diff --git a/core/pom.xml b/core/pom.xml
index 6af229c71d3ad4742dab73dfe9cfab5fac03fe16..38f4be128019c13d177ff3fe6cc4d11f7b5dff5f 100644
--- a/core/pom.xml
+++ b/core/pom.xml
@@ -95,15 +95,15 @@
<version>0.3.1</version>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-actor</artifactId>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-remote</artifactId>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-slf4j</artifactId>
</dependency>
<dependency>
@@ -126,10 +126,6 @@
<groupId>colt</groupId>
<artifactId>colt</artifactId>
</dependency>
- <dependency>
- <groupId>com.github.scala-incubator.io</groupId>
- <artifactId>scala-io-file_2.9.2</artifactId>
- </dependency>
<dependency>
<groupId>org.apache.mesos</groupId>
<artifactId>mesos</artifactId>
diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
index 3da13133dacde4e342118ab5b28cc1c4593e1d02..66006bf21238d7676ee3827db7cc6b9d695a1cdf 100644
--- a/core/src/main/scala/org/apache/spark/SparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -81,7 +81,7 @@ class SparkContext(
val sparkHome: String = null,
val jars: Seq[String] = Nil,
val environment: Map[String, String] = Map(),
- // This is used only by yarn for now, but should be relevant to other cluster types (mesos, etc)
+ // 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]] =
diff --git a/new-yarn/pom.xml b/new-yarn/pom.xml
new file mode 100644
index 0000000000000000000000000000000000000000..8a065c6d7d1d7f458789f3ab50f0054c8a947dfb
--- /dev/null
+++ b/new-yarn/pom.xml
@@ -0,0 +1,161 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+ ~ Licensed to the Apache Software Foundation (ASF) under one or more
+ ~ contributor license agreements. See the NOTICE file distributed with
+ ~ this work for additional information regarding copyright ownership.
+ ~ The ASF licenses this file to You under the Apache License, Version 2.0
+ ~ (the "License"); you may not use this file except in compliance with
+ ~ the License. You may obtain a copy of the License at
+ ~
+ ~ http://www.apache.org/licenses/LICENSE-2.0
+ ~
+ ~ Unless required by applicable law or agreed to in writing, software
+ ~ distributed under the License is distributed on an "AS IS" BASIS,
+ ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ ~ See the License for the specific language governing permissions and
+ ~ limitations under the License.
+ -->
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+ <modelVersion>4.0.0</modelVersion>
+ <parent>
+ <groupId>org.apache.spark</groupId>
+ <artifactId>spark-parent</artifactId>
+ <version>0.9.0-incubating-SNAPSHOT</version>
+ <relativePath>../pom.xml</relativePath>
+ </parent>
+
+ <groupId>org.apache.spark</groupId>
+ <artifactId>spark-yarn_2.9.3</artifactId>
+ <packaging>jar</packaging>
+ <name>Spark Project YARN Support</name>
+ <url>http://spark.incubator.apache.org/</url>
+
+ <dependencies>
+ <dependency>
+ <groupId>org.apache.spark</groupId>
+ <artifactId>spark-core_2.9.3</artifactId>
+ <version>${project.version}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-yarn-api</artifactId>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-yarn-common</artifactId>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-yarn-client</artifactId>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-client</artifactId>
+ <version>${yarn.version}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.avro</groupId>
+ <artifactId>avro</artifactId>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.avro</groupId>
+ <artifactId>avro-ipc</artifactId>
+ </dependency>
+ <dependency>
+ <groupId>org.scalatest</groupId>
+ <artifactId>scalatest_2.9.3</artifactId>
+ <scope>test</scope>
+ </dependency>
+ <dependency>
+ <groupId>org.mockito</groupId>
+ <artifactId>mockito-all</artifactId>
+ <scope>test</scope>
+ </dependency>
+ </dependencies>
+
+ <build>
+ <outputDirectory>target/scala-${scala.version}/classes</outputDirectory>
+ <testOutputDirectory>target/scala-${scala.version}/test-classes</testOutputDirectory>
+ <plugins>
+ <plugin>
+ <groupId>org.apache.maven.plugins</groupId>
+ <artifactId>maven-shade-plugin</artifactId>
+ <configuration>
+ <shadedArtifactAttached>false</shadedArtifactAttached>
+ <outputFile>${project.build.directory}/${project.artifactId}-${project.version}-shaded.jar</outputFile>
+ <artifactSet>
+ <includes>
+ <include>*:*</include>
+ </includes>
+ </artifactSet>
+ <filters>
+ <filter>
+ <artifact>*:*</artifact>
+ <excludes>
+ <exclude>META-INF/*.SF</exclude>
+ <exclude>META-INF/*.DSA</exclude>
+ <exclude>META-INF/*.RSA</exclude>
+ </excludes>
+ </filter>
+ </filters>
+ </configuration>
+ <executions>
+ <execution>
+ <phase>package</phase>
+ <goals>
+ <goal>shade</goal>
+ </goals>
+ <configuration>
+ <transformers>
+ <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
+ <transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
+ <resource>reference.conf</resource>
+ </transformer>
+ </transformers>
+ </configuration>
+ </execution>
+ </executions>
+ </plugin>
+ <plugin>
+ <groupId>org.apache.maven.plugins</groupId>
+ <artifactId>maven-antrun-plugin</artifactId>
+ <executions>
+ <execution>
+ <phase>test</phase>
+ <goals>
+ <goal>run</goal>
+ </goals>
+ <configuration>
+ <exportAntProperties>true</exportAntProperties>
+ <tasks>
+ <property name="spark.classpath" refid="maven.test.classpath" />
+ <property environment="env" />
+ <fail message="Please set the SCALA_HOME (or SCALA_LIBRARY_PATH if scala is on the path) environment variables and retry.">
+ <condition>
+ <not>
+ <or>
+ <isset property="env.SCALA_HOME" />
+ <isset property="env.SCALA_LIBRARY_PATH" />
+ </or>
+ </not>
+ </condition>
+ </fail>
+ </tasks>
+ </configuration>
+ </execution>
+ </executions>
+ </plugin>
+ <plugin>
+ <groupId>org.scalatest</groupId>
+ <artifactId>scalatest-maven-plugin</artifactId>
+ <configuration>
+ <environmentVariables>
+ <SPARK_HOME>${basedir}/..</SPARK_HOME>
+ <SPARK_TESTING>1</SPARK_TESTING>
+ <SPARK_CLASSPATH>${spark.classpath}</SPARK_CLASSPATH>
+ </environmentVariables>
+ </configuration>
+ </plugin>
+ </plugins>
+ </build>
+</project>
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
new file mode 100644
index 0000000000000000000000000000000000000000..eeeca3ea8a33e4f77562383dfef50a7507628894
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -0,0 +1,446 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.io.IOException
+import java.net.Socket
+import java.util.concurrent.CopyOnWriteArrayList
+import java.util.concurrent.atomic.{AtomicInteger, AtomicReference}
+
+import scala.collection.JavaConversions._
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileSystem, Path}
+import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.util.ShutdownHookManager
+import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.api.records._
+import org.apache.hadoop.yarn.client.api.AMRMClient
+import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.ipc.YarnRPC
+import org.apache.hadoop.yarn.util.{ConverterUtils, Records}
+
+import org.apache.spark.{SparkContext, Logging}
+import org.apache.spark.util.Utils
+
+
+class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) extends Logging {
+
+ def this(args: ApplicationMasterArguments) = this(args, new Configuration())
+
+ private var rpc: YarnRPC = YarnRPC.create(conf)
+ private val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
+ private var appAttemptId: ApplicationAttemptId = _
+ private var userThread: Thread = _
+ private val fs = FileSystem.get(yarnConf)
+
+ private var yarnAllocator: YarnAllocationHandler = _
+ private var isFinished: Boolean = false
+ private var uiAddress: String = _
+ private val maxAppAttempts: Int = conf.getInt(
+ YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS)
+ private var isLastAMRetry: Boolean = true
+ private var amClient: AMRMClient[ContainerRequest] = _
+
+ // Default to numWorkers * 2, with minimum of 3
+ private val maxNumWorkerFailures = System.getProperty("spark.yarn.max.worker.failures",
+ math.max(args.numWorkers * 2, 3).toString()).toInt
+
+ def run() {
+ // Setup the directories so things go to YARN approved directories rather
+ // than user specified and /tmp.
+ System.setProperty("spark.local.dir", getLocalDirs())
+
+ // Use priority 30 as it's higher then HDFS. It's same priority as MapReduce is using.
+ ShutdownHookManager.get().addShutdownHook(new AppMasterShutdownHook(this), 30)
+
+ appAttemptId = getApplicationAttemptId()
+ isLastAMRetry = appAttemptId.getAttemptId() >= maxAppAttempts
+ amClient = AMRMClient.createAMRMClient()
+ amClient.init(yarnConf)
+ amClient.start()
+
+ // Workaround until hadoop moves to something which has
+ // https://issues.apache.org/jira/browse/HADOOP-8406 - fixed in (2.0.2-alpha but no 0.23 line)
+ // org.apache.hadoop.io.compress.CompressionCodecFactory.getCodecClasses(conf)
+
+ ApplicationMaster.register(this)
+
+ // Start the user's JAR
+ userThread = startUserClass()
+
+ // This a bit hacky, but we need to wait until the spark.driver.port property has
+ // been set by the Thread executing the user class.
+ waitForSparkMaster()
+
+ waitForSparkContextInitialized()
+
+ // Do this after Spark master is up and SparkContext is created so that we can register UI Url.
+ val appMasterResponse: RegisterApplicationMasterResponse = registerApplicationMaster()
+
+ // Allocate all containers
+ allocateWorkers()
+
+ // Wait for the user class to Finish
+ userThread.join()
+
+ System.exit(0)
+ }
+
+ /** Get the Yarn approved local directories. */
+ private def getLocalDirs(): String = {
+ // Hadoop 0.23 and 2.x have different Environment variable names for the
+ // local dirs, so lets check both. We assume one of the 2 is set.
+ // LOCAL_DIRS => 2.X, YARN_LOCAL_DIRS => 0.23.X
+ val localDirs = Option(System.getenv("YARN_LOCAL_DIRS"))
+ .getOrElse(Option(System.getenv("LOCAL_DIRS"))
+ .getOrElse(""))
+
+ if (localDirs.isEmpty()) {
+ throw new Exception("Yarn Local dirs can't be empty")
+ }
+ localDirs
+ }
+
+ private def getApplicationAttemptId(): ApplicationAttemptId = {
+ val envs = System.getenv()
+ val containerIdString = envs.get(ApplicationConstants.Environment.CONTAINER_ID.name())
+ val containerId = ConverterUtils.toContainerId(containerIdString)
+ val appAttemptId = containerId.getApplicationAttemptId()
+ logInfo("ApplicationAttemptId: " + appAttemptId)
+ appAttemptId
+ }
+
+ private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
+ logInfo("Registering the ApplicationMaster")
+ amClient.registerApplicationMaster(Utils.localHostName(), 0, uiAddress)
+ }
+
+ private def waitForSparkMaster() {
+ logInfo("Waiting for Spark driver to be reachable.")
+ var driverUp = false
+ var tries = 0
+ val numTries = System.getProperty("spark.yarn.applicationMaster.waitTries", "10").toInt
+ while (!driverUp && tries < numTries) {
+ val driverHost = System.getProperty("spark.driver.host")
+ val driverPort = System.getProperty("spark.driver.port")
+ try {
+ val socket = new Socket(driverHost, driverPort.toInt)
+ socket.close()
+ logInfo("Driver now available: %s:%s".format(driverHost, driverPort))
+ driverUp = true
+ } catch {
+ case e: Exception => {
+ logWarning("Failed to connect to driver at %s:%s, retrying ...".
+ format(driverHost, driverPort))
+ Thread.sleep(100)
+ tries = tries + 1
+ }
+ }
+ }
+ }
+
+ private def startUserClass(): Thread = {
+ logInfo("Starting the user JAR in a separate Thread")
+ val mainMethod = Class.forName(
+ args.userClass,
+ false /* initialize */,
+ Thread.currentThread.getContextClassLoader).getMethod("main", classOf[Array[String]])
+ val t = new Thread {
+ override def run() {
+ var successed = false
+ try {
+ // Copy
+ var mainArgs: Array[String] = new Array[String](args.userArgs.size)
+ args.userArgs.copyToArray(mainArgs, 0, args.userArgs.size)
+ mainMethod.invoke(null, mainArgs)
+ // some job script has "System.exit(0)" at the end, for example SparkPi, SparkLR
+ // userThread will stop here unless it has uncaught exception thrown out
+ // It need shutdown hook to set SUCCEEDED
+ successed = true
+ } finally {
+ logDebug("finishing main")
+ isLastAMRetry = true
+ if (successed) {
+ ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
+ } else {
+ ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.FAILED)
+ }
+ }
+ }
+ }
+ t.start()
+ t
+ }
+
+ // This need to happen before allocateWorkers()
+ private def waitForSparkContextInitialized() {
+ logInfo("Waiting for Spark context initialization")
+ try {
+ var sparkContext: SparkContext = null
+ ApplicationMaster.sparkContextRef.synchronized {
+ var numTries = 0
+ val waitTime = 10000L
+ val maxNumTries = System.getProperty("spark.yarn.ApplicationMaster.waitTries", "10").toInt
+ while (ApplicationMaster.sparkContextRef.get() == null && numTries < maxNumTries) {
+ logInfo("Waiting for Spark context initialization ... " + numTries)
+ numTries = numTries + 1
+ ApplicationMaster.sparkContextRef.wait(waitTime)
+ }
+ sparkContext = ApplicationMaster.sparkContextRef.get()
+ assert(sparkContext != null || numTries >= maxNumTries)
+
+ if (sparkContext != null) {
+ uiAddress = sparkContext.ui.appUIAddress
+ this.yarnAllocator = YarnAllocationHandler.newAllocator(
+ yarnConf,
+ amClient,
+ appAttemptId,
+ args,
+ sparkContext.preferredNodeLocationData)
+ } else {
+ logWarning("Unable to retrieve SparkContext inspite of waiting for %d, maxNumTries = %d".
+ format(numTries * waitTime, maxNumTries))
+ this.yarnAllocator = YarnAllocationHandler.newAllocator(
+ yarnConf,
+ amClient,
+ appAttemptId,
+ args)
+ }
+ }
+ } finally {
+ // In case of exceptions, etc - ensure that count is at least ALLOCATOR_LOOP_WAIT_COUNT :
+ // so that the loop (in ApplicationMaster.sparkContextInitialized) breaks.
+ ApplicationMaster.incrementAllocatorLoop(ApplicationMaster.ALLOCATOR_LOOP_WAIT_COUNT)
+ }
+ }
+
+ private def allocateWorkers() {
+ try {
+ logInfo("Allocating " + args.numWorkers + " workers.")
+ // Wait until all containers have finished
+ // TODO: This is a bit ugly. Can we make it nicer?
+ // TODO: Handle container failure
+ yarnAllocator.addResourceRequests(args.numWorkers)
+ // Exits the loop if the user thread exits.
+ while (yarnAllocator.getNumWorkersRunning < args.numWorkers && userThread.isAlive) {
+ if (yarnAllocator.getNumWorkersFailed >= maxNumWorkerFailures) {
+ finishApplicationMaster(FinalApplicationStatus.FAILED,
+ "max number of worker failures reached")
+ }
+ yarnAllocator.allocateResources()
+ ApplicationMaster.incrementAllocatorLoop(1)
+ Thread.sleep(100)
+ }
+ } finally {
+ // In case of exceptions, etc - ensure that count is at least ALLOCATOR_LOOP_WAIT_COUNT,
+ // so that the loop in ApplicationMaster#sparkContextInitialized() breaks.
+ ApplicationMaster.incrementAllocatorLoop(ApplicationMaster.ALLOCATOR_LOOP_WAIT_COUNT)
+ }
+ logInfo("All workers have launched.")
+
+ // Launch a progress reporter thread, else the app will get killed after expiration
+ // (def: 10mins) timeout.
+ if (userThread.isAlive) {
+ // Ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapses.
+ val timeoutInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000)
+
+ // we want to be reasonably responsive without causing too many requests to RM.
+ val schedulerInterval =
+ System.getProperty("spark.yarn.scheduler.heartbeat.interval-ms", "5000").toLong
+
+ // must be <= timeoutInterval / 2.
+ val interval = math.min(timeoutInterval / 2, schedulerInterval)
+
+ launchReporterThread(interval)
+ }
+ }
+
+ private def launchReporterThread(_sleepTime: Long): Thread = {
+ val sleepTime = if (_sleepTime <= 0 ) 0 else _sleepTime
+
+ val t = new Thread {
+ override def run() {
+ while (userThread.isAlive) {
+ if (yarnAllocator.getNumWorkersFailed >= maxNumWorkerFailures) {
+ finishApplicationMaster(FinalApplicationStatus.FAILED,
+ "max number of worker failures reached")
+ }
+ val missingWorkerCount = args.numWorkers - yarnAllocator.getNumWorkersRunning -
+ yarnAllocator.getNumPendingAllocate
+ if (missingWorkerCount > 0) {
+ logInfo("Allocating %d containers to make up for (potentially) lost containers".
+ format(missingWorkerCount))
+ yarnAllocator.addResourceRequests(missingWorkerCount)
+ }
+ sendProgress()
+ Thread.sleep(sleepTime)
+ }
+ }
+ }
+ // Setting to daemon status, though this is usually not a good idea.
+ t.setDaemon(true)
+ t.start()
+ logInfo("Started progress reporter thread - sleep time : " + sleepTime)
+ t
+ }
+
+ private def sendProgress() {
+ logDebug("Sending progress")
+ // Simulated with an allocate request with no nodes requested.
+ yarnAllocator.allocateResources()
+ }
+
+ /*
+ def printContainers(containers: List[Container]) = {
+ for (container <- containers) {
+ logInfo("Launching shell command on a new container."
+ + ", containerId=" + container.getId()
+ + ", containerNode=" + container.getNodeId().getHost()
+ + ":" + container.getNodeId().getPort()
+ + ", containerNodeURI=" + container.getNodeHttpAddress()
+ + ", containerState" + container.getState()
+ + ", containerResourceMemory"
+ + container.getResource().getMemory())
+ }
+ }
+ */
+
+ def finishApplicationMaster(status: FinalApplicationStatus, diagnostics: String = "") {
+ synchronized {
+ if (isFinished) {
+ return
+ }
+ isFinished = true
+ }
+
+ logInfo("finishApplicationMaster with " + status)
+ // Set tracking URL to empty since we don't have a history server.
+ amClient.unregisterApplicationMaster(status, "" /* appMessage */, "" /* appTrackingUrl */)
+ }
+
+ /**
+ * Clean up the staging directory.
+ */
+ private def cleanupStagingDir() {
+ var stagingDirPath: Path = null
+ try {
+ val preserveFiles = System.getProperty("spark.yarn.preserve.staging.files", "false").toBoolean
+ if (!preserveFiles) {
+ stagingDirPath = new Path(System.getenv("SPARK_YARN_STAGING_DIR"))
+ if (stagingDirPath == null) {
+ logError("Staging directory is null")
+ return
+ }
+ logInfo("Deleting staging directory " + stagingDirPath)
+ fs.delete(stagingDirPath, true)
+ }
+ } catch {
+ case ioe: IOException =>
+ logError("Failed to cleanup staging dir " + stagingDirPath, ioe)
+ }
+ }
+
+ // The shutdown hook that runs when a signal is received AND during normal close of the JVM.
+ class AppMasterShutdownHook(appMaster: ApplicationMaster) extends Runnable {
+
+ def run() {
+ logInfo("AppMaster received a signal.")
+ // we need to clean up staging dir before HDFS is shut down
+ // make sure we don't delete it until this is the last AM
+ if (appMaster.isLastAMRetry) appMaster.cleanupStagingDir()
+ }
+ }
+}
+
+object ApplicationMaster {
+ // Number of times to wait for the allocator loop to complete.
+ // Each loop iteration waits for 100ms, so maximum of 3 seconds.
+ // This is to ensure that we have reasonable number of containers before we start
+ // TODO: Currently, task to container is computed once (TaskSetManager) - which need not be
+ // optimal as more containers are available. Might need to handle this better.
