to launch thousands of tasks. val serializedInfoCache = new TimeStampedHashMap[Int, Array[Byte]] - val metadataCleaner = new MetadataCleaner(MetadataCleanerType.SHUFFLE_MAP_TASK, serializedInfoCache.clearOldValues) + // TODO: This object shouldn't have global variables + val metadataCleaner = new MetadataCleaner( + MetadataCleanerType.SHUFFLE_MAP_TASK, serializedInfoCache.clearOldValues, new SparkConf) def serializeInfo(stageId: Int, rdd: RDD[_], dep: ShuffleDependency[_,_]): Array[Byte] = { synchronized { @@ -152,7 +154,7 @@ private[spark] class ShuffleMapTask( try { // Obtain all the block writers for shuffle blocks. - val ser = SparkEnv.get.serializerManager.get(dep.serializerClass) + val ser = SparkEnv.get.serializerManager.get(dep.serializerClass, SparkEnv.get.conf) shuffle = shuffleBlockManager.forMapTask(dep.shuffleId, partitionId, numOutputSplits, ser) // Write the map output to its associated buckets. diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala index 89102720fa..e22b1e53e8 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala @@ -30,7 +30,8 @@ import org.apache.spark.util.Utils */ private[spark] class TaskResultGetter(sparkEnv: SparkEnv, scheduler: TaskSchedulerImpl) extends Logging { - private val THREADS = System.getProperty("spark.resultGetter.threads", "4").toInt + + private val THREADS = sparkEnv.conf.get("spark.resultGetter.threads", "4").toInt private val getTaskResultExecutor = Utils.newDaemonFixedThreadPool( THREADS, "Result resolver thread") diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala index 1b0f82fa24..0c8ed62759 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala @@ -35,7 +35,7 @@ import org.apache.spark.scheduler.SchedulingMode.SchedulingMode * It can also work with a local setup by using a LocalBackend and setting isLocal to true. * It handles common logic, like determining a scheduling order across jobs, waking up to launch * speculative tasks, etc. - * + * * Clients should first call initialize() and start(), then submit task sets through the * runTasks method. * @@ -47,15 +47,19 @@ import org.apache.spark.scheduler.SchedulingMode.SchedulingMode */ private[spark] class TaskSchedulerImpl( val sc: SparkContext, - val maxTaskFailures : Int = System.getProperty("spark.task.maxFailures", "4").toInt, + val maxTaskFailures: Int, isLocal: Boolean = false) - extends TaskScheduler with Logging { + extends TaskScheduler with Logging +{ + def this(sc: SparkContext) = this(sc, sc.conf.get("spark.task.maxFailures", "4").toInt) + + val conf = sc.conf // How often to check for speculative tasks - val SPECULATION_INTERVAL = System.getProperty("spark.speculation.interval", "100").toLong + val SPECULATION_INTERVAL = conf.get("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 STARVATION_TIMEOUT = conf.get("spark.starvation.timeout", "15000").toLong // TaskSetManagers are not thread safe, so any access to one should be synchronized // on this class. @@ -92,7 +96,7 @@ private[spark] class TaskSchedulerImpl( var rootPool: Pool = null // default scheduler is FIFO val schedulingMode: SchedulingMode = SchedulingMode.withName( - System.getProperty("spark.scheduler.mode", "FIFO")) + conf.get("spark.scheduler.mode", "FIFO")) // This is a var so that we can reset it for testing purposes. private[spark] var taskResultGetter = new TaskResultGetter(sc.env, this) @@ -110,7 +114,7 @@ private[spark] class TaskSchedulerImpl( case SchedulingMode.FIFO => new FIFOSchedulableBuilder(rootPool) case SchedulingMode.FAIR => - new FairSchedulableBuilder(rootPool) + new FairSchedulableBuilder(rootPool, conf) } } schedulableBuilder.buildPools() @@ -121,7 +125,7 @@ private[spark] class TaskSchedulerImpl( override def start() { backend.start() - if (!isLocal && System.getProperty("spark.speculation", "false").toBoolean) { + if (!isLocal && conf.get("spark.speculation", "false").toBoolean) { logInfo("Starting speculative execution thread") import sc.env.actorSystem.dispatcher sc.env.actorSystem.scheduler.schedule(SPECULATION_INTERVAL milliseconds, @@ -281,7 +285,8 @@ private[spark] class TaskSchedulerImpl( } } case None => - logInfo("Ignoring update from TID " + tid + " because its task set is gone") + logInfo("Ignoring update with state %s from TID %s because its task set is gone" + .format(state, tid)) } } catch { case e: Exception => logError("Exception in statusUpdate", e) @@ -324,7 +329,7 @@ private[spark] class TaskSchedulerImpl( // Have each task set throw a SparkException with the error for ((taskSetId, manager) <- activeTaskSets) { try { - manager.error(message) + manager.abort(message) } catch { case e: Exception => logError("Exception in error callback", e) } diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala index 7929051791..6dd1469d8f 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala @@ -54,12 +54,14 @@ private[spark] class TaskSetManager( clock: Clock = SystemClock) extends Schedulable with Logging { + val conf = sched.sc.conf + // CPUs to request per task - val CPUS_PER_TASK = System.getProperty("spark.task.cpus", "1").toInt + val CPUS_PER_TASK = conf.get("spark.task.cpus", "1").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 + val SPECULATION_QUANTILE = conf.get("spark.speculation.quantile", "0.75").toDouble + val SPECULATION_MULTIPLIER = conf.get("spark.speculation.multiplier", "1.5").toDouble // Serializer for closures and tasks. val env = SparkEnv.get @@ -114,7 +116,7 @@ private[spark] class TaskSetManager( // How frequently to reprint duplicate exceptions in full, in milliseconds val EXCEPTION_PRINT_INTERVAL = - System.getProperty("spark.logging.exceptionPrintInterval", "10000").toLong + conf.get("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 @@ -546,11 +548,6 @@ private[spark] class TaskSetManager( } } - def error(message: String) { - // Save the error message - abort("Error: " + message) - } - def abort(message: String) { // TODO: Kill running tasks if we were not terminated due to a Mesos error sched.dagScheduler.taskSetFailed(taskSet, message) @@ -676,14 +673,14 @@ private[spark] class TaskSetManager( } private def getLocalityWait(level: TaskLocality.TaskLocality): Long = { - val defaultWait = System.getProperty("spark.locality.wait", "3000") + val defaultWait = conf.get("spark.locality.wait", "3000") level match { case TaskLocality.PROCESS_LOCAL => - System.getProperty("spark.locality.wait.process", defaultWait).toLong + conf.get("spark.locality.wait.process", defaultWait).toLong case TaskLocality.NODE_LOCAL => - System.getProperty("spark.locality.wait.node", defaultWait).toLong + conf.get("spark.locality.wait.node", defaultWait).toLong case TaskLocality.RACK_LOCAL => - System.getProperty("spark.locality.wait.rack", defaultWait).toLong + conf.get("spark.locality.wait.rack", defaultWait).toLong case TaskLocality.ANY => 0L } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala index 5c534a6f43..2f5bcafe40 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala @@ -48,8 +48,8 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A { // Use an atomic variable to track total number of cores in the cluster for simplicity and speed var totalCoreCount = new AtomicInteger(0) - - private