+ private val ALLOCATOR_LOOP_WAIT_COUNT = 30
+
+ private val applicationMasters = new CopyOnWriteArrayList[ApplicationMaster]()
+
+ val sparkContextRef: AtomicReference[SparkContext] =
+ new AtomicReference[SparkContext](null /* initialValue */)
+
+ val yarnAllocatorLoop: AtomicInteger = new AtomicInteger(0)
+
+ def incrementAllocatorLoop(by: Int) {
+ val count = yarnAllocatorLoop.getAndAdd(by)
+ if (count >= ALLOCATOR_LOOP_WAIT_COUNT) {
+ yarnAllocatorLoop.synchronized {
+ // to wake threads off wait ...
+ yarnAllocatorLoop.notifyAll()
+ }
+ }
+ }
+
+ def register(master: ApplicationMaster) {
+ applicationMasters.add(master)
+ }
+
+ // TODO(harvey): See whether this should be discarded - it isn't used anywhere atm...
+ def sparkContextInitialized(sc: SparkContext): Boolean = {
+ var modified = false
+ sparkContextRef.synchronized {
+ modified = sparkContextRef.compareAndSet(null, sc)
+ sparkContextRef.notifyAll()
+ }
+
+ // Add a shutdown hook - as a best case effort in case users do not call sc.stop or do
+ // System.exit.
+ // Should not really have to do this, but it helps YARN to evict resources earlier.
+ // Not to mention, prevent the Client from declaring failure even though we exited properly.
+ // Note that this will unfortunately not properly clean up the staging files because it gets
+ // called too late, after the filesystem is already shutdown.
+ if (modified) {
+ Runtime.getRuntime().addShutdownHook(new Thread with Logging {
+ // This is not only logs, but also ensures that log system is initialized for this instance
+ // when we are actually 'run'-ing.
+ logInfo("Adding shutdown hook for context " + sc)
+ override def run() {
+ logInfo("Invoking sc stop from shutdown hook")
+ sc.stop()
+ // Best case ...
+ for (master <- applicationMasters) {
+ master.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
+ }
+ }
+ } )
+ }
+
+ // Wait for initialization to complete and atleast 'some' nodes can get allocated.
+ yarnAllocatorLoop.synchronized {
+ while (yarnAllocatorLoop.get() <= ALLOCATOR_LOOP_WAIT_COUNT) {
+ yarnAllocatorLoop.wait(1000L)
+ }
+ }
+ modified
+ }
+
+ def main(argStrings: Array[String]) {
+ val args = new ApplicationMasterArguments(argStrings)
+ new ApplicationMaster(args).run()
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala
new file mode 100644
index 0000000000000000000000000000000000000000..f76a5ddd39e90d4998d7712113dd0949823d5e18
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMasterArguments.scala
@@ -0,0 +1,94 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import org.apache.spark.util.IntParam
+import collection.mutable.ArrayBuffer
+
+class ApplicationMasterArguments(val args: Array[String]) {
+ var userJar: String = null
+ var userClass: String = null
+ var userArgs: Seq[String] = Seq[String]()
+ var workerMemory = 1024
+ var workerCores = 1
+ var numWorkers = 2
+
+ parseArgs(args.toList)
+
+ private def parseArgs(inputArgs: List[String]): Unit = {
+ val userArgsBuffer = new ArrayBuffer[String]()
+
+ var args = inputArgs
+
+ while (! args.isEmpty) {
+
+ args match {
+ case ("--jar") :: value :: tail =>
+ userJar = value
+ args = tail
+
+ case ("--class") :: value :: tail =>
+ userClass = value
+ args = tail
+
+ case ("--args") :: value :: tail =>
+ userArgsBuffer += value
+ args = tail
+
+ case ("--num-workers") :: IntParam(value) :: tail =>
+ numWorkers = value
+ args = tail
+
+ case ("--worker-memory") :: IntParam(value) :: tail =>
+ workerMemory = value
+ args = tail
+
+ case ("--worker-cores") :: IntParam(value) :: tail =>
+ workerCores = value
+ args = tail
+
+ case Nil =>
+ if (userJar == null || userClass == null) {
+ printUsageAndExit(1)
+ }
+
+ case _ =>
+ printUsageAndExit(1, args)
+ }
+ }
+
+ userArgs = userArgsBuffer.readOnly
+ }
+
+ def printUsageAndExit(exitCode: Int, unknownParam: Any = null) {
+ if (unknownParam != null) {
+ System.err.println("Unknown/unsupported param " + unknownParam)
+ }
+ System.err.println(
+ "Usage: org.apache.spark.deploy.yarn.ApplicationMaster [options] \n" +
+ "Options:\n" +
+ " --jar JAR_PATH Path to your application's JAR file (required)\n" +
+ " --class CLASS_NAME Name of your application's main class (required)\n" +
+ " --args ARGS Arguments to be passed to your application's main class.\n" +
+ " Mutliple invocations are possible, each will be passed in order.\n" +
+ " --num-workers NUM Number of workers to start (Default: 2)\n" +
+ " --worker-cores NUM Number of cores for the workers (Default: 1)\n" +
+ " --worker-memory MEM Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n")
+ System.exit(exitCode)
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
new file mode 100644
index 0000000000000000000000000000000000000000..94678815e806ad66680880e59ac4f7c01d1fd67c
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -0,0 +1,519 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.{InetAddress, UnknownHostException, URI}
+import java.nio.ByteBuffer
+
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
+import scala.collection.mutable.Map
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileContext, FileStatus, FileSystem, Path, FileUtil}
+import org.apache.hadoop.fs.permission.FsPermission;
+import org.apache.hadoop.io.DataOutputBuffer
+import org.apache.hadoop.mapred.Master
+import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
+import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.api.records._
+import org.apache.hadoop.yarn.client.api.impl.YarnClientImpl
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.ipc.YarnRPC
+import org.apache.hadoop.yarn.util.{Apps, Records}
+
+import org.apache.spark.Logging
+import org.apache.spark.util.Utils
+import org.apache.spark.deploy.SparkHadoopUtil
+
+
+/**
+ * The entry point (starting in Client#main() and Client#run()) for launching Spark on YARN. The
+ * Client submits an application to the global ResourceManager to launch Spark's ApplicationMaster,
+ * which will launch a Spark master process and negotiate resources throughout its duration.
+ */
+class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl with Logging {
+
+ var rpc: YarnRPC = YarnRPC.create(conf)
+ val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
+ val credentials = UserGroupInformation.getCurrentUser().getCredentials()
+ private val SPARK_STAGING: String = ".sparkStaging"
+ private val distCacheMgr = new ClientDistributedCacheManager()
+
+ // Staging directory is private! -> rwx--------
+ val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700: Short)
+ // App files are world-wide readable and owner writable -> rw-r--r--
+ val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644: Short)
+
+ def this(args: ClientArguments) = this(new Configuration(), args)
+
+ def runApp(): ApplicationId = {
+ validateArgs()
+ // Initialize and start the client service.
+ init(yarnConf)
+ start()
+
+ // Log details about this YARN cluster (e.g, the number of slave machines/NodeManagers).
+ logClusterResourceDetails()
+
+ // Prepare to submit a request to the ResourcManager (specifically its ApplicationsManager (ASM)
+ // interface).
+
+ // Get a new client application.
+ val newApp = super.createApplication()
+ val newAppResponse = newApp.getNewApplicationResponse()
+ val appId = newAppResponse.getApplicationId()
+
+ verifyClusterResources(newAppResponse)
+
+ // Set up resource and environment variables.
+ val appStagingDir = getAppStagingDir(appId)
+ val localResources = prepareLocalResources(appStagingDir)
+ val launchEnv = setupLaunchEnv(localResources, appStagingDir)
+ val amContainer = createContainerLaunchContext(newAppResponse, localResources, launchEnv)
+
+ // Set up an application submission context.
+ val appContext = newApp.getApplicationSubmissionContext()
+ appContext.setApplicationName(args.appName)
+ appContext.setQueue(args.amQueue)
+ appContext.setAMContainerSpec(amContainer)
+
+ // Memory for the ApplicationMaster.
+ val memoryResource = Records.newRecord(classOf[Resource]).asInstanceOf[Resource]
+ memoryResource.setMemory(args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+ appContext.setResource(memoryResource)
+
+ // Finally, submit and monitor the application.
+ submitApp(appContext)
+ appId
+ }
+
+ def run() {
+ val appId = runApp()
+ monitorApplication(appId)
+ System.exit(0)
+ }
+
+ // TODO(harvey): This could just go in ClientArguments.
+ def validateArgs() = {
+ Map(
+ (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!",
+ (args.userJar == null) -> "Error: You must specify a user jar!",
+ (args.userClass == null) -> "Error: You must specify a user class!",
+ (args.numWorkers <= 0) -> "Error: You must specify atleast 1 worker!",
+ (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be" +
+ "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD),
+ (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size" +
+ "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString)
+ ).foreach { case(cond, errStr) =>
+ if (cond) {
+ logError(errStr)
+ args.printUsageAndExit(1)
+ }
+ }
+ }
+
+ def getAppStagingDir(appId: ApplicationId): String = {
+ SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR
+ }
+
+ def logClusterResourceDetails() {
+ val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics
+ logInfo("Got Cluster metric info from ApplicationsManager (ASM), number of NodeManagers: " +
+ clusterMetrics.getNumNodeManagers)
+
+ val queueInfo: QueueInfo = super.getQueueInfo(args.amQueue)
+ logInfo("""Queue info ... queueName: %s, queueCurrentCapacity: %s, queueMaxCapacity: %s,
+ queueApplicationCount = %s, queueChildQueueCount = %s""".format(
+ queueInfo.getQueueName,
+ queueInfo.getCurrentCapacity,
+ queueInfo.getMaximumCapacity,
+ queueInfo.getApplications.size,
+ queueInfo.getChildQueues.size))
+ }
+
+ def verifyClusterResources(app: GetNewApplicationResponse) = {
+ val maxMem = app.getMaximumResourceCapability().getMemory()
+ logInfo("Max mem capabililty of a single resource in this cluster " + maxMem)
+
+ // If we have requested more then the clusters max for a single resource then exit.
+ if (args.workerMemory > maxMem) {
+ logError("Required worker memory (%d MB), is above the max threshold (%d MB) of this cluster.".
+ format(args.workerMemory, maxMem))
+ System.exit(1)
+ }
+ val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD
+ if (amMem > maxMem) {
+ logError("Required AM memory (%d) is above the max threshold (%d) of this cluster".
+ format(args.amMemory, maxMem))
+ System.exit(1)
+ }
+
+ // We could add checks to make sure the entire cluster has enough resources but that involves
+ // getting all the node reports and computing ourselves.
+ }
+
+ /** See if two file systems are the same or not. */
+ private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = {
+ val srcUri = srcFs.getUri()
+ val dstUri = destFs.getUri()
+ if (srcUri.getScheme() == null) {
+ return false
+ }
+ if (!srcUri.getScheme().equals(dstUri.getScheme())) {
+ return false
+ }
+ var srcHost = srcUri.getHost()
+ var dstHost = dstUri.getHost()
+ if ((srcHost != null) && (dstHost != null)) {
+ try {
+ srcHost = InetAddress.getByName(srcHost).getCanonicalHostName()
+ dstHost = InetAddress.getByName(dstHost).getCanonicalHostName()
+ } catch {
+ case e: UnknownHostException =>
+ return false
+ }
+ if (!srcHost.equals(dstHost)) {
+ return false
+ }
+ } else if (srcHost == null && dstHost != null) {
+ return false
+ } else if (srcHost != null && dstHost == null) {
+ return false
+ }
+ //check for ports
+ if (srcUri.getPort() != dstUri.getPort()) {
+ return false
+ }
+ return true
+ }
+
+ /** Copy the file into HDFS if needed. */
+ private def copyRemoteFile(
+ dstDir: Path,
+ originalPath: Path,
+ replication: Short,
+ setPerms: Boolean = false): Path = {
+ val fs = FileSystem.get(conf)
+ val remoteFs = originalPath.getFileSystem(conf)
+ var newPath = originalPath
+ if (! compareFs(remoteFs, fs)) {
+ newPath = new Path(dstDir, originalPath.getName())
+ logInfo("Uploading " + originalPath + " to " + newPath)
+ FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf)
+ fs.setReplication(newPath, replication)
+ if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION))
+ }
+ // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific
+ // version shows the specific version in the distributed cache configuration
+ val qualPath = fs.makeQualified(newPath)
+ val fc = FileContext.getFileContext(qualPath.toUri(), conf)
+ val destPath = fc.resolvePath(qualPath)
+ destPath
+ }
+
+ def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = {
+ logInfo("Preparing Local resources")
+ // Upload Spark and the application JAR to the remote file system if necessary. Add them as
+ // local resources to the application master.
+ val fs = FileSystem.get(conf)
+
+ val delegTokenRenewer = Master.getMasterPrincipal(conf)
+ if (UserGroupInformation.isSecurityEnabled()) {
+ if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) {
+ logError("Can't get Master Kerberos principal for use as renewer")
+ System.exit(1)
+ }
+ }
+ val dst = new Path(fs.getHomeDirectory(), appStagingDir)
+ val replication = System.getProperty("spark.yarn.submit.file.replication", "3").toShort
+
+ if (UserGroupInformation.isSecurityEnabled()) {
+ val dstFs = dst.getFileSystem(conf)
+ dstFs.addDelegationTokens(delegTokenRenewer, credentials)
+ }
+
+ val localResources = HashMap[String, LocalResource]()
+ FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION))
+
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+
+ Map(
+ Client.SPARK_JAR -> System.getenv("SPARK_JAR"), Client.APP_JAR -> args.userJar,
+ Client.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF")
+ ).foreach { case(destName, _localPath) =>
+ val localPath: String = if (_localPath != null) _localPath.trim() else ""
+ if (! localPath.isEmpty()) {
+ var localURI = new URI(localPath)
+ // If not specified assume these are in the local filesystem to keep behavior like Hadoop
+ if (localURI.getScheme() == null) {
+ localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString)
+ }
+ val setPermissions = if (destName.equals(Client.APP_JAR)) true else false
+ val destPath = copyRemoteFile(dst, new Path(localURI), replication, setPermissions)
+ distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+ destName, statCache)
+ }
+ }
+
+ // Handle jars local to the ApplicationMaster.
+ if ((args.addJars != null) && (!args.addJars.isEmpty())){
+ args.addJars.split(',').foreach { case file: String =>
+ val localURI = new URI(file.trim())
+ val localPath = new Path(localURI)
+ val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+ val destPath = copyRemoteFile(dst, localPath, replication)
+ // Only add the resource to the Spark ApplicationMaster.
+ val appMasterOnly = true
+ distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+ linkname, statCache, appMasterOnly)
+ }
+ }
+
+ // Handle any distributed cache files
+ if ((args.files != null) && (!args.files.isEmpty())){
+ args.files.split(',').foreach { case file: String =>
+ val localURI = new URI(file.trim())
+ val localPath = new Path(localURI)
+ val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+ val destPath = copyRemoteFile(dst, localPath, replication)
+ distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+ linkname, statCache)
+ }
+ }
+
+ // Handle any distributed cache archives
+ if ((args.archives != null) && (!args.archives.isEmpty())) {
+ args.archives.split(',').foreach { case file:String =>
+ val localURI = new URI(file.trim())
+ val localPath = new Path(localURI)
+ val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+ val destPath = copyRemoteFile(dst, localPath, replication)
+ distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE,
+ linkname, statCache)
+ }
+ }
+
+ UserGroupInformation.getCurrentUser().addCredentials(credentials)
+ localResources
+ }
+
+ def setupLaunchEnv(
+ localResources: HashMap[String, LocalResource],
+ stagingDir: String): HashMap[String, String] = {
+ logInfo("Setting up the launch environment")
+ val log4jConfLocalRes = localResources.getOrElse(Client.LOG4J_PROP, null)
+
+ val env = new HashMap[String, String]()
+
+ Client.populateClasspath(yarnConf, log4jConfLocalRes != null, env)
+ env("SPARK_YARN_MODE") = "true"
+ env("SPARK_YARN_STAGING_DIR") = stagingDir
+
+ // Set the environment variables to be passed on to the Workers.
+ distCacheMgr.setDistFilesEnv(env)
+ distCacheMgr.setDistArchivesEnv(env)
+
+ // Allow users to specify some environment variables.
+ Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
+
+ // Add each SPARK_* key to the environment.
+ System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
+
+ env
+ }
+
+ def userArgsToString(clientArgs: ClientArguments): String = {
+ val prefix = " --args "
+ val args = clientArgs.userArgs
+ val retval = new StringBuilder()
+ for (arg <- args){
+ retval.append(prefix).append(" '").append(arg).append("' ")
+ }
+ retval.toString
+ }
+
+ def createContainerLaunchContext(
+ newApp: GetNewApplicationResponse,
+ localResources: HashMap[String, LocalResource],
+ env: HashMap[String, String]): ContainerLaunchContext = {
+ logInfo("Setting up container launch context")
+ val amContainer = Records.newRecord(classOf[ContainerLaunchContext])
+ amContainer.setLocalResources(localResources)
+ amContainer.setEnvironment(env)
+
+ // TODO: Need a replacement for the following code to fix -Xmx?
+ // val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory()
+ // var amMemory = ((args.amMemory / minResMemory) * minResMemory) +
+ // ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) -
+ // YarnAllocationHandler.MEMORY_OVERHEAD)
+
+ // Extra options for the JVM
+ var JAVA_OPTS = ""
+
+ // Add Xmx for AM memory
+ JAVA_OPTS += "-Xmx" + args.amMemory + "m"
+
+ val tmpDir = new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR)
+ JAVA_OPTS += " -Djava.io.tmpdir=" + tmpDir
+
+ // TODO: Remove once cpuset version is pushed out.
+ // The context is, default gc for server class machines ends up using all cores to do gc -
+ // hence if there are multiple containers in same node, Spark GC affects all other containers'
+ // performance (which can be that of other Spark containers)
+ // Instead of using this, rely on cpusets by YARN to enforce "proper" Spark behavior in
+ // multi-tenant environments. Not sure how default Java GC behaves if it is limited to subset
+ // of cores on a node.
+ val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") &&
+ java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))
+ if (useConcurrentAndIncrementalGC) {
+ // In our expts, using (default) throughput collector has severe perf ramifications in
+ // multi-tenant machines
+ JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
+ JAVA_OPTS += " -XX:+CMSIncrementalMode "
+ JAVA_OPTS += " -XX:+CMSIncrementalPacing "
+ JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 "
+ JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 "
+ }
+
+ if (env.isDefinedAt("SPARK_JAVA_OPTS")) {
+ JAVA_OPTS += " " + env("SPARK_JAVA_OPTS")
+ }
+
+ // Command for the ApplicationMaster
+ var javaCommand = "java"
+ val javaHome = System.getenv("JAVA_HOME")
+ if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) {
+ javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
+ }
+
+ val commands = List[String](
+ javaCommand +
+ " -server " +
+ JAVA_OPTS +
+ " " + args.amClass +
+ " --class " + args.userClass +
+ " --jar " + args.userJar +
+ userArgsToString(args) +
+ " --worker-memory " + args.workerMemory +
+ " --worker-cores " + args.workerCores +
+ " --num-workers " + args.numWorkers +
+ " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" +
+ " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
+
+ logInfo("Command for starting the Spark ApplicationMaster: " + commands(0))
+ amContainer.setCommands(commands)
+
+ // Setup security tokens.
+ val dob = new DataOutputBuffer()
+ credentials.writeTokenStorageToStream(dob)
+ amContainer.setTokens(ByteBuffer.wrap(dob.getData()))
+
+ amContainer
+ }
+
+ def submitApp(appContext: ApplicationSubmissionContext) = {
+ // Submit the application to the applications manager.