val timeout = AkkaUtils.askTimeout + val conf = scheduler.sc.conf + private val timeout = AkkaUtils.askTimeout(conf) class DriverActor(sparkProperties: Seq[(String, String)]) extends Actor { private val executorActor = new HashMap[String, ActorRef] @@ -63,7 +63,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent]) // Periodically revive offers to allow delay scheduling to work - val reviveInterval = System.getProperty("spark.scheduler.revive.interval", "1000").toLong + val reviveInterval = conf.get("spark.scheduler.revive.interval", "1000").toLong import context.dispatcher context.system.scheduler.schedule(0.millis, reviveInterval.millis, self, ReviveOffers) } @@ -119,7 +119,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A removeExecutor(executorId, reason) sender ! true - case DisassociatedEvent(_, address, _) => + case DisassociatedEvent(_, address, _) => addressToExecutorId.get(address).foreach(removeExecutor(_, "remote Akka client disassociated")) } @@ -164,14 +164,12 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A override def start() { val properties = new ArrayBuffer[(String, String)] - val iterator = System.getProperties.entrySet.iterator - while (iterator.hasNext) { - val entry = iterator.next - val (key, value) = (entry.getKey.toString, entry.getValue.toString) + for ((key, value) <- scheduler.sc.conf.getAll) { if (key.startsWith("spark.") && !key.equals("spark.hostPort")) { properties += ((key, value)) } } + //TODO (prashant) send conf instead of properties driverActor = actorSystem.actorOf( Props(new DriverActor(properties)), name = CoarseGrainedSchedulerBackend.ACTOR_NAME) } @@ -210,8 +208,10 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, actorSystem: A driverActor ! KillTask(taskId, executorId) } - override def defaultParallelism() = Option(System.getProperty("spark.default.parallelism")) - .map(_.toInt).getOrElse(math.max(totalCoreCount.get(), 2)) + override def defaultParallelism(): Int = { + conf.getOption("spark.default.parallelism").map(_.toInt).getOrElse( + math.max(totalCoreCount.get(), 2)) + } // Called by subclasses when notified of a lost worker def removeExecutor(executorId: String, reason: String) { diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SimrSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SimrSchedulerBackend.scala index ec3e68e970..b44d1e43c8 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/SimrSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SimrSchedulerBackend.scala @@ -33,13 +33,13 @@ private[spark] class SimrSchedulerBackend( val tmpPath = new Path(driverFilePath + "_tmp") val filePath = new Path(driverFilePath) - val maxCores = System.getProperty("spark.simr.executor.cores", "1").toInt + val maxCores = conf.get("spark.simr.executor.cores", "1").toInt override def start() { super.start() val driverUrl = "akka.tcp://spark@%s:%s/user/%s".format( - System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"), + sc.conf.get("spark.driver.host"), sc.conf.get("spark.driver.port"), CoarseGrainedSchedulerBackend.ACTOR_NAME) val conf = new Configuration() diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala index 404ce7a452..9858717d13 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala @@ -38,23 +38,23 @@ private[spark] class SparkDeploySchedulerBackend( var stopping = false var shutdownCallback : (SparkDeploySchedulerBackend) => Unit = _ - val maxCores = System.getProperty("spark.cores.max", Int.MaxValue.toString).toInt + val maxCores = conf.get("spark.cores.max", Int.MaxValue.toString).toInt override def start() { super.start() // The endpoint for executors to talk to us val driverUrl = "akka.tcp://spark@%s:%s/user/%s".format( - System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"), + conf.get("spark.driver.host"), conf.get("spark.driver.port"), CoarseGrainedSchedulerBackend.ACTOR_NAME) val args = Seq(driverUrl, "{{EXECUTOR_ID}}", "{{HOSTNAME}}", "{{CORES}}") val command = Command( "org.apache.spark.executor.CoarseGrainedExecutorBackend", args, sc.executorEnvs) val sparkHome = sc.getSparkHome().getOrElse(null) - val appDesc = new ApplicationDescription(appName, maxCores, executorMemory, command, sparkHome, + val appDesc = new ApplicationDescription(appName, maxCores, sc.executorMemory, command, sparkHome, "http://" + sc.ui.appUIAddress) - client = new Client(sc.env.actorSystem, masters, appDesc, this) + client = new Client(sc.env.actorSystem, masters, appDesc, this, conf) client.start() } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala index 39573fc8c9..d46fceba89 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala @@ -62,7 +62,7 @@ private[spark] class CoarseMesosSchedulerBackend( var driver: SchedulerDriver = null // Maximum number of cores to acquire (TODO: we'll need more flexible controls here) - val maxCores = System.getProperty("spark.cores.max", Int.MaxValue.toString).toInt + val maxCores = conf.get("spark.cores.max", Int.MaxValue.toString).toInt // Cores we have acquired with each Mesos task ID val coresByTaskId = new HashMap[Int, Int] @@ -77,7 +77,7 @@ private[spark] class CoarseMesosSchedulerBackend( "Spark home is not set; set it through the spark.home system " + "property, the SPARK_HOME environment variable or the SparkContext constructor")) - val extraCoresPerSlave = System.getProperty("spark.mesos.extra.cores", "0").toInt + val extraCoresPerSlave = conf.get("spark.mesos.extra.cores", "0").toInt var nextMesosTaskId = 0 @@ -122,12 +122,12 @@ private[spark] class CoarseMesosSchedulerBackend( val command = CommandInfo.newBuilder() .setEnvironment(environment) val driverUrl = "akka.tcp://spark@%s:%s/user/%s".format( - System.getProperty("spark.driver.host"), - System.getProperty("spark.driver.port"), + conf.get("spark.driver.host"), + conf.get("spark.driver.port"), CoarseGrainedSchedulerBackend.ACTOR_NAME) - val uri = System.getProperty("spark.executor.uri") + val uri = conf.get("spark.executor.uri", null) if (uri == null) { - val runScript = new File(sparkHome, "spark-class").getCanonicalPath + val runScript = new File(sparkHome, "./bin/spark-class").getCanonicalPath command.setValue( "\"%s\" org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d".format( runScript, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores)) @@ -136,7 +136,7 @@ private[spark] class CoarseMesosSchedulerBackend( // glob the directory "correctly". val basename = uri.split('/').last.split('.').head command.setValue( - "cd %s*; ./spark-class org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d" + "cd %s*; ./bin/spark-class org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d" .format(basename, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores)) command.addUris(CommandInfo.URI.newBuilder().setValue(uri)) } @@ -177,7 +177,7 @@ private[spark] class CoarseMesosSchedulerBackend( val slaveId = offer.getSlaveId.toString val mem = getResource(offer.getResourcesList, "mem") val cpus = getResource(offer.getResourcesList, "cpus").toInt - if (totalCoresAcquired < maxCores && mem >= executorMemory && cpus >= 1 && + if (totalCoresAcquired < maxCores && mem >= sc.executorMemory && cpus >= 1 && failuresBySlaveId.getOrElse(slaveId, 