+ logInfo("Submitting application to ASM")
+ super.submitApplication(appContext)
+ }
+
+ def monitorApplication(appId: ApplicationId): Boolean = {
+ while (true) {
+ Thread.sleep(1000)
+ val report = super.getApplicationReport(appId)
+
+ logInfo("Application report from ASM: \n" +
+ "\t application identifier: " + appId.toString() + "\n" +
+ "\t appId: " + appId.getId() + "\n" +
+ "\t clientToAMToken: " + report.getClientToAMToken() + "\n" +
+ "\t appDiagnostics: " + report.getDiagnostics() + "\n" +
+ "\t appMasterHost: " + report.getHost() + "\n" +
+ "\t appQueue: " + report.getQueue() + "\n" +
+ "\t appMasterRpcPort: " + report.getRpcPort() + "\n" +
+ "\t appStartTime: " + report.getStartTime() + "\n" +
+ "\t yarnAppState: " + report.getYarnApplicationState() + "\n" +
+ "\t distributedFinalState: " + report.getFinalApplicationStatus() + "\n" +
+ "\t appTrackingUrl: " + report.getTrackingUrl() + "\n" +
+ "\t appUser: " + report.getUser()
+ )
+
+ val state = report.getYarnApplicationState()
+ val dsStatus = report.getFinalApplicationStatus()
+ if (state == YarnApplicationState.FINISHED ||
+ state == YarnApplicationState.FAILED ||
+ state == YarnApplicationState.KILLED) {
+ return true
+ }
+ }
+ true
+ }
+}
+
+object Client {
+ val SPARK_JAR: String = "spark.jar"
+ val APP_JAR: String = "app.jar"
+ val LOG4J_PROP: String = "log4j.properties"
+
+ def main(argStrings: Array[String]) {
+ // Set an env variable indicating we are running in YARN mode.
+ // Note: anything env variable with SPARK_ prefix gets propagated to all (remote) processes -
+ // see Client#setupLaunchEnv().
+ System.setProperty("SPARK_YARN_MODE", "true")
+
+ val args = new ClientArguments(argStrings)
+
+ (new Client(args)).run()
+ }
+
+ // Based on code from org.apache.hadoop.mapreduce.v2.util.MRApps
+ def populateHadoopClasspath(conf: Configuration, env: HashMap[String, String]) {
+ for (c <- conf.getStrings(YarnConfiguration.YARN_APPLICATION_CLASSPATH)) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, c.trim)
+ }
+ }
+
+ def populateClasspath(conf: Configuration, addLog4j: Boolean, env: HashMap[String, String]) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
+ // If log4j present, ensure ours overrides all others
+ if (addLog4j) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + LOG4J_PROP)
+ }
+ // Normally the users app.jar is last in case conflicts with spark jars
+ val userClasspathFirst = System.getProperty("spark.yarn.user.classpath.first", "false")
+ .toBoolean
+ if (userClasspathFirst) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + APP_JAR)
+ }
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + SPARK_JAR)
+ Client.populateHadoopClasspath(conf, env)
+
+ if (!userClasspathFirst) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + APP_JAR)
+ }
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "*")
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
new file mode 100644
index 0000000000000000000000000000000000000000..9efb28a9426726c4e41e4287291b8ab939ba942e
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
@@ -0,0 +1,148 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import scala.collection.mutable.{ArrayBuffer, HashMap}
+
+import org.apache.spark.scheduler.{InputFormatInfo, SplitInfo}
+import org.apache.spark.util.IntParam
+import org.apache.spark.util.MemoryParam
+
+
+// TODO: Add code and support for ensuring that yarn resource 'tasks' are location aware !
+class ClientArguments(val args: Array[String]) {
+ var addJars: String = null
+ var files: String = null
+ var archives: String = null
+ var userJar: String = null
+ var userClass: String = null
+ var userArgs: Seq[String] = Seq[String]()
+ var workerMemory = 1024 // MB
+ var workerCores = 1
+ var numWorkers = 2
+ var amQueue = System.getProperty("QUEUE", "default")
+ var amMemory: Int = 512 // MB
+ var amClass: String = "org.apache.spark.deploy.yarn.ApplicationMaster"
+ var appName: String = "Spark"
+ // TODO
+ var inputFormatInfo: List[InputFormatInfo] = null
+ // TODO(harvey)
+ var priority = 0
+
+ parseArgs(args.toList)
+
+ private def parseArgs(inputArgs: List[String]): Unit = {
+ val userArgsBuffer: ArrayBuffer[String] = new ArrayBuffer[String]()
+ val inputFormatMap: HashMap[String, InputFormatInfo] = new HashMap[String, InputFormatInfo]()
+
+ var args = inputArgs
+
+ while (!args.isEmpty) {
+ args match {
+ case ("--jar") :: value :: tail =>
+ userJar = value
+ args = tail
+
+ case ("--class") :: value :: tail =>
+ userClass = value
+ args = tail
+
+ case ("--args") :: value :: tail =>
+ userArgsBuffer += value
+ args = tail
+
+ case ("--master-class") :: value :: tail =>
+ amClass = value
+ args = tail
+
+ case ("--master-memory") :: MemoryParam(value) :: tail =>
+ amMemory = value
+ args = tail
+
+ case ("--num-workers") :: IntParam(value) :: tail =>
+ numWorkers = value
+ args = tail
+
+ case ("--worker-memory") :: MemoryParam(value) :: tail =>
+ workerMemory = value
+ args = tail
+
+ case ("--worker-cores") :: IntParam(value) :: tail =>
+ workerCores = value
+ args = tail
+
+ case ("--queue") :: value :: tail =>
+ amQueue = value
+ args = tail
+
+ case ("--name") :: value :: tail =>
+ appName = value
+
+ case ("--addJars") :: value :: tail =>
+ addJars = value
+ args = tail
+
+ case ("--files") :: value :: tail =>
+ files = value
+ args = tail
+
+ case ("--archives") :: value :: tail =>
+ archives = value
+ args = tail
+
+ case Nil =>
+ if (userJar == null || userClass == null) {
+ printUsageAndExit(1)
+ }
+
+ case _ =>
+ printUsageAndExit(1, args)
+ }
+ }
+
+ userArgs = userArgsBuffer.readOnly
+ inputFormatInfo = inputFormatMap.values.toList
+ }
+
+
+ def printUsageAndExit(exitCode: Int, unknownParam: Any = null) {
+ if (unknownParam != null) {
+ System.err.println("Unknown/unsupported param " + unknownParam)
+ }
+ System.err.println(
+ "Usage: org.apache.spark.deploy.yarn.Client [options] \n" +
+ "Options:\n" +
+ " --jar JAR_PATH Path to your application's JAR file (required)\n" +
+ " --class CLASS_NAME Name of your application's main class (required)\n" +
+ " --args ARGS Arguments to be passed to your application's main class.\n" +
+ " Mutliple invocations are possible, each will be passed in order.\n" +
+ " --num-workers NUM Number of workers to start (Default: 2)\n" +
+ " --worker-cores NUM Number of cores for the workers (Default: 1). This is unsused right now.\n" +
+ " --master-class CLASS_NAME Class Name for Master (Default: spark.deploy.yarn.ApplicationMaster)\n" +
+ " --master-memory MEM Memory for Master (e.g. 1000M, 2G) (Default: 512 Mb)\n" +
+ " --worker-memory MEM Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n" +
+ " --name NAME The name of your application (Default: Spark)\n" +
+ " --queue QUEUE The hadoop queue to use for allocation requests (Default: 'default')\n" +
+ " --addJars jars Comma separated list of local jars that want SparkContext.addJar to work with.\n" +
+ " --files files Comma separated list of files to be distributed with the job.\n" +
+ " --archives archives Comma separated list of archives to be distributed with the job."
+ )
+ System.exit(exitCode)
+ }
+
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManager.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManager.scala
new file mode 100644
index 0000000000000000000000000000000000000000..5f159b073f5372dc9e1f73347f88ae8aa48e0cbb
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManager.scala
@@ -0,0 +1,228 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.URI
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.FileStatus
+import org.apache.hadoop.fs.FileSystem
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.fs.permission.FsAction
+import org.apache.hadoop.yarn.api.records.LocalResource
+import org.apache.hadoop.yarn.api.records.LocalResourceVisibility
+import org.apache.hadoop.yarn.api.records.LocalResourceType
+import org.apache.hadoop.yarn.util.{Records, ConverterUtils}
+
+import org.apache.spark.Logging
+
+import scala.collection.mutable.HashMap
+import scala.collection.mutable.LinkedHashMap
+import scala.collection.mutable.Map
+
+
+/** Client side methods to setup the Hadoop distributed cache */
+class ClientDistributedCacheManager() extends Logging {
+ private val distCacheFiles: Map[String, Tuple3[String, String, String]] =
+ LinkedHashMap[String, Tuple3[String, String, String]]()
+ private val distCacheArchives: Map[String, Tuple3[String, String, String]] =
+ LinkedHashMap[String, Tuple3[String, String, String]]()
+
+
+ /**
+ * Add a resource to the list of distributed cache resources. This list can
+ * be sent to the ApplicationMaster and possibly the workers so that it can
+ * be downloaded into the Hadoop distributed cache for use by this application.
+ * Adds the LocalResource to the localResources HashMap passed in and saves
+ * the stats of the resources to they can be sent to the workers and verified.
+ *
+ * @param fs FileSystem
+ * @param conf Configuration
+ * @param destPath path to the resource
+ * @param localResources localResource hashMap to insert the resource into
+ * @param resourceType LocalResourceType
+ * @param link link presented in the distributed cache to the destination
+ * @param statCache cache to store the file/directory stats
+ * @param appMasterOnly Whether to only add the resource to the app master
+ */
+ def addResource(
+ fs: FileSystem,
+ conf: Configuration,
+ destPath: Path,
+ localResources: HashMap[String, LocalResource],
+ resourceType: LocalResourceType,
+ link: String,
+ statCache: Map[URI, FileStatus],
+ appMasterOnly: Boolean = false) = {
+ val destStatus = fs.getFileStatus(destPath)
+ val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource]
+ amJarRsrc.setType(resourceType)
+ val visibility = getVisibility(conf, destPath.toUri(), statCache)
+ amJarRsrc.setVisibility(visibility)
+ amJarRsrc.setResource(ConverterUtils.getYarnUrlFromPath(destPath))
+ amJarRsrc.setTimestamp(destStatus.getModificationTime())
+ amJarRsrc.setSize(destStatus.getLen())
+ if (link == null || link.isEmpty()) throw new Exception("You must specify a valid link name")
+ localResources(link) = amJarRsrc
+
+ if (appMasterOnly == false) {
+ val uri = destPath.toUri()
+ val pathURI = new URI(uri.getScheme(), uri.getAuthority(), uri.getPath(), null, link)
+ if (resourceType == LocalResourceType.FILE) {
+ distCacheFiles(pathURI.toString()) = (destStatus.getLen().toString(),
+ destStatus.getModificationTime().toString(), visibility.name())
+ } else {
+ distCacheArchives(pathURI.toString()) = (destStatus.getLen().toString(),
+ destStatus.getModificationTime().toString(), visibility.name())
+ }
+ }
+ }
+
+ /**
+ * Adds the necessary cache file env variables to the env passed in
+ * @param env
+ */
+ def setDistFilesEnv(env: Map[String, String]) = {
+ val (keys, tupleValues) = distCacheFiles.unzip
+ val (sizes, timeStamps, visibilities) = tupleValues.unzip3
+
+ if (keys.size > 0) {
+ env("SPARK_YARN_CACHE_FILES") = keys.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_FILES_TIME_STAMPS") =
+ timeStamps.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_FILES_FILE_SIZES") =
+ sizes.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_FILES_VISIBILITIES") =
+ visibilities.reduceLeft[String] { (acc,n) => acc + "," + n }
+ }
+ }
+
+ /**
+ * Adds the necessary cache archive env variables to the env passed in
+ * @param env
+ */
+ def setDistArchivesEnv(env: Map[String, String]) = {
+ val (keys, tupleValues) = distCacheArchives.unzip
+ val (sizes, timeStamps, visibilities) = tupleValues.unzip3
+
+ if (keys.size > 0) {
+ env("SPARK_YARN_CACHE_ARCHIVES") = keys.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS") =
+ timeStamps.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES") =
+ sizes.reduceLeft[String] { (acc,n) => acc + "," + n }
+ env("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES") =
+ visibilities.reduceLeft[String] { (acc,n) => acc + "," + n }
+ }
+ }
+
+ /**
+ * Returns the local resource visibility depending on the cache file permissions
+ * @param conf
+ * @param uri
+ * @param statCache
+ * @return LocalResourceVisibility
+ */
+ def getVisibility(conf: Configuration, uri: URI, statCache: Map[URI, FileStatus]):
+ LocalResourceVisibility = {
+ if (isPublic(conf, uri, statCache)) {
+ return LocalResourceVisibility.PUBLIC
+ }
+ return LocalResourceVisibility.PRIVATE
+ }
+
+ /**
+ * Returns a boolean to denote whether a cache file is visible to all(public)
+ * or not
+ * @param conf
+ * @param uri
+ * @param statCache
+ * @return true if the path in the uri is visible to all, false otherwise
+ */
+ def isPublic(conf: Configuration, uri: URI, statCache: Map[URI, FileStatus]): Boolean = {
+ val fs = FileSystem.get(uri, conf)
+ val current = new Path(uri.getPath())
+ //the leaf level file should be readable by others
+ if (!checkPermissionOfOther(fs, current, FsAction.READ, statCache)) {
+ return false
+ }
+ return ancestorsHaveExecutePermissions(fs, current.getParent(), statCache)
+ }
+
+ /**
+ * Returns true if all ancestors of the specified path have the 'execute'
+ * permission set for all users (i.e. that other users can traverse
+ * the directory heirarchy to the given path)
+ * @param fs
+ * @param path
+ * @param statCache
+ * @return true if all ancestors have the 'execute' permission set for all users
+ */
+ def ancestorsHaveExecutePermissions(fs: FileSystem, path: Path,
+ statCache: Map[URI, FileStatus]): Boolean = {
+ var current = path
+ while (current != null) {
+ //the subdirs in the path should have execute permissions for others
+ if (!checkPermissionOfOther(fs, current, FsAction.EXECUTE, statCache)) {
+ return false
+ }
+ current = current.getParent()
+ }
+ return true
+ }
+
+ /**
+ * Checks for a given path whether the Other permissions on it
+ * imply the permission in the passed FsAction
+ * @param fs
+ * @param path
+ * @param action
+ * @param statCache
+ * @return true if the path in the uri is visible to all, false otherwise
+ */
+ def checkPermissionOfOther(fs: FileSystem, path: Path,
+ action: FsAction, statCache: Map[URI, FileStatus]): Boolean = {
+ val status = getFileStatus(fs, path.toUri(), statCache)
+ val perms = status.getPermission()
+ val otherAction = perms.getOtherAction()
+ if (otherAction.implies(action)) {
+ return true
+ }
+ return false
+ }
+
+ /**
+ * Checks to see if the given uri exists in the cache, if it does it
+ * returns the existing FileStatus, otherwise it stats the uri, stores
+ * it in the cache, and returns the FileStatus.
+ * @param fs
+ * @param uri
+ * @param statCache
+ * @return FileStatus
+ */
+ def getFileStatus(fs: FileSystem, uri: URI, statCache: Map[URI, FileStatus]): FileStatus = {
+ val stat = statCache.get(uri) match {
+ case Some(existstat) => existstat
+ case None =>
+ val newStat = fs.getFileStatus(new Path(uri))
+ statCache.put(uri, newStat)
+ newStat
+ }
+ return stat
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerLauncher.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerLauncher.scala
new file mode 100644
index 0000000000000000000000000000000000000000..c38f33e212fbf2e2bf60fa1dd4793012ea288f81
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerLauncher.scala
@@ -0,0 +1,223 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.Socket
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.records._
+import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.util.{ConverterUtils, Records}
+import akka.actor._
+import akka.remote.{RemoteClientShutdown, RemoteClientDisconnected, RemoteClientLifeCycleEvent}
+import akka.actor.Terminated
+import org.apache.spark.{SparkContext, Logging}
+import org.apache.spark.util.{Utils, AkkaUtils}
+import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
+import org.apache.spark.scheduler.SplitInfo
+import org.apache.hadoop.yarn.client.api.AMRMClient
+import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
+
+class WorkerLauncher(args: ApplicationMasterArguments, conf: Configuration) extends Logging {
+
+ def this(args: ApplicationMasterArguments) = this(args, new Configuration())
+
+ private var appAttemptId: ApplicationAttemptId = _
+ private var reporterThread: Thread = _
+ private val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
+
+ private var yarnAllocator: YarnAllocationHandler = _
+ private var driverClosed:Boolean = false
+
+ private var amClient: AMRMClient[ContainerRequest] = _
+
+ val actorSystem : ActorSystem = AkkaUtils.createActorSystem("sparkYarnAM", Utils.localHostName, 0)._1
+ var actor: ActorRef = _
+
+ // This actor just working as a monitor to watch on Driver Actor.
+ class MonitorActor(driverUrl: String) extends Actor {
+
+ var driver: ActorRef = null
+
+ override def preStart() {
+ logInfo("Listen to driver: " + driverUrl)
+ driver = context.actorFor(driverUrl)
+ context.system.eventStream.subscribe(self, classOf[RemoteClientLifeCycleEvent])
+ context.watch(driver) // Doesn't work with remote actors, but useful for testing
+ }
+
+ override def receive = {
+ case Terminated(_) | RemoteClientDisconnected(_, _) | RemoteClientShutdown(_, _) =>
+ logInfo("Driver terminated or disconnected! Shutting down.")
+ driverClosed = true
+ }
+ }
+
+ def run() {
+
+ amClient = AMRMClient.createAMRMClient()
+ amClient.init(yarnConf)
+ amClient.start()
+
+ appAttemptId = getApplicationAttemptId()
+ registerApplicationMaster()
+
+ waitForSparkMaster()
+
+ // Allocate all containers
+ allocateWorkers()
+
+ // Launch a progress reporter thread, else app will get killed after expiration (def: 10mins) timeout
+ // ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapse.
+
+ val timeoutInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000)
+ // must be <= timeoutInterval/ 2.
+ // On other hand, also ensure that we are reasonably responsive without causing too many requests to RM.
+ // so atleast 1 minute or timeoutInterval / 10 - whichever is higher.
+ val interval = math.min(timeoutInterval / 2, math.max(timeoutInterval/ 10, 60000L))
+ reporterThread = launchReporterThread(interval)
+
+ // Wait for the reporter thread to Finish.
+ reporterThread.join()
+
+ finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
+ actorSystem.shutdown()
+
+ logInfo("Exited")
+ System.exit(0)
+ }
+
+ private def getApplicationAttemptId(): ApplicationAttemptId = {
+ val envs = System.getenv()
+ val containerIdString = envs.get(ApplicationConstants.Environment.CONTAINER_ID.name())
+ val containerId = ConverterUtils.toContainerId(containerIdString)
+ val appAttemptId = containerId.getApplicationAttemptId()
+ logInfo("ApplicationAttemptId: " + appAttemptId)
+ appAttemptId
+ }
+
+ private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
+ logInfo("Registering the ApplicationMaster")
+ // TODO:(Raymond) Find out Spark UI address and fill in here?
+ amClient.registerApplicationMaster(Utils.localHostName(), 0, "")
+ }
+
+ private def waitForSparkMaster() {
+ logInfo("Waiting for Spark driver to be reachable.")
+ var driverUp = false
+ val hostport = args.userArgs(0)
+ val (driverHost, driverPort) = Utils.parseHostPort(hostport)
+ while(!driverUp) {
+ try {
+ val socket = new Socket(driverHost, driverPort)
+ socket.close()
+ logInfo("Driver now available: %s:%s".format(driverHost, driverPort))
+ driverUp = true
+ } catch {
+ case e: Exception =>
+ logError("Failed to connect to driver at %s:%s, retrying ...".
+ format(driverHost, driverPort))
+ Thread.sleep(100)
+ }
+ }
+ System.setProperty("spark.driver.host", driverHost)
+ System.setProperty("spark.driver.port", driverPort.toString)
+
+ val driverUrl = "akka://spark@%s:%s/user/%s".format(
+ driverHost, driverPort.toString, CoarseGrainedSchedulerBackend.ACTOR_NAME)
+
+ actor = actorSystem.actorOf(Props(new MonitorActor(driverUrl)), name = "YarnAM")
+ }
+
+
+ private def allocateWorkers() {
+
+ // Fixme: should get preferredNodeLocationData from SparkContext, just fake a empty one for now.
+ val preferredNodeLocationData: scala.collection.Map[String, scala.collection.Set[SplitInfo]] =
+ scala.collection.immutable.Map()
+
+ yarnAllocator = YarnAllocationHandler.newAllocator(
+ yarnConf,
+ amClient,
+ appAttemptId,
+ args,
+ preferredNodeLocationData)
+
+ logInfo("Allocating " + args.numWorkers + " workers.")