0) < MAX_SLAVE_FAILURES && !slaveIdsWithExecutors.contains(slaveId)) { // Launch an executor on the slave @@ -193,7 +193,7 @@ private[spark] class CoarseMesosSchedulerBackend( .setCommand(createCommand(offer, cpusToUse + extraCoresPerSlave)) .setName("Task " + taskId) .addResources(createResource("cpus", cpusToUse)) - .addResources(createResource("mem", executorMemory)) + .addResources(createResource("mem", sc.executorMemory)) .build() d.launchTasks(offer.getId, Collections.singletonList(task), filters) } else { diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala index 6aa788c460..ae8d527352 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala @@ -100,20 +100,20 @@ private[spark] class MesosSchedulerBackend( } val command = CommandInfo.newBuilder() .setEnvironment(environment) - val uri = System.getProperty("spark.executor.uri") + val uri = sc.conf.get("spark.executor.uri", null) if (uri == null) { - command.setValue(new File(sparkHome, "spark-executor").getCanonicalPath) + command.setValue(new File(sparkHome, "/sbin/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.setValue("cd %s*; ./sbin/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()) + .setScalar(Value.Scalar.newBuilder().setValue(sc.executorMemory).build()) .build() ExecutorInfo.newBuilder() .setExecutorId(ExecutorID.newBuilder().setValue(execId).build()) @@ -198,7 +198,7 @@ private[spark] class MesosSchedulerBackend( def enoughMemory(o: Offer) = { val mem = getResource(o.getResourcesList, "mem") val slaveId = o.getSlaveId.getValue - mem >= executorMemory || slaveIdsWithExecutors.contains(slaveId) + mem >= sc.executorMemory || slaveIdsWithExecutors.contains(slaveId) } for ((offer, index) <- offers.zipWithIndex if enoughMemory(offer)) { @@ -340,5 +340,5 @@ private[spark] class MesosSchedulerBackend( } // TODO: query Mesos for number of cores - override def defaultParallelism() = System.getProperty("spark.default.parallelism", "8").toInt + override def defaultParallelism() = sc.conf.get("spark.default.parallelism", "8").toInt } diff --git a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala index 4edc6a0d3f..897d47a9ad 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala @@ -47,7 +47,8 @@ private[spark] class LocalActor( private val localExecutorId = "localhost" private val localExecutorHostname = "localhost" - val executor = new Executor(localExecutorId, localExecutorHostname, Seq.empty, isLocal = true) + val executor = new Executor( + localExecutorId, localExecutorHostname, scheduler.conf.getAll, isLocal = true) def receive = { case ReviveOffers => diff --git a/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala index 4de81617b1..5d3d43623d 100644 --- a/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/JavaSerializer.scala @@ -21,6 +21,7 @@ import java.io._ import java.nio.ByteBuffer import org.apache.spark.util.ByteBufferInputStream +import org.apache.spark.SparkConf private[spark] class JavaSerializationStream(out: OutputStream) extends SerializationStream { val objOut = new ObjectOutputStream(out) @@ -77,6 +78,6 @@ private[spark] class JavaSerializerInstance extends SerializerInstance { /** * A Spark serializer that uses Java's built-in serialization. */ -class JavaSerializer extends Serializer { +class JavaSerializer(conf: SparkConf) extends Serializer { def newInstance(): SerializerInstance = new JavaSerializerInstance } diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala index e748c2275d..a24a3b04b8 100644 --- a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala @@ -25,18 +25,18 @@ import com.esotericsoftware.kryo.{KryoException, Kryo} import com.esotericsoftware.kryo.io.{Input => KryoInput, Output => KryoOutput} import com.twitter.chill.{EmptyScalaKryoInstantiator, AllScalaRegistrar} -import org.apache.spark.{SerializableWritable, Logging} +import org.apache.spark._ import org.apache.spark.broadcast.HttpBroadcast import org.apache.spark.scheduler.MapStatus import org.apache.spark.storage._ +import org.apache.spark.storage.{GetBlock, GotBlock, PutBlock} /** * A Spark serializer that uses the [[https://code.google.com/p/kryo/ Kryo serialization library]]. */ -class KryoSerializer extends org.apache.spark.serializer.Serializer with Logging { - +class KryoSerializer(conf: SparkConf) extends org.apache.spark.serializer.Serializer with Logging { private val bufferSize = { - System.getProperty("spark.kryoserializer.buffer.mb", "2").toInt * 1024 * 1024 + conf.get("spark.kryoserializer.buffer.mb", "2").toInt * 1024 * 1024 } def newKryoOutput() = new KryoOutput(bufferSize) @@ -48,7 +48,7 @@ class KryoSerializer extends org.apache.spark.serializer.Serializer with Logging // Allow disabling Kryo reference tracking if user knows their object graphs don't have loops. // Do this before we invoke the user registrator so the user registrator can override this. - kryo.setReferences(System.getProperty("spark.kryo.referenceTracking", "true").toBoolean) + kryo.setReferences(conf.get("spark.kryo.referenceTracking", "true").toBoolean) for (cls <- KryoSerializer.toRegister) kryo.register(cls) @@ -58,13 +58,13 @@ class KryoSerializer extends org.apache.spark.serializer.Serializer with Logging // Allow the user to register their own classes by setting spark.kryo.registrator try { - Option(System.getProperty("spark.kryo.registrator")).foreach { regCls => + for (regCls <- conf.getOption("spark.kryo.registrator")) { 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") + case e: Exception => logError("Failed to run spark.kryo.registrator", e) } // Register Chill's classes; we do this after our ranges and the user's own classes to let diff --git a/core/src/main/scala/org/apache/spark/serializer/Serializer.scala b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala index 160cca4d6c..9a5e3cb77e 100644 --- a/core/src/main/scala/org/apache/spark/serializer/Serializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala @@ -29,6 +29,9 @@ import org.apache.spark.util.{NextIterator, ByteBufferInputStream} * A serializer. Because some serialization libraries are not thread safe, this class is used to * 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. + * + * Implementations of this trait should have a zero-arg constructor or a constructor that accepts a + * [[org.apache.spark.SparkConf]] as parameter. If both constructors are defined, the latter takes precedence. */ trait Serializer { def newInstance(): SerializerInstance diff --git a/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala b/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala index 2955986fec..36a37af4f8 100644 --- a/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala +++ b/core/src/main/scala/org/apache/spark/serializer/SerializerManager.scala @@ -18,6 +18,7 @@ package org.apache.spark.serializer import java.util.concurrent.ConcurrentHashMap +import org.apache.spark.SparkConf /** @@ -26,18 +27,19 @@ import java.util.concurrent.ConcurrentHashMap * creating a new one. */ private[spark] class SerializerManager { + // TODO: Consider moving this into SparkConf itself to remove the global singleton. private val serializers = new ConcurrentHashMap[String, Serializer] private