+ // Wait until all containers have finished
+ // TODO: This is a bit ugly. Can we make it nicer?
+ // TODO: Handle container failure
+
+ yarnAllocator.addResourceRequests(args.numWorkers)
+ while(yarnAllocator.getNumWorkersRunning < args.numWorkers) {
+ yarnAllocator.allocateResources()
+ Thread.sleep(100)
+ }
+
+ logInfo("All workers have launched.")
+
+ }
+
+ // TODO: We might want to extend this to allocate more containers in case they die !
+ private def launchReporterThread(_sleepTime: Long): Thread = {
+ val sleepTime = if (_sleepTime <= 0 ) 0 else _sleepTime
+
+ val t = new Thread {
+ override def run() {
+ while (!driverClosed) {
+ val missingWorkerCount = args.numWorkers - yarnAllocator.getNumWorkersRunning -
+ yarnAllocator.getNumPendingAllocate
+ if (missingWorkerCount > 0) {
+ logInfo("Allocating %d containers to make up for (potentially) lost containers".
+ format(missingWorkerCount))
+ yarnAllocator.addResourceRequests(missingWorkerCount)
+ }
+ sendProgress()
+ Thread.sleep(sleepTime)
+ }
+ }
+ }
+ // setting to daemon status, though this is usually not a good idea.
+ t.setDaemon(true)
+ t.start()
+ logInfo("Started progress reporter thread - sleep time : " + sleepTime)
+ t
+ }
+
+ private def sendProgress() {
+ logDebug("Sending progress")
+ // simulated with an allocate request with no nodes requested ...
+ yarnAllocator.allocateResources()
+ }
+
+ def finishApplicationMaster(status: FinalApplicationStatus) {
+ logInfo("finish ApplicationMaster with " + status)
+ amClient.unregisterApplicationMaster(status, "" /* appMessage */, "" /* appTrackingUrl */)
+ }
+
+}
+
+
+object WorkerLauncher {
+ def main(argStrings: Array[String]) {
+ val args = new ApplicationMasterArguments(argStrings)
+ new WorkerLauncher(args).run()
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
new file mode 100644
index 0000000000000000000000000000000000000000..9f5523c4b97a8811c14a19f9e34c6cd1e32028e7
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
@@ -0,0 +1,209 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.URI
+import java.nio.ByteBuffer
+import java.security.PrivilegedExceptionAction
+
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.io.DataOutputBuffer
+import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
+import org.apache.hadoop.yarn.api.records._
+import org.apache.hadoop.yarn.api.records.impl.pb.ProtoUtils
+import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.client.api.NMClient
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.ipc.YarnRPC
+import org.apache.hadoop.yarn.util.{Apps, ConverterUtils, Records}
+
+import org.apache.spark.Logging
+
+
+class WorkerRunnable(
+ container: Container,
+ conf: Configuration,
+ masterAddress: String,
+ slaveId: String,
+ hostname: String,
+ workerMemory: Int,
+ workerCores: Int)
+ extends Runnable with Logging {
+
+ var rpc: YarnRPC = YarnRPC.create(conf)
+ var nmClient: NMClient = _
+ val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
+
+ def run = {
+ logInfo("Starting Worker Container")
+ nmClient = NMClient.createNMClient()
+ nmClient.init(yarnConf)
+ nmClient.start()
+ startContainer
+ }
+
+ def startContainer = {
+ logInfo("Setting up ContainerLaunchContext")
+
+ val ctx = Records.newRecord(classOf[ContainerLaunchContext])
+ .asInstanceOf[ContainerLaunchContext]
+
+ val localResources = prepareLocalResources
+ ctx.setLocalResources(localResources)
+
+ val env = prepareEnvironment
+ ctx.setEnvironment(env)
+
+ // Extra options for the JVM
+ var JAVA_OPTS = ""
+ // Set the JVM memory
+ val workerMemoryString = workerMemory + "m"
+ JAVA_OPTS += "-Xms" + workerMemoryString + " -Xmx" + workerMemoryString + " "
+ if (env.isDefinedAt("SPARK_JAVA_OPTS")) {
+ JAVA_OPTS += env("SPARK_JAVA_OPTS") + " "
+ }
+
+ JAVA_OPTS += " -Djava.io.tmpdir=" +
+ new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " "
+
+ // Commenting it out for now - so that people can refer to the properties if required. Remove
+ // it once cpuset version is pushed out.
+ // The context is, default gc for server class machines end up using all cores to do gc - hence
+ // if there are multiple containers in same node, spark gc effects all other containers
+ // performance (which can also be other spark containers)
+ // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in
+ // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset
+ // of cores on a node.
+/*
+ else {
+ // If no java_opts specified, default to using -XX:+CMSIncrementalMode
+ // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont
+ // want to mess with it.
+ // In our expts, using (default) throughput collector has severe perf ramnifications in
+ // multi-tennent machines
+ // The options are based on
+ // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline
+ JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
+ JAVA_OPTS += " -XX:+CMSIncrementalMode "
+ JAVA_OPTS += " -XX:+CMSIncrementalPacing "
+ JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 "
+ JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 "
+ }
+*/
+
+ val credentials = UserGroupInformation.getCurrentUser().getCredentials()
+ val dob = new DataOutputBuffer()
+ credentials.writeTokenStorageToStream(dob)
+ ctx.setTokens(ByteBuffer.wrap(dob.getData()))
+
+ var javaCommand = "java"
+ val javaHome = System.getenv("JAVA_HOME")
+ if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) {
+ javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
+ }
+
+ val commands = List[String](javaCommand +
+ " -server " +
+ // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling.
+ // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in
+ // an inconsistent state.
+ // TODO: If the OOM is not recoverable by rescheduling it on different node, then do
+ // 'something' to fail job ... akin to blacklisting trackers in mapred ?
+ " -XX:OnOutOfMemoryError='kill %p' " +
+ JAVA_OPTS +
+ " org.apache.spark.executor.CoarseGrainedExecutorBackend " +
+ masterAddress + " " +
+ slaveId + " " +
+ hostname + " " +
+ workerCores +
+ " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" +
+ " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
+ logInfo("Setting up worker with commands: " + commands)
+ ctx.setCommands(commands)
+
+ // Send the start request to the ContainerManager
+ nmClient.startContainer(container, ctx)
+ }
+
+ private def setupDistributedCache(
+ file: String,
+ rtype: LocalResourceType,
+ localResources: HashMap[String, LocalResource],
+ timestamp: String,
+ size: String,
+ vis: String) = {
+ val uri = new URI(file)
+ val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource]
+ amJarRsrc.setType(rtype)
+ amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis))
+ amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri))
+ amJarRsrc.setTimestamp(timestamp.toLong)
+ amJarRsrc.setSize(size.toLong)
+ localResources(uri.getFragment()) = amJarRsrc
+ }
+
+ def prepareLocalResources: HashMap[String, LocalResource] = {
+ logInfo("Preparing Local resources")
+ val localResources = HashMap[String, LocalResource]()
+
+ if (System.getenv("SPARK_YARN_CACHE_FILES") != null) {
+ val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',')
+ val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',')
+ val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',')
+ val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',')
+ for( i <- 0 to distFiles.length - 1) {
+ setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i),
+ fileSizes(i), visibilities(i))
+ }
+ }
+
+ if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) {
+ val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',')
+ val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',')
+ val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',')
+ val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',')
+ for( i <- 0 to distArchives.length - 1) {
+ setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources,
+ timeStamps(i), fileSizes(i), visibilities(i))
+ }
+ }
+
+ logInfo("Prepared Local resources " + localResources)
+ localResources
+ }
+
+ def prepareEnvironment: HashMap[String, String] = {
+ val env = new HashMap[String, String]()
+
+ Client.populateClasspath(yarnConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env)
+
+ // Allow users to specify some environment variables
+ Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
+
+ System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
+ env
+ }
+
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
new file mode 100644
index 0000000000000000000000000000000000000000..dba0f7640e67cc88bbe432ec12e218c6103244ff
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
@@ -0,0 +1,687 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.lang.{Boolean => JBoolean}
+import java.util.{Collections, Set => JSet}
+import java.util.concurrent.{CopyOnWriteArrayList, ConcurrentHashMap}
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection
+import scala.collection.JavaConversions._
+import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet}
+
+import org.apache.spark.Logging
+import org.apache.spark.scheduler.SplitInfo
+import org.apache.spark.scheduler.cluster.{ClusterScheduler, CoarseGrainedSchedulerBackend}
+import org.apache.spark.util.Utils
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.yarn.api.ApplicationMasterProtocol
+import org.apache.hadoop.yarn.api.records.ApplicationAttemptId
+import org.apache.hadoop.yarn.api.records.{Container, ContainerId, ContainerStatus}
+import org.apache.hadoop.yarn.api.records.{Priority, Resource, ResourceRequest}
+import org.apache.hadoop.yarn.api.protocolrecords.{AllocateRequest, AllocateResponse}
+import org.apache.hadoop.yarn.client.api.AMRMClient
+import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
+import org.apache.hadoop.yarn.util.{RackResolver, Records}
+
+
+object AllocationType extends Enumeration ("HOST", "RACK", "ANY") {
+ type AllocationType = Value
+ val HOST, RACK, ANY = Value
+}
+
+// TODO:
+// Too many params.
+// Needs to be mt-safe
+// Need to refactor this to make it 'cleaner' ... right now, all computation is reactive - should
+// make it more proactive and decoupled.
+
+// Note that right now, we assume all node asks as uniform in terms of capabilities and priority
+// Refer to http://developer.yahoo.com/blogs/hadoop/posts/2011/03/mapreduce-nextgen-scheduler/ for
+// more info on how we are requesting for containers.
+private[yarn] class YarnAllocationHandler(
+ val conf: Configuration,
+ val amClient: AMRMClient[ContainerRequest],
+ val appAttemptId: ApplicationAttemptId,
+ val maxWorkers: Int,
+ val workerMemory: Int,
+ val workerCores: Int,
+ val preferredHostToCount: Map[String, Int],
+ val preferredRackToCount: Map[String, Int])
+ extends Logging {
+ // These three are locked on allocatedHostToContainersMap. Complementary data structures
+ // allocatedHostToContainersMap : containers which are running : host, Set<containerid>
+ // allocatedContainerToHostMap: container to host mapping.
+ private val allocatedHostToContainersMap =
+ new HashMap[String, collection.mutable.Set[ContainerId]]()
+
+ private val allocatedContainerToHostMap = new HashMap[ContainerId, String]()
+
+ // allocatedRackCount is populated ONLY if allocation happens (or decremented if this is an
+ // allocated node)
+ // As with the two data structures above, tightly coupled with them, and to be locked on
+ // allocatedHostToContainersMap
+ private val allocatedRackCount = new HashMap[String, Int]()
+
+ // Containers which have been released.
+ private val releasedContainerList = new CopyOnWriteArrayList[ContainerId]()
+ // Containers to be released in next request to RM
+ private val pendingReleaseContainers = new ConcurrentHashMap[ContainerId, Boolean]
+
+ // Number of container requests that have been sent to, but not yet allocated by the
+ // ApplicationMaster.
+ private val numPendingAllocate = new AtomicInteger()
+ private val numWorkersRunning = new AtomicInteger()
+ // Used to generate a unique id per worker
+ private val workerIdCounter = new AtomicInteger()
+ private val lastResponseId = new AtomicInteger()
+ private val numWorkersFailed = new AtomicInteger()
+
+ def getNumPendingAllocate: Int = numPendingAllocate.intValue
+
+ def getNumWorkersRunning: Int = numWorkersRunning.intValue
+
+ def getNumWorkersFailed: Int = numWorkersFailed.intValue
+
+ def isResourceConstraintSatisfied(container: Container): Boolean = {
+ container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+ }
+
+ def releaseContainer(container: Container) {
+ val containerId = container.getId
+ pendingReleaseContainers.put(containerId, true)
+ amClient.releaseAssignedContainer(containerId)
+ }
+
+ def allocateResources() {
+ // We have already set the container request. Poll the ResourceManager for a response.
+ // This doubles as a heartbeat if there are no pending container requests.
+ val progressIndicator = 0.1f
+ val allocateResponse = amClient.allocate(progressIndicator)
+
+ val allocatedContainers = allocateResponse.getAllocatedContainers()
+ if (allocatedContainers.size > 0) {
+ var numPendingAllocateNow = numPendingAllocate.addAndGet(-1 * allocatedContainers.size)
+
+ if (numPendingAllocateNow < 0) {
+ numPendingAllocateNow = numPendingAllocate.addAndGet(-1 * numPendingAllocateNow)
+ }
+
+ logDebug("""
+ Allocated containers: %d
+ Current worker count: %d
+ Containers released: %s
+ Containers to-be-released: %s
+ Cluster resources: %s
+ """.format(
+ allocatedContainers.size,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers,
+ allocateResponse.getAvailableResources))
+
+ val hostToContainers = new HashMap[String, ArrayBuffer[Container]]()
+
+ for (container <- allocatedContainers) {
+ if (isResourceConstraintSatisfied(container)) {
+ // Add the accepted `container` to the host's list of already accepted,
+ // allocated containers
+ val host = container.getNodeId.getHost
+ val containersForHost = hostToContainers.getOrElseUpdate(host,
+ new ArrayBuffer[Container]())
+ containersForHost += container
+ } else {
+ // Release container, since it doesn't satisfy resource constraints.
+ releaseContainer(container)
+ }
+ }
+
+ // Find the appropriate containers to use.
+ // TODO: Cleanup this group-by...
+ val dataLocalContainers = new HashMap[String, ArrayBuffer[Container]]()
+ val rackLocalContainers = new HashMap[String, ArrayBuffer[Container]]()
+ val offRackContainers = new HashMap[String, ArrayBuffer[Container]]()
+
+ for (candidateHost <- hostToContainers.keySet) {
+ val maxExpectedHostCount = preferredHostToCount.getOrElse(candidateHost, 0)
+ val requiredHostCount = maxExpectedHostCount - allocatedContainersOnHost(candidateHost)
+
+ val remainingContainersOpt = hostToContainers.get(candidateHost)
+ assert(remainingContainersOpt.isDefined)
+ var remainingContainers = remainingContainersOpt.get
+
+ if (requiredHostCount >= remainingContainers.size) {
+ // Since we have <= required containers, add all remaining containers to
+ // `dataLocalContainers`.
+ dataLocalContainers.put(candidateHost, remainingContainers)
+ // There are no more free containers remaining.
+ remainingContainers = null
+ } else if (requiredHostCount > 0) {
+ // Container list has more containers than we need for data locality.
+ // Split the list into two: one based on the data local container count,
+ // (`remainingContainers.size` - `requiredHostCount`), and the other to hold remaining
+ // containers.
+ val (dataLocal, remaining) = remainingContainers.splitAt(
+ remainingContainers.size - requiredHostCount)
+ dataLocalContainers.put(candidateHost, dataLocal)
+
+ // Invariant: remainingContainers == remaining
+
+ // YARN has a nasty habit of allocating a ton of containers on a host - discourage this.
+ // Add each container in `remaining` to list of containers to release. If we have an
+ // insufficient number of containers, then the next allocation cycle will reallocate
+ // (but won't treat it as data local).
+ // TODO(harvey): Rephrase this comment some more.
+ for (container <- remaining) releaseContainer(container)
+ remainingContainers = null
+ }
+
+ // For rack local containers
+ if (remainingContainers != null) {
+ val rack = YarnAllocationHandler.lookupRack(conf, candidateHost)
+ if (rack != null) {
+ val maxExpectedRackCount = preferredRackToCount.getOrElse(rack, 0)
+ val requiredRackCount = maxExpectedRackCount - allocatedContainersOnRack(rack) -
+ rackLocalContainers.getOrElse(rack, List()).size
+
+ if (requiredRackCount >= remainingContainers.size) {
+ // Add all remaining containers to to `dataLocalContainers`.
+ dataLocalContainers.put(rack, remainingContainers)
+ remainingContainers = null
+ } else if (requiredRackCount > 0) {
+ // Container list has more containers that we need for data locality.
+ // Split the list into two: one based on the data local container count,
+ // (`remainingContainers.size` - `requiredHostCount`), and the other to hold remaining
+ // containers.
+ val (rackLocal, remaining) = remainingContainers.splitAt(
+ remainingContainers.size - requiredRackCount)
+ val existingRackLocal = rackLocalContainers.getOrElseUpdate(rack,
+ new ArrayBuffer[Container]())
+
+ existingRackLocal ++= rackLocal
+
+ remainingContainers = remaining
+ }
+ }
+ }
+
+ if (remainingContainers != null) {
+ // Not all containers have been consumed - add them to the list of off-rack containers.
+ offRackContainers.put(candidateHost, remainingContainers)
+ }
+ }
+
+ // Now that we have split the containers into various groups, go through them in order:
+ // first host-local, then rack-local, and finally off-rack.
+ // Note that the list we create below tries to ensure that not all containers end up within
+ // a host if there is a sufficiently large number of hosts/containers.
+ val allocatedContainersToProcess = new ArrayBuffer[Container](allocatedContainers.size)
+ allocatedContainersToProcess ++= ClusterScheduler.prioritizeContainers(dataLocalContainers)
+ allocatedContainersToProcess ++= ClusterScheduler.prioritizeContainers(rackLocalContainers)
+ allocatedContainersToProcess ++= ClusterScheduler.prioritizeContainers(offRackContainers)
+
+ // Run each of the allocated containers.
+ for (container <- allocatedContainersToProcess) {
+ val numWorkersRunningNow = numWorkersRunning.incrementAndGet()
+ val workerHostname = container.getNodeId.getHost
+ val containerId = container.getId
+
+ val workerMemoryOverhead = (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+ assert(container.getResource.getMemory >= workerMemoryOverhead)
+
+ if (numWorkersRunningNow > maxWorkers) {
+ logInfo("""Ignoring container %s at host %s, since we already have the required number of
+ containers for it.""".format(containerId, workerHostname))
+ releaseContainer(container)
+ numWorkersRunning.decrementAndGet()
+ } else {
+ val workerId = workerIdCounter.incrementAndGet().toString
+ val driverUrl = "akka://spark@%s:%s/user/%s".format(
+ System.getProperty("spark.driver.host"),
+ System.getProperty("spark.driver.port"),
+ CoarseGrainedSchedulerBackend.ACTOR_NAME)
+
+ logInfo("Launching container %s for on host %s".format(containerId, workerHostname))
+
+ // To be safe, remove the container from `pendingReleaseContainers`.
+ pendingReleaseContainers.remove(containerId)
+
+ val rack = YarnAllocationHandler.lookupRack(conf, workerHostname)
+ allocatedHostToContainersMap.synchronized {
+ val containerSet = allocatedHostToContainersMap.getOrElseUpdate(workerHostname,
+ new HashSet[ContainerId]())
+
+ containerSet += containerId
+ allocatedContainerToHostMap.put(containerId, workerHostname)
+
+ if (rack != null) {
+ allocatedRackCount.put(rack, allocatedRackCount.getOrElse(rack, 0) + 1)
+ }
+ }
+ logInfo("Launching WorkerRunnable. driverUrl: %s, workerHostname: %s".format(driverUrl, workerHostname))
+ val workerRunnable = new WorkerRunnable(
+ container,
+ conf,
+ driverUrl,
+ workerId,
+ workerHostname,
+ workerMemory,
+ workerCores)
+ new Thread(workerRunnable).start()
+ }
+ }
+ logDebug("""
+ Finished allocating %s containers (from %s originally).
+ Current number of workers running: %d,
+ releasedContainerList: %s,
+ pendingReleaseContainers: %s
+ """.format(
+ allocatedContainersToProcess,
+ allocatedContainers,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers))
+ }
+
+ val completedContainers = allocateResponse.getCompletedContainersStatuses()
+ if (completedContainers.size > 0) {
+ logDebug("Completed %d containers".format(completedContainers.size))
+
+ for (completedContainer <- completedContainers) {
+ val containerId = completedContainer.getContainerId
+
+ if (pendingReleaseContainers.containsKey(containerId)) {
+ // YarnAllocationHandler already marked the container for release, so remove it from
+ // `pendingReleaseContainers`.
+ pendingReleaseContainers.remove(containerId)
+ } else {
+ // Decrement the number of workers running. The next iteration of the ApplicationMaster's
+ // reporting thread will take care of allocating.