var _default: Serializer = _ def default = _default - def setDefault(clsName: String): Serializer = { - _default = get(clsName) + def setDefault(clsName: String, conf: SparkConf): Serializer = { + _default = get(clsName, conf) _default } - def get(clsName: String): Serializer = { + def get(clsName: String, conf: SparkConf): Serializer = { if (clsName == null) { default } else { @@ -51,8 +53,19 @@ private[spark] class SerializerManager { serializer = serializers.get(clsName) if (serializer == null) { val clsLoader = Thread.currentThread.getContextClassLoader - serializer = - Class.forName(clsName, true, clsLoader).newInstance().asInstanceOf[Serializer] + val cls = Class.forName(clsName, true, clsLoader) + + // First try with the constructor that takes SparkConf. If we can't find one, + // use a no-arg constructor instead. + try { + val constructor = cls.getConstructor(classOf[SparkConf]) + serializer = constructor.newInstance(conf).asInstanceOf[Serializer] + } catch { + case _: NoSuchMethodException => + val constructor = cls.getConstructor() + serializer = constructor.newInstance().asInstanceOf[Serializer] + } + serializers.put(clsName, serializer) } serializer diff --git a/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala b/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala index e51c5b30a3..47478631a1 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockFetcherIterator.scala @@ -312,7 +312,7 @@ object BlockFetcherIterator { logDebug("Sending request for %d blocks (%s) from %s".format( req.blocks.size, Utils.bytesToString(req.size), req.address.host)) val cmId = new ConnectionManagerId(req.address.host, req.address.nettyPort) - val cpier = new ShuffleCopier + val cpier = new ShuffleCopier(blockManager.conf) cpier.getBlocks(cmId, req.blocks, putResult) logDebug("Sent request for remote blocks " + req.blocks + " from " + req.address.host ) } @@ -327,7 +327,7 @@ object BlockFetcherIterator { fetchRequestsSync.put(request) } - copiers = startCopiers(System.getProperty("spark.shuffle.copier.threads", "6").toInt) + copiers = startCopiers(conf.get("spark.shuffle.copier.threads", "6").toInt) logInfo("Started " + fetchRequestsSync.size + " remote gets in " + Utils.getUsedTimeMs(startTime)) diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index 19a025a329..6d2cda97b0 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala @@ -30,7 +30,7 @@ import scala.concurrent.duration._ import it.unimi.dsi.fastutil.io.{FastBufferedOutputStream, FastByteArrayOutputStream} -import org.apache.spark.{Logging, SparkEnv, SparkException} +import org.apache.spark.{SparkConf, Logging, SparkEnv, SparkException} import org.apache.spark.io.CompressionCodec import org.apache.spark.network._ import org.apache.spark.serializer.Serializer @@ -43,12 +43,13 @@ private[spark] class BlockManager( actorSystem: ActorSystem, val master: BlockManagerMaster, val defaultSerializer: Serializer, - maxMemory: Long) + maxMemory: Long, + val conf: SparkConf) extends Logging { val shuffleBlockManager = new ShuffleBlockManager(this) val diskBlockManager = new DiskBlockManager(shuffleBlockManager, - System.getProperty("spark.local.dir", System.getProperty("java.io.tmpdir"))) + conf.get("spark.local.dir", System.getProperty("java.io.tmpdir"))) private val blockInfo = new TimeStampedHashMap[BlockId, BlockInfo] @@ -57,12 +58,12 @@ private[spark] class BlockManager( // If we use Netty for shuffle, start a new Netty-based shuffle sender service. private val nettyPort: Int = { - val useNetty = System.getProperty("spark.shuffle.use.netty", "false").toBoolean - val nettyPortConfig = System.getProperty("spark.shuffle.sender.port", "0").toInt + val useNetty = conf.get("spark.shuffle.use.netty", "false").toBoolean + val nettyPortConfig = conf.get("spark.shuffle.sender.port", "0").toInt if (useNetty) diskBlockManager.startShuffleBlockSender(nettyPortConfig) else 0 } - val connectionManager = new ConnectionManager(0) + val connectionManager = new ConnectionManager(0, conf) implicit val futureExecContext = connectionManager.futureExecContext val blockManagerId = BlockManagerId( @@ -71,18 +72,18 @@ private[spark] class BlockManager( // Max megabytes of data to keep in flight per reducer (to avoid over-allocating memory // for receiving shuffle outputs) val maxBytesInFlight = - System.getProperty("spark.reducer.maxMbInFlight", "48").toLong * 1024 * 1024 + conf.get("spark.reducer.maxMbInFlight", "48").toLong * 1024 * 1024 // Whether to compress broadcast variables that are stored - val compressBroadcast = System.getProperty("spark.broadcast.compress", "true").toBoolean + val compressBroadcast = conf.get("spark.broadcast.compress", "true").toBoolean // Whether to compress shuffle output that are stored - val compressShuffle = System.getProperty("spark.shuffle.compress", "true").toBoolean + val compressShuffle = conf.get("spark.shuffle.compress", "true").toBoolean // Whether to compress RDD partitions that are stored serialized - val compressRdds = System.getProperty("spark.rdd.compress", "false").toBoolean + val compressRdds = conf.get("spark.rdd.compress", "false").toBoolean - val heartBeatFrequency = BlockManager.getHeartBeatFrequencyFromSystemProperties + val heartBeatFrequency = BlockManager.getHeartBeatFrequency(conf) - val hostPort = Utils.localHostPort() + val hostPort = Utils.localHostPort(conf) val slaveActor = actorSystem.actorOf(Props(new BlockManagerSlaveActor(this)), name = "BlockManagerActor" + BlockManager.ID_GENERATOR.next) @@ -100,8 +101,11 @@ private[spark] class BlockManager( var heartBeatTask: Cancellable = null - private val metadataCleaner = new MetadataCleaner(MetadataCleanerType.BLOCK_MANAGER, this.dropOldNonBroadcastBlocks) - private val broadcastCleaner = new MetadataCleaner(MetadataCleanerType.BROADCAST_VARS, this.dropOldBroadcastBlocks) + private val metadataCleaner = new MetadataCleaner( + MetadataCleanerType.BLOCK_MANAGER, this.dropOldNonBroadcastBlocks, conf) + private val broadcastCleaner = new MetadataCleaner( + MetadataCleanerType.BROADCAST_VARS, this.dropOldBroadcastBlocks, conf) + initialize() // The compression codec to use. Note that the "lazy" val is necessary because we want to delay @@ -109,14 +113,14 @@ private[spark] class BlockManager( // 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() + private lazy val compressionCodec: CompressionCodec = CompressionCodec.createCodec(conf) /** * Construct a BlockManager with a memory limit set based on system properties. */ def this(execId: String, actorSystem: ActorSystem, master: BlockManagerMaster, - serializer: Serializer) = { - this(execId, actorSystem, master, serializer, BlockManager.getMaxMemoryFromSystemProperties) + serializer: Serializer, conf: SparkConf) = { + this(execId, actorSystem, master, serializer, BlockManager.getMaxMemory(conf), conf) } /** @@ -126,7 +130,7 @@ private[spark] class BlockManager( private def initialize() { master.registerBlockManager(blockManagerId, maxMemory, slaveActor) BlockManagerWorker.startBlockManagerWorker(this) - if (!BlockManager.getDisableHeartBeatsForTesting) { + if (!BlockManager.getDisableHeartBeatsForTesting(conf)) { heartBeatTask = actorSystem.scheduler.schedule(0.seconds, heartBeatFrequency.milliseconds) { heartBeat() } @@ -439,7 +443,7 @@ private[spark] class BlockManager( : BlockFetcherIterator = { val iter = - if (System.getProperty("spark.shuffle.use.netty", "false").toBoolean) { + if (conf.get("spark.shuffle.use.netty", "false").toBoolean) { new BlockFetcherIterator.NettyBlockFetcherIterator(this, blocksByAddress, serializer) } else { new BlockFetcherIterator.BasicBlockFetcherIterator(this, blocksByAddress, serializer) @@ -465,7 +469,8 @@ private[spark] class BlockManager( def getDiskWriter(blockId: BlockId, file: File, serializer: Serializer, bufferSize: Int) : BlockObjectWriter = { val compressStream: OutputStream => OutputStream = wrapForCompression(blockId, _) - new DiskBlockObjectWriter(blockId, file, serializer, bufferSize, compressStream) + val syncWrites = conf.get("spark.shuffle.sync", "false").toBoolean + new DiskBlockObjectWriter(blockId, file, serializer, bufferSize, compressStream, syncWrites) } /** @@ -856,19 +861,18 @@ private[spark] class BlockManager( private[spark] object BlockManager extends Logging { - val ID_GENERATOR = new IdGenerator - def getMaxMemoryFromSystemProperties: Long = { - val memoryFraction = System.getProperty("spark.storage.memoryFraction", "0.66").toDouble + def getMaxMemory(conf: SparkConf): Long = { + val memoryFraction = conf.get("spark.storage.memoryFraction", "0.66").toDouble (Runtime.getRuntime.maxMemory * memoryFraction).toLong } - def getHeartBeatFrequencyFromSystemProperties: Long = - System.getProperty("spark.storage.blockManagerTimeoutIntervalMs", "60000").toLong / 4 + def getHeartBeatFrequency(conf: SparkConf): Long = + conf.get("spark.storage.blockManagerTimeoutIntervalMs", "60000").toLong / 4 - def getDisableHeartBeatsForTesting: Boolean = - System.getProperty("spark.test.disableBlockManagerHeartBeat", "false").toBoolean + def getDisableHeartBeatsForTesting(conf: SparkConf): Boolean = + conf.get("spark.test.disableBlockManagerHeartBeat", "false").toBoolean /** * Attempt to clean up a ByteBuffer if it is memory-mapped. This uses an *unsafe* Sun API that diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala index e1d68ef592..b5afe8cd23 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala @@ -23,19 +23,20 @@ import scala.concurrent.ExecutionContext.Implicits.global import akka.actor._ import akka.pattern.ask -import org.apache.spark.{Logging, SparkException} +import org.apache.spark.{SparkConf, Logging, SparkException} import org.apache.spark.storage.BlockManagerMessages._ import org.apache.spark.util.AkkaUtils private[spark] -class BlockManagerMaster(var driverActor : Either[ActorRef, ActorSelection]) extends Logging { +class BlockManagerMaster(var driverActor : Either[ActorRef, ActorSelection], + conf: SparkConf) extends Logging { - val AKKA_RETRY_ATTEMPTS: Int = System.getProperty("spark.akka.num.retries", "3").toInt - val AKKA_RETRY_INTERVAL_MS: Int = System.getProperty("spark.akka.retry.wait", "3000").toInt + val AKKA_RETRY_ATTEMPTS: Int = conf.get("spark.akka.num.retries", "3").toInt + val AKKA_RETRY_INTERVAL_MS: Int = conf.get("spark.akka.retry.wait", "3000").toInt val DRIVER_AKKA_ACTOR_NAME = "BlockManagerMaster" - val timeout = AkkaUtils.askTimeout + val timeout = AkkaUtils.askTimeout(conf) /** Remove a dead executor from the driver actor. This is only called on the driver side. */ def removeExecutor(execId: String) { diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala index 21022e1cfb..58452d9657 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala @@ -27,7 +27,7 @@ import scala.concurrent.duration._ import akka.actor.{Actor, ActorRef, Cancellable} import akka.pattern.ask -import org.apache.spark.{Logging, SparkException} +import org.apache.spark.{SparkConf, Logging, SparkException} import org.apache.spark.storage.BlockManagerMessages._ import org.apache.spark.util.{AkkaUtils, Utils} @@ -36,7 +36,7 @@ import org.apache.spark.util.{AkkaUtils, Utils} * all slaves' block managers. */ private[spark] -class BlockManagerMasterActor(val isLocal: Boolean) extends Actor with Logging { +class BlockManagerMasterActor(val isLocal: Boolean, conf: SparkConf) extends Actor with Logging { // Mapping from block manager id to the block manager's information. private val blockManagerInfo = @@ -48,20 +48,18 @@ class BlockManagerMasterActor(val isLocal: Boolean) extends Actor with Logging { // Mapping from block id to the set of block managers that have the block. private val blockLocations = new JHashMap[BlockId, mutable.HashSet[BlockManagerId]] - private val akkaTimeout = AkkaUtils.askTimeout + private val akkaTimeout = AkkaUtils.askTimeout(conf) - initLogging() + val slaveTimeout = conf.get("spark.storage.blockManagerSlaveTimeoutMs", + "" + (BlockManager.getHeartBeatFrequency(conf) * 3)).toLong - val slaveTimeout = System.getProperty("spark.storage.blockManagerSlaveTimeoutMs", - "" + (BlockManager.getHeartBeatFrequencyFromSystemProperties * 3)).toLong - - val checkTimeoutInterval = System.getProperty("spark.storage.blockManagerTimeoutIntervalMs", + val checkTimeoutInterval = conf.get("spark.storage.blockManagerTimeoutIntervalMs", "60000").toLong var timeoutCheckingTask: Cancellable = null override def preStart() { - if (!BlockManager.getDisableHeartBeatsForTesting) { + if (!BlockManager.getDisableHeartBeatsForTesting(conf)) { import context.dispatcher timeoutCheckingTask = context.system.scheduler.schedule( 0.seconds, checkTimeoutInterval.milliseconds, self, ExpireDeadHosts) diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala index 0c66addf9d..21f003609b 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerWorker.scala @@ -30,7 +30,6 @@ import org.apache.spark.util.Utils * TODO: Use event model. */ private[spark] class BlockManagerWorker(val blockManager: BlockManager) extends Logging { - initLogging() blockManager.connectionManager.onReceiveMessage(onBlockMessageReceive) @@ -101,8 +100,6 @@ private[spark] class BlockManagerWorker(val blockManager: BlockManager) extends private[spark] object BlockManagerWorker extends Logging { private var blockManagerWorker: BlockManagerWorker = null - initLogging() - def startBlockManagerWorker(manager: BlockManager) { blockManagerWorker = new BlockManagerWorker(manager) } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala b/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala index 6ce9127c74..a06f50a0ac 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockMessageArray.scala @@ -37,8 +37,6 @@ class BlockMessageArray(var blockMessages: Seq[BlockMessage]) extends Seq[BlockM def length = blockMessages.length - initLogging() - def set(bufferMessage: BufferMessage) { val startTime = System.currentTimeMillis val newBlockMessages = new ArrayBuffer[BlockMessage]() diff --git a/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala index b4451fc7b8..61e63c60d5 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala @@ -74,7 +74,8 @@ class DiskBlockObjectWriter( file: File, serializer: Serializer, bufferSize: Int, - compressStream: OutputStream => OutputStream) + compressStream: OutputStream => OutputStream, + syncWrites: Boolean) extends