+ numWorkersRunning.decrementAndGet()
+ logInfo("Completed container %s (state: %s, exit status: %s)".format(
+ containerId,
+ completedContainer.getState,
+ completedContainer.getExitStatus()))
+ // Hadoop 2.2.X added a ContainerExitStatus we should switch to use
+ // there are some exit status' we shouldn't necessarily count against us, but for
+ // now I think its ok as none of the containers are expected to exit
+ if (completedContainer.getExitStatus() != 0) {
+ logInfo("Container marked as failed: " + containerId)
+ numWorkersFailed.incrementAndGet()
+ }
+ }
+
+ allocatedHostToContainersMap.synchronized {
+ if (allocatedContainerToHostMap.containsKey(containerId)) {
+ val hostOpt = allocatedContainerToHostMap.get(containerId)
+ assert(hostOpt.isDefined)
+ val host = hostOpt.get
+
+ val containerSetOpt = allocatedHostToContainersMap.get(host)
+ assert(containerSetOpt.isDefined)
+ val containerSet = containerSetOpt.get
+
+ containerSet.remove(containerId)
+ if (containerSet.isEmpty) {
+ allocatedHostToContainersMap.remove(host)
+ } else {
+ allocatedHostToContainersMap.update(host, containerSet)
+ }
+
+ allocatedContainerToHostMap.remove(containerId)
+
+ // TODO: Move this part outside the synchronized block?
+ val rack = YarnAllocationHandler.lookupRack(conf, host)
+ if (rack != null) {
+ val rackCount = allocatedRackCount.getOrElse(rack, 0) - 1
+ if (rackCount > 0) {
+ allocatedRackCount.put(rack, rackCount)
+ } else {
+ allocatedRackCount.remove(rack)
+ }
+ }
+ }
+ }
+ }
+ logDebug("""
+ Finished processing %d completed containers.
+ Current number of workers running: %d,
+ releasedContainerList: %s,
+ pendingReleaseContainers: %s
+ """.format(
+ completedContainers.size,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers))
+ }
+ }
+
+ def createRackResourceRequests(
+ hostContainers: ArrayBuffer[ContainerRequest]
+ ): ArrayBuffer[ContainerRequest] = {
+ // Generate modified racks and new set of hosts under it before issuing requests.
+ val rackToCounts = new HashMap[String, Int]()
+
+ for (container <- hostContainers) {
+ val candidateHost = container.getNodes.last
+ assert(YarnAllocationHandler.ANY_HOST != candidateHost)
+
+ val rack = YarnAllocationHandler.lookupRack(conf, candidateHost)
+ if (rack != null) {
+ var count = rackToCounts.getOrElse(rack, 0)
+ count += 1
+ rackToCounts.put(rack, count)
+ }
+ }
+
+ val requestedContainers = new ArrayBuffer[ContainerRequest](rackToCounts.size)
+ for ((rack, count) <- rackToCounts) {
+ requestedContainers ++= createResourceRequests(
+ AllocationType.RACK,
+ rack,
+ count,
+ YarnAllocationHandler.PRIORITY)
+ }
+
+ requestedContainers
+ }
+
+ def allocatedContainersOnHost(host: String): Int = {
+ var retval = 0
+ allocatedHostToContainersMap.synchronized {
+ retval = allocatedHostToContainersMap.getOrElse(host, Set()).size
+ }
+ retval
+ }
+
+ def allocatedContainersOnRack(rack: String): Int = {
+ var retval = 0
+ allocatedHostToContainersMap.synchronized {
+ retval = allocatedRackCount.getOrElse(rack, 0)
+ }
+ retval
+ }
+
+ def addResourceRequests(numWorkers: Int) {
+ val containerRequests: List[ContainerRequest] =
+ if (numWorkers <= 0 || preferredHostToCount.isEmpty) {
+ logDebug("numWorkers: " + numWorkers + ", host preferences: " +
+ preferredHostToCount.isEmpty)
+ createResourceRequests(
+ AllocationType.ANY,
+ resource = null,
+ numWorkers,
+ YarnAllocationHandler.PRIORITY).toList
+ } else {
+ // Request for all hosts in preferred nodes and for numWorkers -
+ // candidates.size, request by default allocation policy.
+ val hostContainerRequests = new ArrayBuffer[ContainerRequest](preferredHostToCount.size)
+ for ((candidateHost, candidateCount) <- preferredHostToCount) {
+ val requiredCount = candidateCount - allocatedContainersOnHost(candidateHost)
+
+ if (requiredCount > 0) {
+ hostContainerRequests ++= createResourceRequests(
+ AllocationType.HOST,
+ candidateHost,
+ requiredCount,
+ YarnAllocationHandler.PRIORITY)
+ }
+ }
+ val rackContainerRequests: List[ContainerRequest] = createRackResourceRequests(
+ hostContainerRequests).toList
+
+ val anyContainerRequests = createResourceRequests(
+ AllocationType.ANY,
+ resource = null,
+ numWorkers,
+ YarnAllocationHandler.PRIORITY)
+
+ val containerRequestBuffer = new ArrayBuffer[ContainerRequest](
+ hostContainerRequests.size + rackContainerRequests.size() + anyContainerRequests.size)
+
+ containerRequestBuffer ++= hostContainerRequests
+ containerRequestBuffer ++= rackContainerRequests
+ containerRequestBuffer ++= anyContainerRequests
+ containerRequestBuffer.toList
+ }
+
+ for (request <- containerRequests) {
+ amClient.addContainerRequest(request)
+ }
+
+ if (numWorkers > 0) {
+ numPendingAllocate.addAndGet(numWorkers)
+ logInfo("Will Allocate %d worker containers, each with %d memory".format(
+ numWorkers,
+ (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)))
+ } else {
+ logDebug("Empty allocation request ...")
+ }
+
+ for (request <- containerRequests) {
+ val nodes = request.getNodes
+ var hostStr = if (nodes == null || nodes.isEmpty) {
+ "Any"
+ } else {
+ nodes.last
+ }
+ logInfo("Container request (host: %s, priority: %s, capability: %s".format(
+ hostStr,
+ request.getPriority().getPriority,
+ request.getCapability))
+ }
+ }
+
+ private def createResourceRequests(
+ requestType: AllocationType.AllocationType,
+ resource: String,
+ numWorkers: Int,
+ priority: Int
+ ): ArrayBuffer[ContainerRequest] = {
+
+ // If hostname is specified, then we need at least two requests - node local and rack local.
+ // There must be a third request, which is ANY. That will be specially handled.
+ requestType match {
+ case AllocationType.HOST => {
+ assert(YarnAllocationHandler.ANY_HOST != resource)
+ val hostname = resource
+ val nodeLocal = constructContainerRequests(
+ Array(hostname),
+ racks = null,
+ numWorkers,
+ priority)
+
+ // Add `hostname` to the global (singleton) host->rack mapping in YarnAllocationHandler.
+ YarnAllocationHandler.populateRackInfo(conf, hostname)
+ nodeLocal
+ }
+ case AllocationType.RACK => {
+ val rack = resource
+ constructContainerRequests(hosts = null, Array(rack), numWorkers, priority)
+ }
+ case AllocationType.ANY => constructContainerRequests(
+ hosts = null, racks = null, numWorkers, priority)
+ case _ => throw new IllegalArgumentException(
+ "Unexpected/unsupported request type: " + requestType)
+ }
+ }
+
+ private def constructContainerRequests(
+ hosts: Array[String],
+ racks: Array[String],
+ numWorkers: Int,
+ priority: Int
+ ): ArrayBuffer[ContainerRequest] = {
+
+ val memoryResource = Records.newRecord(classOf[Resource])
+ memoryResource.setMemory(workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+
+ val prioritySetting = Records.newRecord(classOf[Priority])
+ prioritySetting.setPriority(priority)
+
+ val requests = new ArrayBuffer[ContainerRequest]()
+ for (i <- 0 until numWorkers) {
+ requests += new ContainerRequest(memoryResource, hosts, racks, prioritySetting)
+ }
+ requests
+ }
+}
+
+object YarnAllocationHandler {
+
+ val ANY_HOST = "*"
+ // All requests are issued with same priority : we do not (yet) have any distinction between
+ // request types (like map/reduce in hadoop for example)
+ val PRIORITY = 1
+
+ // Additional memory overhead - in mb.
+ val MEMORY_OVERHEAD = 384
+
+ // Host to rack map - saved from allocation requests. We are expecting this not to change.
+ // Note that it is possible for this to change : and ResurceManager will indicate that to us via
+ // update response to allocate. But we are punting on handling that for now.
+ private val hostToRack = new ConcurrentHashMap[String, String]()
+ private val rackToHostSet = new ConcurrentHashMap[String, JSet[String]]()
+
+
+ def newAllocator(
+ conf: Configuration,
+ amClient: AMRMClient[ContainerRequest],
+ appAttemptId: ApplicationAttemptId,
+ args: ApplicationMasterArguments
+ ): YarnAllocationHandler = {
+ new YarnAllocationHandler(
+ conf,
+ amClient,
+ appAttemptId,
+ args.numWorkers,
+ args.workerMemory,
+ args.workerCores,
+ Map[String, Int](),
+ Map[String, Int]())
+ }
+
+ def newAllocator(
+ conf: Configuration,
+ amClient: AMRMClient[ContainerRequest],
+ appAttemptId: ApplicationAttemptId,
+ args: ApplicationMasterArguments,
+ map: collection.Map[String,
+ collection.Set[SplitInfo]]
+ ): YarnAllocationHandler = {
+ val (hostToSplitCount, rackToSplitCount) = generateNodeToWeight(conf, map)
+ new YarnAllocationHandler(
+ conf,
+ amClient,
+ appAttemptId,
+ args.numWorkers,
+ args.workerMemory,
+ args.workerCores,
+ hostToSplitCount,
+ rackToSplitCount)
+ }
+
+ def newAllocator(
+ conf: Configuration,
+ amClient: AMRMClient[ContainerRequest],
+ appAttemptId: ApplicationAttemptId,
+ maxWorkers: Int,
+ workerMemory: Int,
+ workerCores: Int,
+ map: collection.Map[String, collection.Set[SplitInfo]]
+ ): YarnAllocationHandler = {
+ val (hostToCount, rackToCount) = generateNodeToWeight(conf, map)
+ new YarnAllocationHandler(
+ conf,
+ amClient,
+ appAttemptId,
+ maxWorkers,
+ workerMemory,
+ workerCores,
+ hostToCount,
+ rackToCount)
+ }
+
+ // A simple method to copy the split info map.
+ private def generateNodeToWeight(
+ conf: Configuration,
+ input: collection.Map[String, collection.Set[SplitInfo]]
+ ): (Map[String, Int], Map[String, Int]) = {
+
+ if (input == null) {
+ return (Map[String, Int](), Map[String, Int]())
+ }
+
+ val hostToCount = new HashMap[String, Int]
+ val rackToCount = new HashMap[String, Int]
+
+ for ((host, splits) <- input) {
+ val hostCount = hostToCount.getOrElse(host, 0)
+ hostToCount.put(host, hostCount + splits.size)
+
+ val rack = lookupRack(conf, host)
+ if (rack != null){
+ val rackCount = rackToCount.getOrElse(host, 0)
+ rackToCount.put(host, rackCount + splits.size)
+ }
+ }
+
+ (hostToCount.toMap, rackToCount.toMap)
+ }
+
+ def lookupRack(conf: Configuration, host: String): String = {
+ if (!hostToRack.contains(host)) {
+ populateRackInfo(conf, host)
+ }
+ hostToRack.get(host)
+ }
+
+ def fetchCachedHostsForRack(rack: String): Option[Set[String]] = {
+ Option(rackToHostSet.get(rack)).map { set =>
+ val convertedSet: collection.mutable.Set[String] = set
+ // TODO: Better way to get a Set[String] from JSet.
+ convertedSet.toSet
+ }
+ }
+
+ def populateRackInfo(conf: Configuration, hostname: String) {
+ Utils.checkHost(hostname)
+
+ if (!hostToRack.containsKey(hostname)) {
+ // If there are repeated failures to resolve, all to an ignore list.
+ val rackInfo = RackResolver.resolve(conf, hostname)
+ if (rackInfo != null && rackInfo.getNetworkLocation != null) {
+ val rack = rackInfo.getNetworkLocation
+ hostToRack.put(hostname, rack)
+ if (! rackToHostSet.containsKey(rack)) {
+ rackToHostSet.putIfAbsent(rack,
+ Collections.newSetFromMap(new ConcurrentHashMap[String, JBoolean]()))
+ }
+ rackToHostSet.get(rack).add(hostname)
+
+ // TODO(harvey): Figure out what this comment means...
+ // Since RackResolver caches, we are disabling this for now ...
+ } /* else {
+ // right ? Else we will keep calling rack resolver in case we cant resolve rack info ...
+ hostToRack.put(hostname, null)
+ } */
+ }
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala
new file mode 100644
index 0000000000000000000000000000000000000000..2ba2366ead17113c764663ed934a5221f0eeb0ee
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala
@@ -0,0 +1,43 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.hadoop.mapred.JobConf
+import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.conf.Configuration
+
+/**
+ * Contains util methods to interact with Hadoop from spark.
+ */
+class YarnSparkHadoopUtil extends SparkHadoopUtil {
+
+ // Note that all params which start with SPARK are propagated all the way through, so if in yarn mode, this MUST be set to true.
+ override def isYarnMode(): Boolean = { true }
+
+ // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems
+ // Always create a new config, dont reuse yarnConf.
+ override def newConfiguration(): Configuration = new YarnConfiguration(new Configuration())
+
+ // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster
+ override def addCredentials(conf: JobConf) {
+ val jobCreds = conf.getCredentials()
+ jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientClusterScheduler.scala b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientClusterScheduler.scala
new file mode 100644
index 0000000000000000000000000000000000000000..63a0449e5a0730085554d2b8ae86067135fa8dba
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientClusterScheduler.scala
@@ -0,0 +1,47 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler.cluster
+
+import org.apache.spark._
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.deploy.yarn.YarnAllocationHandler
+import org.apache.spark.util.Utils
+
+/**
+ *
+ * This scheduler launch worker through Yarn - by call into Client to launch WorkerLauncher as AM.
+ */
+private[spark] class YarnClientClusterScheduler(sc: SparkContext, conf: Configuration) extends ClusterScheduler(sc) {
+
+ def this(sc: SparkContext) = this(sc, new Configuration())
+
+ // By default, rack is unknown
+ override def getRackForHost(hostPort: String): Option[String] = {
+ val host = Utils.parseHostPort(hostPort)._1
+ val retval = YarnAllocationHandler.lookupRack(conf, host)
+ if (retval != null) Some(retval) else None
+ }
+
+ override def postStartHook() {
+
+ // The yarn application is running, but the worker might not yet ready
+ // Wait for a few seconds for the slaves to bootstrap and register with master - best case attempt
+ Thread.sleep(2000L)
+ logInfo("YarnClientClusterScheduler.postStartHook done")
+ }
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
new file mode 100644
index 0000000000000000000000000000000000000000..b206780c7806e15c84944db05876f89c8f848040
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala
@@ -0,0 +1,109 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler.cluster
+
+import org.apache.hadoop.yarn.api.records.{ApplicationId, YarnApplicationState}
+import org.apache.spark.{SparkException, Logging, SparkContext}
+import org.apache.spark.deploy.yarn.{Client, ClientArguments}
+
+private[spark] class YarnClientSchedulerBackend(
+ scheduler: ClusterScheduler,
+ sc: SparkContext)
+ extends CoarseGrainedSchedulerBackend(scheduler, sc.env.actorSystem)
+ with Logging {
+
+ var client: Client = null
+ var appId: ApplicationId = null
+
+ override def start() {
+ super.start()
+
+ val defalutWorkerCores = "2"
+ val defalutWorkerMemory = "512m"
+ val defaultWorkerNumber = "1"
+
+ val userJar = System.getenv("SPARK_YARN_APP_JAR")
+ var workerCores = System.getenv("SPARK_WORKER_CORES")
+ var workerMemory = System.getenv("SPARK_WORKER_MEMORY")
+ var workerNumber = System.getenv("SPARK_WORKER_INSTANCES")
+
+ if (userJar == null)
+ throw new SparkException("env SPARK_YARN_APP_JAR is not set")
+
+ if (workerCores == null)
+ workerCores = defalutWorkerCores
+ if (workerMemory == null)
+ workerMemory = defalutWorkerMemory
+ if (workerNumber == null)
+ workerNumber = defaultWorkerNumber
+
+ val driverHost = System.getProperty("spark.driver.host")
+ val driverPort = System.getProperty("spark.driver.port")
+ val hostport = driverHost + ":" + driverPort
+
+ val argsArray = Array[String](
+ "--class", "notused",
+ "--jar", userJar,
+ "--args", hostport,
+ "--worker-memory", workerMemory,
+ "--worker-cores", workerCores,
+ "--num-workers", workerNumber,
+ "--master-class", "org.apache.spark.deploy.yarn.WorkerLauncher"
+ )
+
+ val args = new ClientArguments(argsArray)
+ client = new Client(args)
+ appId = client.runApp()
+ waitForApp()
+ }
+
+ def waitForApp() {
+
+ // TODO : need a better way to find out whether the workers are ready or not
+ // maybe by resource usage report?
+ while(true) {
+ val report = client.getApplicationReport(appId)
+
+ logInfo("Application report from ASM: \n" +
+ "\t appMasterRpcPort: " + report.getRpcPort() + "\n" +
+ "\t appStartTime: " + report.getStartTime() + "\n" +
+ "\t yarnAppState: " + report.getYarnApplicationState() + "\n"
+ )
+
+ // Ready to go, or already gone.
+ val state = report.getYarnApplicationState()
+ if (state == YarnApplicationState.RUNNING) {
+ return
+ } else if (state == YarnApplicationState.FINISHED ||
+ state == YarnApplicationState.FAILED ||
+ state == YarnApplicationState.KILLED) {
+ throw new SparkException("Yarn application already ended," +
+ "might be killed or not able to launch application master.")
+ }
+
+ Thread.sleep(1000)
+ }
+ }
+
+ override def stop() {
+ super.stop()
+ client.stop()
+ logInfo("Stoped")
+ }
+
+}
diff --git a/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterScheduler.scala b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterScheduler.scala
new file mode 100644
index 0000000000000000000000000000000000000000..29b3f22e13697b38bc501e2f914d8fc0a202d722
--- /dev/null
+++ b/new-yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterScheduler.scala
@@ -0,0 +1,55 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler.cluster
+
+import org.apache.spark._
+import org.apache.spark.deploy.yarn.{ApplicationMaster, YarnAllocationHandler}
+import org.apache.spark.util.Utils
+import org.apache.hadoop.conf.Configuration
+
+/**
+ *
+ * This is a simple extension to ClusterScheduler - to ensure that appropriate initialization of ApplicationMaster, etc is done
+ */
+private[spark] class YarnClusterScheduler(sc: SparkContext, conf: Configuration) extends ClusterScheduler(sc) {
+
+ logInfo("Created YarnClusterScheduler")
+
+ def this(sc: SparkContext) = this(sc, new Configuration())
+
+ // Nothing else for now ... initialize application master : which needs sparkContext to determine how to allocate
+ // Note that only the first creation of SparkContext influences (and ideally, there must be only one SparkContext, right ?)
+ // Subsequent creations are ignored - since nodes are already allocated by then.