BlockObjectWriter(blockId) with Logging { @@ -97,8 +98,6 @@ class DiskBlockObjectWriter( override def flush() = out.flush() } - private val syncWrites = System.getProperty("spark.shuffle.sync", "false").toBoolean - /** The file channel, used for repositioning / truncating the file. */ private var channel: FileChannel = null private var bs: OutputStream = null diff --git a/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala index fcd2e97982..55dcb3742c 100644 --- a/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala @@ -38,7 +38,7 @@ private[spark] class DiskBlockManager(shuffleManager: ShuffleBlockManager, rootD extends PathResolver with Logging { private val MAX_DIR_CREATION_ATTEMPTS: Int = 10 - private val subDirsPerLocalDir = System.getProperty("spark.diskStore.subDirectories", "64").toInt + private val subDirsPerLocalDir = shuffleManager.conf.get("spark.diskStore.subDirectories", "64").toInt // Create one local directory for each path mentioned in spark.local.dir; then, inside this // directory, create multiple subdirectories that we will hash files into, in order to avoid diff --git a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala index 212ef6506f..39dc7bb19a 100644 --- a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala @@ -59,12 +59,14 @@ private[spark] trait ShuffleWriterGroup { */ private[spark] class ShuffleBlockManager(blockManager: BlockManager) { + def conf = blockManager.conf + // Turning off shuffle file consolidation causes all shuffle Blocks to get their own file. // TODO: Remove this once the shuffle file consolidation feature is stable. val consolidateShuffleFiles = - System.getProperty("spark.shuffle.consolidateFiles", "false").toBoolean + conf.get("spark.shuffle.consolidateFiles", "false").toBoolean - private val bufferSize = System.getProperty("spark.shuffle.file.buffer.kb", "100").toInt * 1024 + private val bufferSize = conf.get("spark.shuffle.file.buffer.kb", "100").toInt * 1024 /** * Contains all the state related to a particular shuffle. This includes a pool of unused @@ -85,8 +87,8 @@ class ShuffleBlockManager(blockManager: BlockManager) { type ShuffleId = Int private val shuffleStates = new TimeStampedHashMap[ShuffleId, ShuffleState] - private - val metadataCleaner = new MetadataCleaner(MetadataCleanerType.SHUFFLE_BLOCK_MANAGER, this.cleanup) + private val metadataCleaner = + new MetadataCleaner(MetadataCleanerType.SHUFFLE_BLOCK_MANAGER, this.cleanup, conf) def forMapTask(shuffleId: Int, mapId: Int, numBuckets: Int, serializer: Serializer) = { new ShuffleWriterGroup { diff --git a/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala b/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala index d52b3d8284..40734aab49 100644 --- a/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala +++ b/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala @@ -56,7 +56,7 @@ object StoragePerfTester { def writeOutputBytes(mapId: Int, total: AtomicLong) = { val shuffle = blockManager.shuffleBlockManager.forMapTask(1, mapId, numOutputSplits, - new KryoSerializer()) + new KryoSerializer(sc.conf)) val writers = shuffle.writers for (i <- 1 to recordsPerMap) { writers(i % numOutputSplits).write(writeData) diff --git a/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala b/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala index a8db37ded1..dca98c6c05 100644 --- a/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala +++ b/core/src/main/scala/org/apache/spark/storage/ThreadingTest.scala @@ -22,6 +22,7 @@ import akka.actor._ import java.util.concurrent.ArrayBlockingQueue import util.Random import org.apache.spark.serializer.KryoSerializer +import org.apache.spark.{SparkConf, SparkContext} /** * This class tests the BlockManager and MemoryStore for thread safety and @@ -91,11 +92,12 @@ private[spark] object ThreadingTest { def main(args: Array[String]) { System.setProperty("spark.kryoserializer.buffer.mb", "1") val actorSystem = ActorSystem("test") - val serializer = new KryoSerializer + val conf = new SparkConf() + val serializer = new KryoSerializer(conf) val blockManagerMaster = new BlockManagerMaster( - Left(actorSystem.actorOf(Props(new BlockManagerMasterActor(true))))) + Left(actorSystem.actorOf(Props(new BlockManagerMasterActor(true, conf)))), conf) val blockManager = new BlockManager( - "<driver>", actorSystem, blockManagerMaster, serializer, 1024 * 1024) + "<driver>", actorSystem, blockManagerMaster, serializer, 1024 * 1024, conf) val producers = (1 to numProducers).map(i => new ProducerThread(blockManager, i)) val consumers = producers.map(p => new ConsumerThread(blockManager, p.queue)) producers.foreach(_.start) diff --git a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala index f1d86c0221..50dfdbdf5a 100644 --- a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala +++ b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala @@ -1,4 +1,4 @@ -/* +/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. @@ -32,7 +32,7 @@ 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 + val port = sc.conf.get("spark.ui.port", SparkUI.DEFAULT_PORT).toInt var boundPort: Option[Int] = None var server: Option[Server] = None diff --git a/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala index fcd1b518d0..6ba15187d9 100644 --- a/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala +++ b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala @@ -19,7 +19,7 @@ package org.apache.spark.ui import scala.util.Random -import org.apache.spark.SparkContext +import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.SparkContext._ import org.apache.spark.scheduler.SchedulingMode @@ -27,25 +27,26 @@ import org.apache.spark.scheduler.SchedulingMode /** * Continuously generates jobs that expose various features of the WebUI (internal testing tool). * - * Usage: ./run spark.ui.UIWorkloadGenerator [master] + * Usage: ./bin/spark-class org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR] */ 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 org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]") + println("usage: ./bin/spark-class org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]") System.exit(1) } - val master = args(0) - val schedulingMode = SchedulingMode.withName(args(1)) - val appName = "Spark UI Tester" + val conf = new SparkConf().setMaster(args(0)).setAppName("Spark UI tester") + + val schedulingMode = SchedulingMode.withName(args(1)) if (schedulingMode == SchedulingMode.FAIR) { - System.setProperty("spark.scheduler.mode", "FAIR") + conf.set("spark.scheduler.mode", "FAIR") } - val sc = new SparkContext(master, appName) + val sc = new SparkContext(conf) def setProperties(s: String) = { if(schedulingMode == SchedulingMode.FAIR) { @@ -55,11 +56,11 @@ private[spark] object UIWorkloadGenerator { } val baseData = sc.makeRDD(1 to NUM_PARTITIONS * 10, NUM_PARTITIONS) - def nextFloat() = (new Random()).nextFloat() + def nextFloat() = new Random().nextFloat() val jobs = Seq[(String, () => Long)]( ("Count", baseData.count), - ("Cache and Count", baseData.map(x => x).cache.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", { 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 index c5bf2acc9e..88f41be8d3 100644 --- a/core/src/main/scala/org/apache/spark/ui/env/EnvironmentUI.scala +++ b/core/src/main/scala/org/apache/spark/ui/env/EnvironmentUI.scala @@ -48,12 +48,15 @@ private[spark] class EnvironmentUI(sc: SparkContext) { 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") + val sparkProperties = sc.conf.getAll.sorted + + val systemProperties = System.getProperties.iterator.toSeq + val classPathProperty = systemProperties.find { case (k, v) => + k == "java.class.path" }.getOrElse(("", "")) - val sparkProperties = properties.filter(_._1.startsWith("spark")).sorted - val otherProperties = properties.diff(sparkProperties :+ classPathProperty).sorted + val otherProperties = systemProperties.filter { case (k, v) => + k != "java.class.path" && !k.startsWith("spark.") + }.sorted val propertyHeaders = Seq("Name", "Value") def propertyRow(kv: (String, String)) = <tr><td>{kv._1}</td><td>{kv._2}</td></tr> @@ -63,7 +66,7 @@ private[spark] class EnvironmentUI(sc: SparkContext) { UIUtils.listingTable(propertyHeaders, propertyRow, otherProperties, fixedWidth = true) val classPathEntries = classPathProperty._2 - .split(System.getProperty("path.separator", ":")) + .split(sc.conf.get("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")} 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 index 058bc2a2e5..b7b87250b9 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala @@ -33,7 +33,7 @@ import org.apache.spark.scheduler._ */ 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 RETAINED_STAGES = sc.conf.get("spark.ui.retained_stages", "1000").toInt val DEFAULT_POOL_NAME = "default" val stageIdToPool = new HashMap[Int, String]() @@ -106,7 +106,7 @@ private[spark] class JobProgressListener(val sc: SparkContext) extends SparkList val stages = poolToActiveStages.getOrElseUpdate(poolName, new HashSet[StageInfo]()) stages += stage } - + override def onTaskStart(taskStart: SparkListenerTaskStart) = synchronized { val sid = taskStart.task.stageId val tasksActive = stageIdToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]()) diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index 1c8b51b8bc..7df7e3d8e5 100644 --- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -21,6 +21,9 @@ import scala.concurrent.duration.{Duration, FiniteDuration} import akka.actor.{ActorSystem, ExtendedActorSystem, IndestructibleActorSystem} import com.typesafe.config.ConfigFactory +import org.apache.log4j.{Level, Logger} + +import org.apache.spark.SparkConf /** * Various utility classes for working with Akka. @@ -37,22 +40,29 @@ private[spark] object AkkaUtils { * If indestructible is set to true, the Actor System will continue running in the event * of a fatal exception. This is used by [[org.apache.spark.executor.Executor]]. */ - def createActorSystem(name: String, host: String, port: Int, indestructible: Boolean = false) - : (ActorSystem, Int) = { + def createActorSystem(name: String, host: String, port: Int, indestructible: Boolean = false, + conf: SparkConf): (ActorSystem, Int) = { + + val akkaThreads = conf.get("spark.akka.threads", "4").toInt + val akkaBatchSize = conf.get("spark.akka.batchSize", "15").toInt - val akkaThreads = System.getProperty("spark.akka.threads", "4").toInt - val akkaBatchSize = System.getProperty("spark.akka.batchSize", "15").toInt + val akkaTimeout = conf.get("spark.akka.timeout", "100").toInt - val akkaTimeout = System.getProperty("spark.akka.timeout", "100").toInt + val akkaFrameSize = conf.get("spark.akka.frameSize", "10").toInt + val akkaLogLifecycleEvents = conf.get("spark.akka.logLifecycleEvents", "false").toBoolean + val lifecycleEvents = if (akkaLogLifecycleEvents) "on" else "off" + if (!akkaLogLifecycleEvents) { + // As a workaround for Akka issue #3787, we coerce the "EndpointWriter" log to be silent. + // See: https://www.assembla.com/spaces/akka/tickets/3787#/ + Option(Logger.getLogger("akka.remote.EndpointWriter")).map(l => l.setLevel(Level.FATAL)) + } - val akkaFrameSize = System.getProperty("spark.akka.frameSize", "10").toInt - val lifecycleEvents = - if (System.getProperty("spark.akka.logLifecycleEvents", "false").toBoolean) "on" else "off" + val logAkkaConfig = if (conf.get("spark.akka.logAkkaConfig", "false").toBoolean) "on" else "off" - val akkaHeartBeatPauses = System.getProperty("spark.akka.heartbeat.pauses", "600").toInt + val akkaHeartBeatPauses = conf.get("spark.akka.heartbeat.pauses", "600").toInt val akkaFailureDetector = - System.getProperty("spark.akka.failure-detector.threshold", "300.0").toDouble - val akkaHeartBeatInterval = System.getProperty("spark.akka.heartbeat.interval", "1000").toInt + conf.get("spark.akka.failure-detector.threshold", "300.0").toDouble + val akkaHeartBeatInterval = conf.get("spark.akka.heartbeat.interval", "1000").toInt val akkaConf = ConfigFactory.parseString( s""" @@ -72,7 +82,10 @@ private[spark] object AkkaUtils { |akka.remote.netty.tcp.maximum-frame-size = ${akkaFrameSize}MiB |akka.remote.netty.tcp.execution-pool-size = $akkaThreads |akka.actor.default-dispatcher.throughput = $akkaBatchSize + |akka.log-config-on-start = $logAkkaConfig |akka.remote.log-remote-lifecycle-events = $lifecycleEvents + |akka.log-dead-letters = $lifecycleEvents + |akka.log-dead-letters-during-shutdown = $lifecycleEvents """.stripMargin) val actorSystem = if (indestructible) { @@ -87,7 +100,7 @@ private[spark] object AkkaUtils { } /** Returns the default Spark timeout to use for Akka ask operations. */ - def askTimeout: FiniteDuration = { - Duration.create(System.getProperty("spark.akka.askTimeout", "30").toLong, "seconds") + def askTimeout(conf: SparkConf): FiniteDuration = { + Duration.create(conf.get("spark.akka.askTimeout", "30").toLong, "seconds") } } diff --git a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala index fe56960cbf..aa7f52cafb 100644 --- a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala +++ b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala @@ -18,16 +18,21 @@ package org.apache.spark.util import java.util.{TimerTask, Timer} -import org.apache.spark.Logging +import org.apache.spark.