+
+
+ // By default, rack is unknown
+ override def getRackForHost(hostPort: String): Option[String] = {
+ val host = Utils.parseHostPort(hostPort)._1
+ val retval = YarnAllocationHandler.lookupRack(conf, host)
+ if (retval != null) Some(retval) else None
+ }
+
+ override def postStartHook() {
+ val sparkContextInitialized = ApplicationMaster.sparkContextInitialized(sc)
+ if (sparkContextInitialized){
+ // Wait for a few seconds for the slaves to bootstrap and register with master - best case attempt
+ Thread.sleep(3000L)
+ }
+ logInfo("YarnClusterScheduler.postStartHook done")
+ }
+}
diff --git a/new-yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManagerSuite.scala b/new-yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManagerSuite.scala
new file mode 100644
index 0000000000000000000000000000000000000000..2941356bc55f9f85ca176c3ef0d23a1a08c6a8e5
--- /dev/null
+++ b/new-yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientDistributedCacheManagerSuite.scala
@@ -0,0 +1,220 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.URI
+
+import org.scalatest.FunSuite
+import org.scalatest.mock.MockitoSugar
+import org.mockito.Mockito.when
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.FileStatus
+import org.apache.hadoop.fs.FileSystem
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.fs.permission.FsAction
+import org.apache.hadoop.yarn.api.records.LocalResource
+import org.apache.hadoop.yarn.api.records.LocalResourceVisibility
+import org.apache.hadoop.yarn.api.records.LocalResourceType
+import org.apache.hadoop.yarn.util.{Records, ConverterUtils}
+
+import scala.collection.mutable.HashMap
+import scala.collection.mutable.Map
+
+
+class ClientDistributedCacheManagerSuite extends FunSuite with MockitoSugar {
+
+ class MockClientDistributedCacheManager extends ClientDistributedCacheManager {
+ override def getVisibility(conf: Configuration, uri: URI, statCache: Map[URI, FileStatus]):
+ LocalResourceVisibility = {
+ return LocalResourceVisibility.PRIVATE
+ }
+ }
+
+ test("test getFileStatus empty") {
+ val distMgr = new ClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val uri = new URI("/tmp/testing")
+ when(fs.getFileStatus(new Path(uri))).thenReturn(new FileStatus())
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+ val stat = distMgr.getFileStatus(fs, uri, statCache)
+ assert(stat.getPath() === null)
+ }
+
+ test("test getFileStatus cached") {
+ val distMgr = new ClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val uri = new URI("/tmp/testing")
+ val realFileStatus = new FileStatus(10, false, 1, 1024, 10, 10, null, "testOwner",
+ null, new Path("/tmp/testing"))
+ when(fs.getFileStatus(new Path(uri))).thenReturn(new FileStatus())
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus](uri -> realFileStatus)
+ val stat = distMgr.getFileStatus(fs, uri, statCache)
+ assert(stat.getPath().toString() === "/tmp/testing")
+ }
+
+ test("test addResource") {
+ val distMgr = new MockClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val conf = new Configuration()
+ val destPath = new Path("file:///foo.invalid.com:8080/tmp/testing")
+ val localResources = HashMap[String, LocalResource]()
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+ when(fs.getFileStatus(destPath)).thenReturn(new FileStatus())
+
+ distMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, "link",
+ statCache, false)
+ val resource = localResources("link")
+ assert(resource.getVisibility() === LocalResourceVisibility.PRIVATE)
+ assert(ConverterUtils.getPathFromYarnURL(resource.getResource()) === destPath)
+ assert(resource.getTimestamp() === 0)
+ assert(resource.getSize() === 0)
+ assert(resource.getType() === LocalResourceType.FILE)
+
+ val env = new HashMap[String, String]()
+ distMgr.setDistFilesEnv(env)
+ assert(env("SPARK_YARN_CACHE_FILES") === "file:/foo.invalid.com:8080/tmp/testing#link")
+ assert(env("SPARK_YARN_CACHE_FILES_TIME_STAMPS") === "0")
+ assert(env("SPARK_YARN_CACHE_FILES_FILE_SIZES") === "0")
+ assert(env("SPARK_YARN_CACHE_FILES_VISIBILITIES") === LocalResourceVisibility.PRIVATE.name())
+
+ distMgr.setDistArchivesEnv(env)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES") === None)
+
+ //add another one and verify both there and order correct
+ val realFileStatus = new FileStatus(20, false, 1, 1024, 10, 30, null, "testOwner",
+ null, new Path("/tmp/testing2"))
+ val destPath2 = new Path("file:///foo.invalid.com:8080/tmp/testing2")
+ when(fs.getFileStatus(destPath2)).thenReturn(realFileStatus)
+ distMgr.addResource(fs, conf, destPath2, localResources, LocalResourceType.FILE, "link2",
+ statCache, false)
+ val resource2 = localResources("link2")
+ assert(resource2.getVisibility() === LocalResourceVisibility.PRIVATE)
+ assert(ConverterUtils.getPathFromYarnURL(resource2.getResource()) === destPath2)
+ assert(resource2.getTimestamp() === 10)
+ assert(resource2.getSize() === 20)
+ assert(resource2.getType() === LocalResourceType.FILE)
+
+ val env2 = new HashMap[String, String]()
+ distMgr.setDistFilesEnv(env2)
+ val timestamps = env2("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',')
+ val files = env2("SPARK_YARN_CACHE_FILES").split(',')
+ val sizes = env2("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',')
+ val visibilities = env2("SPARK_YARN_CACHE_FILES_VISIBILITIES") .split(',')
+ assert(files(0) === "file:/foo.invalid.com:8080/tmp/testing#link")
+ assert(timestamps(0) === "0")
+ assert(sizes(0) === "0")
+ assert(visibilities(0) === LocalResourceVisibility.PRIVATE.name())
+
+ assert(files(1) === "file:/foo.invalid.com:8080/tmp/testing2#link2")
+ assert(timestamps(1) === "10")
+ assert(sizes(1) === "20")
+ assert(visibilities(1) === LocalResourceVisibility.PRIVATE.name())
+ }
+
+ test("test addResource link null") {
+ val distMgr = new MockClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val conf = new Configuration()
+ val destPath = new Path("file:///foo.invalid.com:8080/tmp/testing")
+ val localResources = HashMap[String, LocalResource]()
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+ when(fs.getFileStatus(destPath)).thenReturn(new FileStatus())
+
+ intercept[Exception] {
+ distMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE, null,
+ statCache, false)
+ }
+ assert(localResources.get("link") === None)
+ assert(localResources.size === 0)
+ }
+
+ test("test addResource appmaster only") {
+ val distMgr = new MockClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val conf = new Configuration()
+ val destPath = new Path("file:///foo.invalid.com:8080/tmp/testing")
+ val localResources = HashMap[String, LocalResource]()
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+ val realFileStatus = new FileStatus(20, false, 1, 1024, 10, 30, null, "testOwner",
+ null, new Path("/tmp/testing"))
+ when(fs.getFileStatus(destPath)).thenReturn(realFileStatus)
+
+ distMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE, "link",
+ statCache, true)
+ val resource = localResources("link")
+ assert(resource.getVisibility() === LocalResourceVisibility.PRIVATE)
+ assert(ConverterUtils.getPathFromYarnURL(resource.getResource()) === destPath)
+ assert(resource.getTimestamp() === 10)
+ assert(resource.getSize() === 20)
+ assert(resource.getType() === LocalResourceType.ARCHIVE)
+
+ val env = new HashMap[String, String]()
+ distMgr.setDistFilesEnv(env)
+ assert(env.get("SPARK_YARN_CACHE_FILES") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_TIME_STAMPS") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_FILE_SIZES") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_VISIBILITIES") === None)
+
+ distMgr.setDistArchivesEnv(env)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES") === None)
+ assert(env.get("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES") === None)
+ }
+
+ test("test addResource archive") {
+ val distMgr = new MockClientDistributedCacheManager()
+ val fs = mock[FileSystem]
+ val conf = new Configuration()
+ val destPath = new Path("file:///foo.invalid.com:8080/tmp/testing")
+ val localResources = HashMap[String, LocalResource]()
+ val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+ val realFileStatus = new FileStatus(20, false, 1, 1024, 10, 30, null, "testOwner",
+ null, new Path("/tmp/testing"))
+ when(fs.getFileStatus(destPath)).thenReturn(realFileStatus)
+
+ distMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE, "link",
+ statCache, false)
+ val resource = localResources("link")
+ assert(resource.getVisibility() === LocalResourceVisibility.PRIVATE)
+ assert(ConverterUtils.getPathFromYarnURL(resource.getResource()) === destPath)
+ assert(resource.getTimestamp() === 10)
+ assert(resource.getSize() === 20)
+ assert(resource.getType() === LocalResourceType.ARCHIVE)
+
+ val env = new HashMap[String, String]()
+
+ distMgr.setDistArchivesEnv(env)
+ assert(env("SPARK_YARN_CACHE_ARCHIVES") === "file:/foo.invalid.com:8080/tmp/testing#link")
+ assert(env("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS") === "10")
+ assert(env("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES") === "20")
+ assert(env("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES") === LocalResourceVisibility.PRIVATE.name())
+
+ distMgr.setDistFilesEnv(env)
+ assert(env.get("SPARK_YARN_CACHE_FILES") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_TIME_STAMPS") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_FILE_SIZES") === None)
+ assert(env.get("SPARK_YARN_CACHE_FILES_VISIBILITIES") === None)
+ }
+
+
+}
diff --git a/pom.xml b/pom.xml
index 42c1e00e9d11da954ea90e26f5a48a5ff1d09db7..9348c770fb523877db19fc4dca81c63e71962840 100644
--- a/pom.xml
+++ b/pom.xml
@@ -102,7 +102,9 @@
<java.version>1.5</java.version>
<scala.version>2.9.3</scala.version>
<mesos.version>0.13.0</mesos.version>
+ <akka.group>com.typesafe.akka</akka.group>
<akka.version>2.0.5</akka.version>
+ <protobuf.version>2.4.1</protobuf.version>
<slf4j.version>1.7.2</slf4j.version>
<log4j.version>1.2.17</log4j.version>
<hadoop.version>1.0.4</hadoop.version>
@@ -245,7 +247,7 @@
<dependency>
<groupId>com.google.protobuf</groupId>
<artifactId>protobuf-java</artifactId>
- <version>2.4.1</version>
+ <version>${protobuf.version}</version>
</dependency>
<dependency>
<groupId>com.twitter</groupId>
@@ -258,7 +260,7 @@
<version>0.3.1</version>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-actor</artifactId>
<version>${akka.version}</version>
<exclusions>
@@ -269,7 +271,7 @@
</exclusions>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-remote</artifactId>
<version>${akka.version}</version>
<exclusions>
@@ -280,7 +282,7 @@
</exclusions>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-slf4j</artifactId>
<version>${akka.version}</version>
<exclusions>
@@ -290,6 +292,17 @@
</exclusion>
</exclusions>
</dependency>
+ <dependency>
+ <groupId>${akka.group}</groupId>
+ <artifactId>akka-zeromq</artifactId>
+ <version>${akka.version}</version>
+ <exclusions>
+ <exclusion>
+ <groupId>org.jboss.netty</groupId>
+ <artifactId>netty</artifactId>
+ </exclusion>
+ </exclusions>
+ </dependency>
<dependency>
<groupId>it.unimi.dsi</groupId>
<artifactId>fastutil</artifactId>
@@ -300,11 +313,6 @@
<artifactId>colt</artifactId>
<version>1.2.0</version>
</dependency>
- <dependency>
- <groupId>com.github.scala-incubator.io</groupId>
- <artifactId>scala-io-file_2.9.2</artifactId>
- <version>0.4.1</version>
- </dependency>
<dependency>
<groupId>org.apache.mesos</groupId>
<artifactId>mesos</artifactId>
@@ -770,6 +778,41 @@
</dependencies>
</dependencyManagement>
</profile>
+
+ <profile>
+ <id>new-yarn</id>
+ <properties>
+ <akka.group>org.spark-project</akka.group>
+ <akka.version>2.0.5-protobuf-2.5-java-1.5</akka.version>
+ <hadoop.major.version>2</hadoop.major.version>
+ <hadoop.version>2.2.0</hadoop.version>
+ <protobuf.version>2.5.0</protobuf.version>
+ </properties>
+
+ <modules>
+ <module>new-yarn</module>
+ </modules>
+
+ <repositories>
+ <repository>
+ <id>maven-root</id>
+ <name>Maven root repository</name>
+ <url>http://repo1.maven.org/maven2/</url>
+ <releases>
+ <enabled>true</enabled>
+ </releases>
+ <snapshots>
+ <enabled>false</enabled>
+ </snapshots>
+ </repository>
+ </repositories>
+
+ <dependencyManagement>
+ <dependencies>
+ </dependencies>
+ </dependencyManagement>
+ </profile>
+
<profile>
<id>repl-bin</id>
<activation>
diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala
index 819dfa29a9e02c714a5260f8a9f4560d7e27f8fe..ac87cffd9fbd434875fad4d205b5c8ecb72310dd 100644
--- a/project/SparkBuild.scala
+++ b/project/SparkBuild.scala
@@ -28,6 +28,11 @@ object SparkBuild extends Build {
// "2.0.0-mr1-cdh4.2.0" for Cloudera Hadoop. Note that these variables can be set
// through the environment variables SPARK_HADOOP_VERSION and SPARK_YARN.
val DEFAULT_HADOOP_VERSION = "1.0.4"
+
+ // Whether the Hadoop version to build against is 2.2.x, or a variant of it. This can be set
+ // through the SPARK_IS_NEW_HADOOP environment variable.
+ val DEFAULT_IS_NEW_HADOOP = false
+
val DEFAULT_YARN = false
// HBase version; set as appropriate.
@@ -55,8 +60,6 @@ object SparkBuild extends Build {
lazy val mllib = Project("mllib", file("mllib"), settings = mllibSettings) dependsOn(core)
- lazy val yarn = Project("yarn", file("yarn"), settings = yarnSettings) dependsOn(core)
-
lazy val assemblyProj = Project("assembly", file("assembly"), settings = assemblyProjSettings)
.dependsOn(core, bagel, mllib, repl, streaming) dependsOn(maybeYarn: _*)
@@ -68,14 +71,27 @@ object SparkBuild extends Build {
// Allows build configuration to be set through environment variables
lazy val hadoopVersion = scala.util.Properties.envOrElse("SPARK_HADOOP_VERSION", DEFAULT_HADOOP_VERSION)
+ lazy val isNewHadoop = scala.util.Properties.envOrNone("SPARK_IS_NEW_HADOOP") match {
+ case None => {
+ val isNewHadoopVersion = "2.[2-9]+".r.findFirstIn(hadoopVersion).isDefined
+ (isNewHadoopVersion|| DEFAULT_IS_NEW_HADOOP)
+ }
+ case Some(v) => v.toBoolean
+ }
lazy val isYarnEnabled = scala.util.Properties.envOrNone("SPARK_YARN") match {
case None => DEFAULT_YARN
case Some(v) => v.toBoolean
}
+ // Build against a protobuf-2.5 compatible Akka if Hadoop 2 is used.
+ lazy val protobufVersion = if (isNewHadoop) "2.5.0" else "2.4.1"
+ lazy val akkaVersion = if (isNewHadoop) "2.0.5-protobuf-2.5-java-1.5" else "2.0.5"
+ lazy val akkaGroup = if (isNewHadoop) "org.spark-project" else "com.typesafe.akka"
+
// Conditionally include the yarn sub-project
- lazy val maybeYarn = if(isYarnEnabled) Seq[ClasspathDependency](yarn) else Seq[ClasspathDependency]()
- lazy val maybeYarnRef = if(isYarnEnabled) Seq[ProjectReference](yarn) else Seq[ProjectReference]()
+ lazy val yarn = Project("yarn", file(if (isNewHadoop) "new-yarn" else "yarn"), settings = yarnSettings) dependsOn(core)
+ lazy val maybeYarn = if (isYarnEnabled) Seq[ClasspathDependency](yarn) else Seq[ClasspathDependency]()
+ lazy val maybeYarnRef = if (isYarnEnabled) Seq[ProjectReference](yarn) else Seq[ProjectReference]()
// Everything except assembly, tools and examples belong to packageProjects
lazy val packageProjects = Seq[ProjectReference](core, repl, bagel, streaming, mllib) ++ maybeYarnRef
@@ -211,10 +227,10 @@ object SparkBuild extends Build {
"com.ning" % "compress-lzf" % "0.8.4",
"org.xerial.snappy" % "snappy-java" % "1.0.5",
"org.ow2.asm" % "asm" % "4.0",
- "com.google.protobuf" % "protobuf-java" % "2.4.1",
- "com.typesafe.akka" % "akka-actor" % "2.0.5" excludeAll(excludeNetty),
- "com.typesafe.akka" % "akka-remote" % "2.0.5" excludeAll(excludeNetty),
- "com.typesafe.akka" % "akka-slf4j" % "2.0.5" excludeAll(excludeNetty),
+ "com.google.protobuf" % "protobuf-java" % protobufVersion,
+ akkaGroup % "akka-actor" % akkaVersion excludeAll(excludeNetty),
+ akkaGroup % "akka-remote" % akkaVersion excludeAll(excludeNetty),
+ akkaGroup % "akka-slf4j" % akkaVersion excludeAll(excludeNetty),
"it.unimi.dsi" % "fastutil" % "6.4.4",
"colt" % "colt" % "1.2.0",
"net.liftweb" % "lift-json_2.9.2" % "2.5",
@@ -290,7 +306,7 @@ object SparkBuild extends Build {
"org.eclipse.paho" % "mqtt-client" % "0.4.0",
"org.apache.flume" % "flume-ng-sdk" % "1.2.0" % "compile" excludeAll(excludeNetty, excludeSnappy),
"org.twitter4j" % "twitter4j-stream" % "3.0.3" excludeAll(excludeNetty),
- "com.typesafe.akka" % "akka-zeromq" % "2.0.5" excludeAll(excludeNetty),
+ akkaGroup % "akka-zeromq" % akkaVersion excludeAll(excludeNetty),
"org.apache.kafka" % "kafka_2.9.2" % "0.8.0-beta1"
exclude("com.sun.jdmk", "jmxtools")
exclude("com.sun.jmx", "jmxri")
diff --git a/streaming/pom.xml b/streaming/pom.xml
index 7a9ae6a97ba7ff615e3e24c76923dc941d76b8f3..40892937b8ca5f031a6844938739bc75324f29ff 100644
--- a/streaming/pom.xml
+++ b/streaming/pom.xml
@@ -110,15 +110,8 @@
<artifactId>scala-library</artifactId>
</dependency>
<dependency>
- <groupId>com.typesafe.akka</groupId>
+ <groupId>${akka.group}</groupId>
<artifactId>akka-zeromq</artifactId>
- <version>2.0.3</version>
- <exclusions>
- <exclusion>
- <groupId>org.jboss.netty</groupId>
- <artifactId>netty</artifactId>
- </exclusion>
- </exclusions>
</dependency>
<dependency>
<groupId>org.scalatest</groupId>
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
index a7baf0c36cfd4db3ab2831c073b0af0f830a834e..240ed8b32ae93b7099b7d83adb2fcbf600a444b8 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -22,9 +22,12 @@ import java.net.Socket
import java.util.concurrent.CopyOnWriteArrayList
import java.util.concurrent.atomic.{AtomicInteger, AtomicReference}
+import scala.collection.JavaConversions._
+
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FileSystem, Path}
import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.security.UserGroupInformation
import org.apache.hadoop.util.ShutdownHookManager
import org.apache.hadoop.yarn.api._
import org.apache.hadoop.yarn.api.records._
@@ -32,38 +35,38 @@ import org.apache.hadoop.yarn.api.protocolrecords._
import org.apache.hadoop.yarn.conf.YarnConfiguration
import org.apache.hadoop.yarn.ipc.YarnRPC
import org.apache.hadoop.yarn.util.{ConverterUtils, Records}
+
import org.apache.spark.{SparkContext, Logging}
import org.apache.spark.util.Utils
-import scala.collection.JavaConversions._
class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) extends Logging {
def this(args: ApplicationMasterArguments) = this(args, new Configuration())
private var rpc: YarnRPC = YarnRPC.create(conf)
- private var resourceManager: AMRMProtocol = null
- private var appAttemptId: ApplicationAttemptId = null
- private var userThread: Thread = null
+ private var resourceManager: AMRMProtocol = _
+ private var appAttemptId: ApplicationAttemptId = _
+ private var userThread: Thread = _
private val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
private val fs = FileSystem.get(yarnConf)
- private var yarnAllocator: YarnAllocationHandler = null
- private var isFinished:Boolean = false
- private var uiAddress: String = ""
+ private var yarnAllocator: YarnAllocationHandler = _
+ private var isFinished: Boolean = false
+ private var uiAddress: String = _
private val maxAppAttempts: Int = conf.getInt(YarnConfiguration.RM_AM_MAX_RETRIES,
YarnConfiguration.DEFAULT_RM_AM_MAX_RETRIES)
private var isLastAMRetry: Boolean = true
- // default to numWorkers * 2, with minimum of 3
+ // default to numWorkers * 2, with minimum of 3
private val maxNumWorkerFailures = System.getProperty("spark.yarn.max.worker.failures",
math.max(args.numWorkers * 2, 3).toString()).toInt
def run() {
- // setup the directories so things go to yarn approved directories rather
- // then user specified and /tmp
+ // Setup the directories so things go to yarn approved directories rather
+ // then user specified and /tmp.