{SparkConf, SparkContext, Logging} /** * Runs a timer task to periodically clean up metadata (e.g. old files or hashtable entries) */ -class MetadataCleaner(cleanerType: MetadataCleanerType.MetadataCleanerType, cleanupFunc: (Long) => Unit) extends Logging { +class MetadataCleaner( + cleanerType: MetadataCleanerType.MetadataCleanerType, + cleanupFunc: (Long) => Unit, + conf: SparkConf) + extends Logging +{ val name = cleanerType.toString - private val delaySeconds = MetadataCleaner.getDelaySeconds(cleanerType) + private val delaySeconds = MetadataCleaner.getDelaySeconds(conf, cleanerType) private val periodSeconds = math.max(10, delaySeconds / 10) private val timer = new Timer(name + " cleanup timer", true) @@ -65,22 +70,28 @@ object MetadataCleanerType extends Enumeration { def systemProperty(which: MetadataCleanerType.MetadataCleanerType) = "spark.cleaner.ttl." + which.toString } +// TODO: This mutates a Conf to set properties right now, which is kind of ugly when used in the +// initialization of StreamingContext. It's okay for users trying to configure stuff themselves. object MetadataCleaner { + def getDelaySeconds(conf: SparkConf) = { + conf.get("spark.cleaner.ttl", "3500").toInt + } - // using only sys props for now : so that workers can also get to it while preserving earlier behavior. - def getDelaySeconds = System.getProperty("spark.cleaner.ttl", "-1").toInt - - def getDelaySeconds(cleanerType: MetadataCleanerType.MetadataCleanerType): Int = { - System.getProperty(MetadataCleanerType.systemProperty(cleanerType), getDelaySeconds.toString).toInt + def getDelaySeconds(conf: SparkConf, cleanerType: MetadataCleanerType.MetadataCleanerType): Int = + { + conf.get(MetadataCleanerType.systemProperty(cleanerType), getDelaySeconds(conf).toString) + .toInt } - def setDelaySeconds(cleanerType: MetadataCleanerType.MetadataCleanerType, delay: Int) { - System.setProperty(MetadataCleanerType.systemProperty(cleanerType), delay.toString) + def setDelaySeconds(conf: SparkConf, cleanerType: MetadataCleanerType.MetadataCleanerType, + delay: Int) + { + conf.set(MetadataCleanerType.systemProperty(cleanerType), delay.toString) } - def setDelaySeconds(delay: Int, resetAll: Boolean = true) { + def setDelaySeconds(conf: SparkConf, delay: Int, resetAll: Boolean = true) { // override for all ? - System.setProperty("spark.cleaner.ttl", delay.toString) + conf.set("spark.cleaner.ttl", delay.toString) if (resetAll) { for (cleanerType <- MetadataCleanerType.values) { System.clearProperty(MetadataCleanerType.systemProperty(cleanerType)) diff --git a/core/src/main/scala/org/apache/spark/util/SerializableHyperLogLog.scala b/core/src/main/scala/org/apache/spark/util/SerializableHyperLogLog.scala new file mode 100644 index 0000000000..8b4e7c104c --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/SerializableHyperLogLog.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.util + +import java.io.{Externalizable, ObjectOutput, ObjectInput} +import com.clearspring.analytics.stream.cardinality.{ICardinality, HyperLogLog} + +/** + * A wrapper around [[com.clearspring.analytics.stream.cardinality.HyperLogLog]] that is serializable. + */ +private[spark] +class SerializableHyperLogLog(var value: ICardinality) extends Externalizable { + + def this() = this(null) // For deserialization + + def merge(other: SerializableHyperLogLog) = new SerializableHyperLogLog(value.merge(other.value)) + + def add[T](elem: T) = { + this.value.offer(elem) + this + } + + def readExternal(in: ObjectInput) { + val byteLength = in.readInt() + val bytes = new Array[Byte](byteLength) + in.readFully(bytes) + value = HyperLogLog.Builder.build(bytes) + } + + def writeExternal(out: ObjectOutput) { + val bytes = value.getBytes() + out.writeInt(bytes.length) + out.write(bytes) + } +} diff --git a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala index a25b37a2a9..bddb3bb735 100644 --- a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala +++ b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala @@ -30,10 +30,10 @@ import java.lang.management.ManagementFactory import scala.collection.mutable.ArrayBuffer import it.unimi.dsi.fastutil.ints.IntOpenHashSet -import org.apache.spark.Logging +import org.apache.spark.{SparkEnv, SparkConf, SparkContext, Logging} /** - * Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in + * Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in * memory-aware caches. * * Based on the following JavaWorld article: @@ -89,9 +89,11 @@ private[spark] object SizeEstimator extends Logging { classInfos.put(classOf[Object], new ClassInfo(objectSize, Nil)) } - private def getIsCompressedOops : Boolean = { + private def getIsCompressedOops: Boolean = { + // This is only used by tests to override the detection of compressed oops. The test + // actually uses a system property instead of a SparkConf, so we'll stick with that. if (System.getProperty("spark.test.useCompressedOops") != null) { - return System.getProperty("spark.test.useCompressedOops").toBoolean + return System.getProperty("spark.test.useCompressedOops").toBoolean } try { @@ -103,7 +105,7 @@ private[spark] object SizeEstimator extends Logging { val getVMMethod = hotSpotMBeanClass.getDeclaredMethod("getVMOption", Class.forName("java.lang.String")) - val bean = ManagementFactory.newPlatformMXBeanProxy(server, + val bean = ManagementFactory.newPlatformMXBeanProxy(server, hotSpotMBeanName, hotSpotMBeanClass) // TODO: We could use reflection on the VMOption returned ? return getVMMethod.invoke(bean, "UseCompressedOops").toString.contains("true") @@ -251,7 +253,7 @@ private[spark] object SizeEstimator extends Logging { if (info != null) { return info } - + val parent = getClassInfo(cls.getSuperclass) var shellSize = parent.shellSize var pointerFields = parent.pointerFields diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 3f7858d2de..5f1253100b 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -36,14 +36,13 @@ 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.{SparkException, Logging} +import org.apache.spark.{SparkConf, SparkContext, SparkException, Logging} /** * Various utility methods used by Spark. */ private[spark] object Utils extends Logging { - /** Serialize an object using Java serialization */ def serialize[T](o: T): Array[Byte] = { val bos = new ByteArrayOutputStream() @@ -239,9 +238,9 @@ private[spark] object Utils extends Logging { * Throws SparkException if the target file already exists and has different contents than * the requested file. */ - def fetchFile(url: String, targetDir: File) { + def fetchFile(url: String, targetDir: File, conf: SparkConf) { val filename = url.split("/").last - val tempDir = getLocalDir + val tempDir = getLocalDir(conf) val tempFile = File.createTempFile("fetchFileTemp", null, new File(tempDir)) val targetFile = new File(targetDir, filename) val uri = new URI(url) @@ -311,8 +310,8 @@ private[spark] object Utils extends Logging { * return a single directory, even though the spark.local.dir property might be a list of * multiple paths. */ - def getLocalDir: String = { - System.getProperty("spark.local.dir", System.getProperty("java.io.tmpdir")).split(',')(0) + def getLocalDir(conf: SparkConf): String = { + conf.get("spark.local.dir", System.getProperty("java.io.tmpdir")).split(',')(0) } /** @@ -397,13 +396,12 @@ private[spark] object Utils extends Logging { InetAddress.getByName(address).getHostName } - def localHostPort(): String = { - val retval = System.getProperty("spark.hostPort", null) + def localHostPort(conf: SparkConf): String = { + val retval = conf.get("spark.hostPort", null) if (retval == null) { logErrorWithStack("spark.hostPort not set but invoking localHostPort") return localHostName() } - retval } @@ -415,9 +413,12 @@ private[spark] object Utils extends Logging { 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) } } + try { + throw new Exception + } catch { + case ex: Exception => logError(msg, ex) + } } // Typically, this will be of order of number of nodes in cluster @@ -837,7 +838,7 @@ private[spark] object Utils extends Logging { } } - /** + /** * Timing method based on iterations that permit JVM JIT optimization. * @param numIters number of iterations * @param f function to be executed |