System.setProperty("spark.local.dir", getLocalDirs())
- // use priority 30 as its higher then HDFS. Its same priority as MapReduce is using
+ // Use priority 30 as its higher then HDFS. Its same priority as MapReduce is using.
ShutdownHookManager.get().addShutdownHook(new AppMasterShutdownHook(this), 30)
appAttemptId = getApplicationAttemptId()
@@ -72,9 +75,9 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
// Workaround until hadoop moves to something which has
// https://issues.apache.org/jira/browse/HADOOP-8406 - fixed in (2.0.2-alpha but no 0.23 line)
- // ignore result
+ // ignore result.
// This does not, unfortunately, always work reliably ... but alleviates the bug a lot of times
- // Hence args.workerCores = numCore disabled above. Any better option ?
+ // Hence args.workerCores = numCore disabled above. Any better option?
// Compute number of threads for akka
//val minimumMemory = appMasterResponse.getMinimumResourceCapability().getMemory()
@@ -100,7 +103,7 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
waitForSparkContextInitialized()
- // do this after spark master is up and SparkContext is created so that we can register UI Url
+ // Do this after spark master is up and SparkContext is created so that we can register UI Url
val appMasterResponse: RegisterApplicationMasterResponse = registerApplicationMaster()
// Allocate all containers
@@ -119,12 +122,12 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
// LOCAL_DIRS => 2.X, YARN_LOCAL_DIRS => 0.23.X
val localDirs = Option(System.getenv("YARN_LOCAL_DIRS"))
.getOrElse(Option(System.getenv("LOCAL_DIRS"))
- .getOrElse(""))
+ .getOrElse(""))
if (localDirs.isEmpty()) {
throw new Exception("Yarn Local dirs can't be empty")
}
- return localDirs
+ localDirs
}
private def getApplicationAttemptId(): ApplicationAttemptId = {
@@ -133,7 +136,7 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
val containerId = ConverterUtils.toContainerId(containerIdString)
val appAttemptId = containerId.getApplicationAttemptId()
logInfo("ApplicationAttemptId: " + appAttemptId)
- return appAttemptId
+ appAttemptId
}
private def registerWithResourceManager(): AMRMProtocol = {
@@ -141,7 +144,7 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
YarnConfiguration.RM_SCHEDULER_ADDRESS,
YarnConfiguration.DEFAULT_RM_SCHEDULER_ADDRESS))
logInfo("Connecting to ResourceManager at " + rmAddress)
- return rpc.getProxy(classOf[AMRMProtocol], rmAddress, conf).asInstanceOf[AMRMProtocol]
+ rpc.getProxy(classOf[AMRMProtocol], rmAddress, conf).asInstanceOf[AMRMProtocol]
}
private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
@@ -149,12 +152,13 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
val appMasterRequest = Records.newRecord(classOf[RegisterApplicationMasterRequest])
.asInstanceOf[RegisterApplicationMasterRequest]
appMasterRequest.setApplicationAttemptId(appAttemptId)
- // Setting this to master host,port - so that the ApplicationReport at client has some sensible info.
+ // Setting this to master host,port - so that the ApplicationReport at client has some
+ // sensible info.
// Users can then monitor stderr/stdout on that node if required.
appMasterRequest.setHost(Utils.localHostName())
appMasterRequest.setRpcPort(0)
appMasterRequest.setTrackingUrl(uiAddress)
- return resourceManager.registerApplicationMaster(appMasterRequest)
+ resourceManager.registerApplicationMaster(appMasterRequest)
}
private def waitForSparkMaster() {
@@ -168,21 +172,25 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
try {
val socket = new Socket(driverHost, driverPort.toInt)
socket.close()
- logInfo("Driver now available: " + driverHost + ":" + driverPort)
+ logInfo("Driver now available: %s:%s".format(driverHost, driverPort))
driverUp = true
} catch {
- case e: Exception =>
- logWarning("Failed to connect to driver at " + driverHost + ":" + driverPort + ", retrying")
- Thread.sleep(100)
- tries = tries + 1
+ case e: Exception => {
+ logWarning("Failed to connect to driver at %s:%s, retrying ...".
+ format(driverHost, driverPort))
+ Thread.sleep(100)
+ tries = tries + 1
+ }
}
}
}
private def startUserClass(): Thread = {
logInfo("Starting the user JAR in a separate Thread")
- val mainMethod = Class.forName(args.userClass, false, Thread.currentThread.getContextClassLoader)
- .getMethod("main", classOf[Array[String]])
+ val mainMethod = Class.forName(
+ args.userClass,
+ false /* initialize */,
+ Thread.currentThread.getContextClassLoader).getMethod("main", classOf[Array[String]])
val t = new Thread {
override def run() {
var successed = false
@@ -207,7 +215,7 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
}
}
t.start()
- return t
+ t
}
// this need to happen before allocateWorkers
@@ -229,13 +237,20 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
if (null != sparkContext) {
uiAddress = sparkContext.ui.appUIAddress
- this.yarnAllocator = YarnAllocationHandler.newAllocator(yarnConf, resourceManager,
- appAttemptId, args, sparkContext.preferredNodeLocationData)
+ this.yarnAllocator = YarnAllocationHandler.newAllocator(
+ yarnConf,
+ resourceManager,
+ appAttemptId,
+ args,
+ sparkContext.preferredNodeLocationData)
} else {
- logWarning("Unable to retrieve sparkContext inspite of waiting for " + count * waitTime +
- ", numTries = " + numTries)
- this.yarnAllocator = YarnAllocationHandler.newAllocator(yarnConf, resourceManager,
- appAttemptId, args)
+ logWarning("Unable to retrieve sparkContext inspite of waiting for %d, numTries = %d".
+ format(count * waitTime, numTries))
+ this.yarnAllocator = YarnAllocationHandler.newAllocator(
+ yarnConf,
+ resourceManager,
+ appAttemptId,
+ args)
}
}
} finally {
@@ -251,36 +266,39 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
// Wait until all containers have finished
// TODO: This is a bit ugly. Can we make it nicer?
// TODO: Handle container failure
- while(yarnAllocator.getNumWorkersRunning < args.numWorkers &&
- // If user thread exists, then quit !
- userThread.isAlive) {
- if (yarnAllocator.getNumWorkersFailed >= maxNumWorkerFailures) {
- finishApplicationMaster(FinalApplicationStatus.FAILED,
- "max number of worker failures reached")
- }
- yarnAllocator.allocateContainers(math.max(args.numWorkers - yarnAllocator.getNumWorkersRunning, 0))
- ApplicationMaster.incrementAllocatorLoop(1)
- Thread.sleep(100)
+
+ // Exists the loop if the user thread exits.
+ while (yarnAllocator.getNumWorkersRunning < args.numWorkers && userThread.isAlive) {
+ if (yarnAllocator.getNumWorkersFailed >= maxNumWorkerFailures) {
+ finishApplicationMaster(FinalApplicationStatus.FAILED,
+ "max number of worker failures reached")
+ }
+ yarnAllocator.allocateContainers(
+ math.max(args.numWorkers - yarnAllocator.getNumWorkersRunning, 0))
+ ApplicationMaster.incrementAllocatorLoop(1)
+ Thread.sleep(100)
}
} finally {
- // in case of exceptions, etc - ensure that count is atleast ALLOCATOR_LOOP_WAIT_COUNT :
- // so that the loop (in ApplicationMaster.sparkContextInitialized) breaks
+ // In case of exceptions, etc - ensure that count is at least ALLOCATOR_LOOP_WAIT_COUNT,
+ // so that the loop in ApplicationMaster#sparkContextInitialized() breaks.
ApplicationMaster.incrementAllocatorLoop(ApplicationMaster.ALLOCATOR_LOOP_WAIT_COUNT)
}
logInfo("All workers have launched.")
- // Launch a progress reporter thread, else app will get killed after expiration (def: 10mins) timeout
+ // Launch a progress reporter thread, else the app will get killed after expiration
+ // (def: 10mins) timeout.
+ // TODO(harvey): Verify the timeout
if (userThread.isAlive) {
- // ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapse.
-
+ // Ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapses.
val timeoutInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000)
// we want to be reasonably responsive without causing too many requests to RM.
- val schedulerInterval =
+ val schedulerInterval =
System.getProperty("spark.yarn.scheduler.heartbeat.interval-ms", "5000").toLong
// must be <= timeoutInterval / 2.
val interval = math.min(timeoutInterval / 2, schedulerInterval)
+
launchReporterThread(interval)
}
}
@@ -292,12 +310,13 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
override def run() {
while (userThread.isAlive) {
if (yarnAllocator.getNumWorkersFailed >= maxNumWorkerFailures) {
- finishApplicationMaster(FinalApplicationStatus.FAILED,
+ finishApplicationMaster(FinalApplicationStatus.FAILED,
"max number of worker failures reached")
}
val missingWorkerCount = args.numWorkers - yarnAllocator.getNumWorkersRunning
if (missingWorkerCount > 0) {
- logInfo("Allocating " + missingWorkerCount + " containers to make up for (potentially ?) lost containers")
+ logInfo("Allocating %d containers to make up for (potentially) lost containers".
+ format(missingWorkerCount))
yarnAllocator.allocateContainers(missingWorkerCount)
}
else sendProgress()
@@ -305,16 +324,16 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
}
}
}
- // setting to daemon status, though this is usually not a good idea.
+ // Setting to daemon status, though this is usually not a good idea.
t.setDaemon(true)
t.start()
logInfo("Started progress reporter thread - sleep time : " + sleepTime)
- return t
+ t
}
private def sendProgress() {
logDebug("Sending progress")
- // simulated with an allocate request with no nodes requested ...
+ // Simulated with an allocate request with no nodes requested ...
yarnAllocator.allocateContainers(0)
}
@@ -334,7 +353,6 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
*/
def finishApplicationMaster(status: FinalApplicationStatus, diagnostics: String = "") {
-
synchronized {
if (isFinished) {
return
@@ -348,14 +366,13 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
finishReq.setAppAttemptId(appAttemptId)
finishReq.setFinishApplicationStatus(status)
finishReq.setDiagnostics(diagnostics)
- // set tracking url to empty since we don't have a history server
+ // Set tracking url to empty since we don't have a history server.
finishReq.setTrackingUrl("")
resourceManager.finishApplicationMaster(finishReq)
-
}
/**
- * clean up the staging directory.
+ * Clean up the staging directory.
*/
private def cleanupStagingDir() {
var stagingDirPath: Path = null
@@ -371,13 +388,12 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
fs.delete(stagingDirPath, true)
}
} catch {
- case e: IOException =>
- logError("Failed to cleanup staging dir " + stagingDirPath, e)
+ case ioe: IOException =>
+ logError("Failed to cleanup staging dir " + stagingDirPath, ioe)
}
}
- // The shutdown hook that runs when a signal is received AND during normal
- // close of the JVM.
+ // The shutdown hook that runs when a signal is received AND during normal close of the JVM.
class AppMasterShutdownHook(appMaster: ApplicationMaster) extends Runnable {
def run() {
@@ -387,15 +403,14 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
if (appMaster.isLastAMRetry) appMaster.cleanupStagingDir()
}
}
-
}
object ApplicationMaster {
- // number of times to wait for the allocator loop to complete.
- // each loop iteration waits for 100ms, so maximum of 3 seconds.
+ // Number of times to wait for the allocator loop to complete.
+ // Each loop iteration waits for 100ms, so maximum of 3 seconds.
// This is to ensure that we have reasonable number of containers before we start
- // TODO: Currently, task to container is computed once (TaskSetManager) - which need not be optimal as more
- // containers are available. Might need to handle this better.
+ // TODO: Currently, task to container is computed once (TaskSetManager) - which need not be
+ // optimal as more containers are available. Might need to handle this better.
private val ALLOCATOR_LOOP_WAIT_COUNT = 30
def incrementAllocatorLoop(by: Int) {
val count = yarnAllocatorLoop.getAndAdd(by)
@@ -413,7 +428,8 @@ object ApplicationMaster {
applicationMasters.add(master)
}
- val sparkContextRef: AtomicReference[SparkContext] = new AtomicReference[SparkContext](null)
+ val sparkContextRef: AtomicReference[SparkContext] =
+ new AtomicReference[SparkContext](null /* initialValue */)
val yarnAllocatorLoop: AtomicInteger = new AtomicInteger(0)
def sparkContextInitialized(sc: SparkContext): Boolean = {
@@ -423,19 +439,21 @@ object ApplicationMaster {
sparkContextRef.notifyAll()
}
- // Add a shutdown hook - as a best case effort in case users do not call sc.stop or do System.exit
- // Should not really have to do this, but it helps yarn to evict resources earlier.
- // not to mention, prevent Client declaring failure even though we exit'ed properly.
- // Note that this will unfortunately not properly clean up the staging files because it gets called to
- // late and the filesystem is already shutdown.
+ // Add a shutdown hook - as a best case effort in case users do not call sc.stop or do
+ // System.exit.
+ // Should not really have to do this, but it helps YARN to evict resources earlier.
+ // Not to mention, prevent the Client from declaring failure even though we exited properly.
+ // Note that this will unfortunately not properly clean up the staging files because it gets
+ // called too late, after the filesystem is already shutdown.
if (modified) {
Runtime.getRuntime().addShutdownHook(new Thread with Logging {
- // This is not just to log, but also to ensure that log system is initialized for this instance when we actually are 'run'
+ // This is not only logs, but also ensures that log system is initialized for this instance
+ // when we are actually 'run'-ing.
logInfo("Adding shutdown hook for context " + sc)
override def run() {
logInfo("Invoking sc stop from shutdown hook")
sc.stop()
- // best case ...
+ // Best case ...
for (master <- applicationMasters) {
master.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
}
@@ -443,7 +461,7 @@ object ApplicationMaster {
} )
}
- // Wait for initialization to complete and atleast 'some' nodes can get allocated
+ // Wait for initialization to complete and atleast 'some' nodes can get allocated.
yarnAllocatorLoop.synchronized {
while (yarnAllocatorLoop.get() <= ALLOCATOR_LOOP_WAIT_COUNT) {
yarnAllocatorLoop.wait(1000L)
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index bb73f6d337ba04f47bd407c24b6311f0a50e10b6..79dd03806523bcea066fcafd05160fe732032d22 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -20,41 +20,46 @@ package org.apache.spark.deploy.yarn
import java.net.{InetAddress, UnknownHostException, URI}
import java.nio.ByteBuffer
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
+import scala.collection.mutable.Map
+
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FileContext, FileStatus, FileSystem, Path, FileUtil}
-import org.apache.hadoop.fs.permission.FsPermission
-import org.apache.hadoop.mapred.Master
+import org.apache.hadoop.fs.permission.FsPermission;
import org.apache.hadoop.io.DataOutputBuffer
+import org.apache.hadoop.mapred.Master
+import org.apache.hadoop.net.NetUtils
import org.apache.hadoop.security.UserGroupInformation
import org.apache.hadoop.yarn.api._
import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
-import org.apache.hadoop.yarn.api.records._
import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.api.records._
import org.apache.hadoop.yarn.client.YarnClientImpl
import org.apache.hadoop.yarn.conf.YarnConfiguration
import org.apache.hadoop.yarn.ipc.YarnRPC
import org.apache.hadoop.yarn.util.{Apps, Records}
-import scala.collection.mutable.HashMap
-import scala.collection.mutable.Map
-import scala.collection.JavaConversions._
+import org.apache.spark.Logging
+import org.apache.spark.util.Utils
+import org.apache.spark.deploy.SparkHadoopUtil
-import org.apache.spark.Logging
class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl with Logging {
-
+
def this(args: ClientArguments) = this(new Configuration(), args)
-
+
var rpc: YarnRPC = YarnRPC.create(conf)
val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
val credentials = UserGroupInformation.getCurrentUser().getCredentials()
private val SPARK_STAGING: String = ".sparkStaging"
private val distCacheMgr = new ClientDistributedCacheManager()
- // staging directory is private! -> rwx--------
+ // Staging directory is private! -> rwx--------
val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700:Short)
- // app files are world-wide readable and owner writable -> rw-r--r--
- val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644:Short)
+
+ // App files are world-wide readable and owner writable -> rw-r--r--
+ val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644:Short)
// for client user who want to monitor app status by itself.
def runApp() = {
@@ -89,15 +94,16 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
}
def validateArgs() = {
- Map((System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!",
+ Map(
+ (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!",
(args.userJar == null) -> "Error: You must specify a user jar!",
(args.userClass == null) -> "Error: You must specify a user class!",
(args.numWorkers <= 0) -> "Error: You must specify atleast 1 worker!",
- (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) ->
- ("Error: AM memory size must be greater then: " + YarnAllocationHandler.MEMORY_OVERHEAD),
- (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) ->
- ("Error: Worker memory size must be greater then: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString()))
- .foreach { case(cond, errStr) =>
+ (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be " +
+ "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD),
+ (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size " +
+ "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD)
+ ).foreach { case(cond, errStr) =>
if (cond) {
logError(errStr)
args.printUsageAndExit(1)
@@ -111,19 +117,24 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
def logClusterResourceDetails() {
val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics
- logInfo("Got Cluster metric info from ASM, numNodeManagers=" + clusterMetrics.getNumNodeManagers)
+ logInfo("Got Cluster metric info from ASM, numNodeManagers = " +
+ clusterMetrics.getNumNodeManagers)
val queueInfo: QueueInfo = super.getQueueInfo(args.amQueue)
- logInfo("Queue info .. queueName=" + queueInfo.getQueueName + ", queueCurrentCapacity=" + queueInfo.getCurrentCapacity +
- ", queueMaxCapacity=" + queueInfo.getMaximumCapacity + ", queueApplicationCount=" + queueInfo.getApplications.size +
- ", queueChildQueueCount=" + queueInfo.getChildQueues.size)
+ logInfo("""Queue info ... queueName = %s, queueCurrentCapacity = %s, queueMaxCapacity = %s,
+ queueApplicationCount = %s, queueChildQueueCount = %s""".format(
+ queueInfo.getQueueName,
+ queueInfo.getCurrentCapacity,
+ queueInfo.getMaximumCapacity,
+ queueInfo.getApplications.size,
+ queueInfo.getChildQueues.size))
}
-
+
def verifyClusterResources(app: GetNewApplicationResponse) = {
val maxMem = app.getMaximumResourceCapability().getMemory()
logInfo("Max mem capabililty of a single resource in this cluster " + maxMem)
-
- // if we have requested more then the clusters max for a single resource then exit.
+
+ // If we have requested more then the clusters max for a single resource then exit.
if (args.workerMemory > maxMem) {
logError("the worker size is to large to run on this cluster " + args.workerMemory)
System.exit(1)
@@ -134,10 +145,10 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
System.exit(1)
}
- // We could add checks to make sure the entire cluster has enough resources but that involves getting
- // all the node reports and computing ourselves
+ // We could add checks to make sure the entire cluster has enough resources but that involves
+ // getting all the node reports and computing ourselves
}
-
+
def createApplicationSubmissionContext(appId: ApplicationId): ApplicationSubmissionContext = {
logInfo("Setting up application submission context for ASM")
val appContext = Records.newRecord(classOf[ApplicationSubmissionContext])
@@ -146,9 +157,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
return appContext
}
- /*
- * see if two file systems are the same or not.
- */
+ /** See if two file systems are the same or not. */
private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = {
val srcUri = srcFs.getUri()
val dstUri = destFs.getUri()
@@ -183,9 +192,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
return true
}
- /**
- * Copy the file into HDFS if needed.
- */
+ /** Copy the file into HDFS if needed. */
private def copyRemoteFile(
dstDir: Path,
originalPath: Path,
@@ -201,9 +208,8 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
fs.setReplication(newPath, replication)
if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION))
}
- // resolve any symlinks in the URI path so using a "current" symlink
- // to point to a specific version shows the specific version
- // in the distributed cache configuration
+ // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific
+ // version shows the specific version in the distributed cache configuration
val qualPath = fs.makeQualified(newPath)
val fc = FileContext.getFileContext(qualPath.toUri(), conf)
val destPath = fc.resolvePath(qualPath)
@@ -212,8 +218,8 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = {
logInfo("Preparing Local resources")
- // Upload Spark and the application JAR to the remote file system if necessary
- // Add them as local resources to the AM
+ // Upload Spark and the application JAR to the remote file system if necessary. Add them as
+ // local resources to the AM.
val fs = FileSystem.get(conf)
val delegTokenRenewer = Master.getMasterPrincipal(conf)
@@ -243,7 +249,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
var localURI = new URI(localPath)
// if not specified assume these are in the local filesystem to keep behavior like Hadoop
if (localURI.getScheme() == null) {
- localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString())
+ localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString)
}
val setPermissions = if (destName.equals(Client.APP_JAR)) true else false
val destPath = copyRemoteFile(dst, new Path(localURI), replication, setPermissions)
@@ -291,7 +297,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
UserGroupInformation.getCurrentUser().addCredentials(credentials)
return localResources
}
-
+
def setupLaunchEnv(
localResources: HashMap[String, LocalResource],
stagingDir: String): HashMap[String, String] = {
@@ -304,16 +310,16 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
env("SPARK_YARN_MODE") = "true"
env("SPARK_YARN_STAGING_DIR") = stagingDir
- // set the environment variables to be passed on to the Workers
+ // Set the environment variables to be passed on to the Workers.
distCacheMgr.setDistFilesEnv(env)
distCacheMgr.setDistArchivesEnv(env)
- // allow users to specify some environment variables
+ // Allow users to specify some environment variables.
Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
- // Add each SPARK-* key to the environment
+ // Add each SPARK-* key to the environment.
System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
- return env
+ env
}
def userArgsToString(clientArgs: ClientArguments): String = {
@@ -323,13 +329,13 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
for (arg <- args){
retval.append(prefix).append(" '").append(arg).append("' ")
}
-
retval.toString
}
- def createContainerLaunchContext(newApp: GetNewApplicationResponse,
- localResources: HashMap[String, LocalResource],
- env: HashMap[String, String]): ContainerLaunchContext = {
+ def createContainerLaunchContext(
+ newApp: GetNewApplicationResponse,
+ localResources: HashMap[String, LocalResource],
+ env: HashMap[String, String]): ContainerLaunchContext = {
logInfo("Setting up container launch context")
val amContainer = Records.newRecord(classOf[ContainerLaunchContext])
amContainer.setLocalResources(localResources)
@@ -337,8 +343,10 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory()
+ // TODO(harvey): This can probably be a val.
var amMemory = ((args.amMemory / minResMemory) * minResMemory) +
- (if (0 != (args.amMemory % minResMemory)) minResMemory else 0) - YarnAllocationHandler.MEMORY_OVERHEAD
+ ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) -
+ YarnAllocationHandler.MEMORY_OVERHEAD)
// Extra options for the JVM
var JAVA_OPTS = ""
@@ -349,13 +357,18 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
JAVA_OPTS += " -Djava.io.tmpdir=" +
new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " "
- // Commenting it out for now - so that people can refer to the properties if required. Remove it once cpuset version is pushed out.
- // The context is, default gc for server class machines end up using all cores to do gc - hence if there are multiple containers in same
- // node, spark gc effects all other containers performance (which can also be other spark containers)
- // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in multi-tenant environments. Not sure how default java gc behaves if it is
- // limited to subset of cores on a node.
- if (env.isDefinedAt("SPARK_USE_CONC_INCR_GC") && java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))) {
- // In our expts, using (default) throughput collector has severe perf ramnifications in multi-tenant machines
+ // Commenting it out for now - so that people can refer to the properties if required. Remove
+ // it once cpuset version is pushed out. The context is, default gc for server class machines
+ // end up using all cores to do gc - hence if there are multiple containers in same node,
+ // spark gc effects all other containers performance (which can also be other spark containers)
+ // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in
+ // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset
+ // of cores on a node.
+ val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") &&
+ java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))
+ if (useConcurrentAndIncrementalGC) {
+ // In our expts, using (default) throughput collector has severe perf ramnifications in
+ // multi-tenant machines
JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
JAVA_OPTS += " -XX:+CMSIncrementalMode "
JAVA_OPTS += " -XX:+CMSIncrementalPacing "
@@ -388,28 +401,28 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
" 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
logInfo("Command for the ApplicationMaster: " + commands(0))
amContainer.setCommands(commands)
-
+
val capability = Records.newRecord(classOf[Resource]).asInstanceOf[Resource]
- // Memory for the ApplicationMaster
+ // Memory for the ApplicationMaster.
capability.setMemory(args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
amContainer.setResource(capability)
- // Setup security tokens
+ // Setup security tokens.
val dob = new DataOutputBuffer()
credentials.writeTokenStorageToStream(dob)
amContainer.setContainerTokens(ByteBuffer.wrap(dob.getData()))
- return amContainer
+ amContainer
}
-
+
def submitApp(appContext: ApplicationSubmissionContext) = {
- // Submit the application to the applications manager
+ // Submit the application to the applications manager.
logInfo("Submitting application to ASM")
super.submitApplication(appContext)
}
-
+
def monitorApplication(appId: ApplicationId): Boolean = {
- while(true) {
+ while (true) {
Thread.sleep(1000)
val report = super.getApplicationReport(appId)
@@ -427,16 +440,16 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
"\t appTrackingUrl: " + report.getTrackingUrl() + "\n" +
"\t appUser: " + report.getUser()
)
-
+
val state = report.getYarnApplicationState()
val dsStatus = report.getFinalApplicationStatus()
if (state == YarnApplicationState.FINISHED ||
state == YarnApplicationState.FAILED ||
state == YarnApplicationState.KILLED) {
- return true
+ return true
}
}
- return true
+ true
}
}
@@ -469,7 +482,7 @@ object Client {
Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
Path.SEPARATOR + LOG4J_PROP)
}
- // normally the users app.jar is last in case conflicts with spark jars
+ // Normally the users app.jar is last in case conflicts with spark jars
val userClasspathFirst = System.getProperty("spark.yarn.user.classpath.first", "false")
.toBoolean
if (userClasspathFirst) {
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
index a4d6e1d87d1270fd48e8f0f6273f8cfd076e7e64..6a90cc51cfbaf71ef5683703dd84fa6d5b872ccb 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
@@ -21,52 +21,59 @@ import java.net.URI
import java.nio.ByteBuffer
import java.security.PrivilegedExceptionAction
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
+
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path
import org.apache.hadoop.io.DataOutputBuffer
import org.apache.hadoop.net.NetUtils
import org.apache.hadoop.security.UserGroupInformation
import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
import org.apache.hadoop.yarn.api.records._
import org.apache.hadoop.yarn.api.protocolrecords._
import org.apache.hadoop.yarn.conf.YarnConfiguration
import org.apache.hadoop.yarn.ipc.YarnRPC
import org.apache.hadoop.yarn.util.{Apps, ConverterUtils, Records, ProtoUtils}
-import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
-
-import scala.collection.JavaConversions._
-import scala.collection.mutable.HashMap
import org.apache.spark.Logging
-class WorkerRunnable(container: Container, conf: Configuration, masterAddress: String,
- slaveId: String, hostname: String, workerMemory: Int, workerCores: Int)
- extends Runnable with Logging {
-
+
+class WorkerRunnable(
+ container: Container,
+ conf: Configuration,
+ masterAddress: String,
+ slaveId: String,
+ hostname: String,
+ workerMemory: Int,
+ workerCores: Int)
+ extends Runnable with Logging {
+
var rpc: YarnRPC = YarnRPC.create(conf)
var cm: ContainerManager = null
val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
-
+
def run = {
logInfo("Starting Worker Container")
cm = connectToCM
startContainer
}
-
+
def startContainer = {
logInfo("Setting up ContainerLaunchContext")
-
+
val ctx = Records.newRecord(classOf[ContainerLaunchContext])
.asInstanceOf[ContainerLaunchContext]
-
+
ctx.setContainerId(container.getId())
ctx.setResource(container.getResource())
val localResources = prepareLocalResources
ctx.setLocalResources(localResources)
-
+
val env = prepareEnvironment
ctx.setEnvironment(env)
-
+
// Extra options for the JVM
var JAVA_OPTS = ""
// Set the JVM memory
@@ -79,17 +86,21 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
JAVA_OPTS += " -Djava.io.tmpdir=" +
new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " "
-
- // Commenting it out for now - so that people can refer to the properties if required. Remove it once cpuset version is pushed out.
- // The context is, default gc for server class machines end up using all cores to do gc - hence if there are multiple containers in same
- // node, spark gc effects all other containers performance (which can also be other spark containers)
- // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in multi-tenant environments. Not sure how default java gc behaves if it is
- // limited to subset of cores on a node.
+ // Commenting it out for now - so that people can refer to the properties if required. Remove
+ // it once cpuset version is pushed out.
+ // The context is, default gc for server class machines end up using all cores to do gc - hence
+ // if there are multiple containers in same node, spark gc effects all other containers
+ // performance (which can also be other spark containers)
+ // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in
+ // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset
+ // of cores on a node.
/*
else {
// If no java_opts specified, default to using -XX:+CMSIncrementalMode
- // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont want to mess with it.
- // In our expts, using (default) throughput collector has severe perf ramnifications in multi-tennent machines
+ // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont
+ // want to mess with it.
+ // In our expts, using (default) throughput collector has severe perf ramnifications in
+ // multi-tennent machines
// The options are based on
// http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline
JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
@@ -116,8 +127,10 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
val commands = List[String](javaCommand +
" -server " +
// Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling.
- // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in an inconsistent state.
- // TODO: If the OOM is not recoverable by rescheduling it on different node, then do 'something' to fail job ... akin to blacklisting trackers in mapred ?
+ // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in
+ // an inconsistent state.
+ // TODO: If the OOM is not recoverable by rescheduling it on different node, then do
+ // 'something' to fail job ... akin to blacklisting trackers in mapred ?
" -XX:OnOutOfMemoryError='kill %p' " +
JAVA_OPTS +
" org.apache.spark.executor.CoarseGrainedExecutorBackend " +
@@ -129,7 +142,7 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
" 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
logInfo("Setting up worker with commands: " + commands)
ctx.setCommands(commands)
-
+
// Send the start request to the ContainerManager
val startReq = Records.newRecord(classOf[StartContainerRequest])
.asInstanceOf[StartContainerRequest]
@@ -137,7 +150,8 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
cm.startContainer(startReq)
}
- private def setupDistributedCache(file: String,
+ private def setupDistributedCache(
+ file: String,
rtype: LocalResourceType,
localResources: HashMap[String, LocalResource],
timestamp: String,
@@ -152,12 +166,11 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
amJarRsrc.setSize(size.toLong)
localResources(uri.getFragment()) = amJarRsrc
}
-
-
+
def prepareLocalResources: HashMap[String, LocalResource] = {
logInfo("Preparing Local resources")
val localResources = HashMap[String, LocalResource]()
-
+
if (System.getenv("SPARK_YARN_CACHE_FILES") != null) {
val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',')
val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',')
@@ -179,30 +192,30 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
timeStamps(i), fileSizes(i), visibilities(i))
}
}
-
+
logInfo("Prepared Local resources " + localResources)
return localResources
}
-
+
def prepareEnvironment: HashMap[String, String] = {
val env = new HashMap[String, String]()
Client.populateClasspath(yarnConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env)
- // allow users to specify some environment variables
+ // Allow users to specify some environment variables
Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
return env
}
-
+
def connectToCM: ContainerManager = {
val cmHostPortStr = container.getNodeId().getHost() + ":" + container.getNodeId().getPort()
val cmAddress = NetUtils.createSocketAddr(cmHostPortStr)
logInfo("Connecting to ContainerManager at " + cmHostPortStr)
- // use doAs and remoteUser here so we can add the container token and not
- // pollute the current users credentials with all of the individual container tokens
+ // Use doAs and remoteUser here so we can add the container token and not pollute the current
+ // users credentials with all of the individual container tokens
val user = UserGroupInformation.createRemoteUser(container.getId().toString())
val containerToken = container.getContainerToken()
if (containerToken != null) {
@@ -218,5 +231,5 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
})
proxy
}
-
+
}
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
index 507a0743fd77abf8a7feed9aa953f1d52b4e9b35..f15f3c7c1195c61cf8ad31987e8879d0885c8233 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
@@ -17,55 +17,70 @@
package org.apache.spark.deploy.yarn
+import java.lang.{Boolean => JBoolean}
+import java.util.{Collections, Set => JSet}
+import java.util.concurrent.{CopyOnWriteArrayList, ConcurrentHashMap}
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection
+import scala.collection.JavaConversions._
+import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet}
+
import org.apache.spark.Logging
-import org.apache.spark.util.Utils
import org.apache.spark.scheduler.SplitInfo
-import scala.collection
-import org.apache.hadoop.yarn.api.records.{AMResponse, ApplicationAttemptId, ContainerId, Priority, Resource, ResourceRequest, ContainerStatus, Container}
import org.apache.spark.scheduler.cluster.{ClusterScheduler, CoarseGrainedSchedulerBackend}
+import org.apache.spark.util.Utils
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.yarn.api.AMRMProtocol
+import org.apache.hadoop.yarn.api.records.{AMResponse, ApplicationAttemptId}
+import org.apache.hadoop.yarn.api.records.{Container, ContainerId, ContainerStatus}
+import org.apache.hadoop.yarn.api.records.{Priority, Resource, ResourceRequest}
import org.apache.hadoop.yarn.api.protocolrecords.{AllocateRequest, AllocateResponse}
import org.apache.hadoop.yarn.util.{RackResolver, Records}
-import java.util.concurrent.{CopyOnWriteArrayList, ConcurrentHashMap}
-import java.util.concurrent.atomic.AtomicInteger
-import org.apache.hadoop.yarn.api.AMRMProtocol
-import collection.JavaConversions._
-import collection.mutable.{ArrayBuffer, HashMap, HashSet}
-import org.apache.hadoop.conf.Configuration
-import java.util.{Collections, Set => JSet}
-import java.lang.{Boolean => JBoolean}
+
object AllocationType extends Enumeration ("HOST", "RACK", "ANY") {
type AllocationType = Value
val HOST, RACK, ANY = Value
}
-// too many params ? refactor it 'somehow' ?
-// needs to be mt-safe
-// Need to refactor this to make it 'cleaner' ... right now, all computation is reactive : should make it
-// more proactive and decoupled.
+// TODO:
+// Too many params.
+// Needs to be mt-safe
+// Need to refactor this to make it 'cleaner' ... right now, all computation is reactive - should
+// make it more proactive and decoupled.
+
// Note that right now, we assume all node asks as uniform in terms of capabilities and priority
-// Refer to http://developer.yahoo.com/blogs/hadoop/posts/2011/03/mapreduce-nextgen-scheduler/ for more info
-// on how we are requesting for containers.
-private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceManager: AMRMProtocol,
- val appAttemptId: ApplicationAttemptId,
- val maxWorkers: Int, val workerMemory: Int, val workerCores: Int,
- val preferredHostToCount: Map[String, Int],
- val preferredRackToCount: Map[String, Int])
+// Refer to http://developer.yahoo.com/blogs/hadoop/posts/2011/03/mapreduce-nextgen-scheduler/ for
+// more info on how we are requesting for containers.
+private[yarn] class YarnAllocationHandler(
+ val conf: Configuration,
+ val resourceManager: AMRMProtocol,
+ val appAttemptId: ApplicationAttemptId,
+ val maxWorkers: Int,
+ val workerMemory: Int,
+ val workerCores: Int,
+ val preferredHostToCount: Map[String, Int],
+ val preferredRackToCount: Map[String, Int])
extends Logging {
-
-
// These three are locked on allocatedHostToContainersMap. Complementary data structures
// allocatedHostToContainersMap : containers which are running : host, Set<containerid>
- // allocatedContainerToHostMap: container to host mapping
- private val allocatedHostToContainersMap = new HashMap[String, collection.mutable.Set[ContainerId]]()
+ // allocatedContainerToHostMap: container to host mapping.
+ private val allocatedHostToContainersMap =
+ new HashMap[String, collection.mutable.Set[ContainerId]]()
+
private val allocatedContainerToHostMap = new HashMap[ContainerId, String]()
- // allocatedRackCount is populated ONLY if allocation happens (or decremented if this is an allocated node)
- // As with the two data structures above, tightly coupled with them, and to be locked on allocatedHostToContainersMap
+
+ // allocatedRackCount is populated ONLY if allocation happens (or decremented if this is an
+ // allocated node)
+ // As with the two data structures above, tightly coupled with them, and to be locked on
+ // allocatedHostToContainersMap
private val allocatedRackCount = new HashMap[String, Int]()
- // containers which have been released.
+ // Containers which have been released.
private val releasedContainerList = new CopyOnWriteArrayList[ContainerId]()
- // containers to be released in next request to RM
+ // Containers to be released in next request to RM
private val pendingReleaseContainers = new ConcurrentHashMap[ContainerId, Boolean]
private val numWorkersRunning = new AtomicInteger()
@@ -83,23 +98,31 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
}
def allocateContainers(workersToRequest: Int) {
- // We need to send the request only once from what I understand ... but for now, not modifying this much.
+ // We need to send the request only once from what I understand ... but for now, not modifying
+ // this much.
// Keep polling the Resource Manager for containers
val amResp = allocateWorkerResources(workersToRequest).getAMResponse
val _allocatedContainers = amResp.getAllocatedContainers()
- if (_allocatedContainers.size > 0) {
-
- logDebug("Allocated " + _allocatedContainers.size + " containers, current count " +
- numWorkersRunning.get() + ", to-be-released " + releasedContainerList +
- ", pendingReleaseContainers : " + pendingReleaseContainers)
- logDebug("Cluster Resources: " + amResp.getAvailableResources)
+ if (_allocatedContainers.size > 0) {
+ logDebug("""
+ Allocated containers: %d
+ Current worker count: %d
+ Containers released: %s
+ Containers to be released: %s
+ Cluster resources: %s
+ """.format(
+ _allocatedContainers.size,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers,
+ amResp.getAvailableResources))
val hostToContainers = new HashMap[String, ArrayBuffer[Container]]()
- // ignore if not satisfying constraints {
+ // Ignore if not satisfying constraints {
for (container <- _allocatedContainers) {
if (isResourceConstraintSatisfied(container)) {
// allocatedContainers += container
@@ -113,8 +136,7 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
else releasedContainerList.add(container.getId())
}
- // Find the appropriate containers to use
- // Slightly non trivial groupBy I guess ...
+ // Find the appropriate containers to use. Slightly non trivial groupBy ...
val dataLocalContainers = new HashMap[String, ArrayBuffer[Container]]()
val rackLocalContainers = new HashMap[String, ArrayBuffer[Container]]()
val offRackContainers = new HashMap[String, ArrayBuffer[Container]]()
@@ -134,21 +156,22 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
remainingContainers = null
}
else if (requiredHostCount > 0) {
- // container list has more containers than we need for data locality.
- // Split into two : data local container count of (remainingContainers.size - requiredHostCount)
- // and rest as remainingContainer
- val (dataLocal, remaining) = remainingContainers.splitAt(remainingContainers.size - requiredHostCount)
+ // Container list has more containers than we need for data locality.
+ // Split into two : data local container count of (remainingContainers.size -
+ // requiredHostCount) and rest as remainingContainer
+ val (dataLocal, remaining) = remainingContainers.splitAt(
+ remainingContainers.size - requiredHostCount)
dataLocalContainers.put(candidateHost, dataLocal)
// remainingContainers = remaining
// yarn has nasty habit of allocating a tonne of containers on a host - discourage this :
- // add remaining to release list. If we have insufficient containers, next allocation cycle
- // will reallocate (but wont treat it as data local)
+ // add remaining to release list. If we have insufficient containers, next allocation
+ // cycle will reallocate (but wont treat it as data local)
for (container <- remaining) releasedContainerList.add(container.getId())
remainingContainers = null
}
- // now rack local
+ // Now rack local
if (remainingContainers != null){
val rack = YarnAllocationHandler.lookupRack(conf, candidateHost)
@@ -161,15 +184,17 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
if (requiredRackCount >= remainingContainers.size){
// Add all to dataLocalContainers
dataLocalContainers.put(rack, remainingContainers)
- // all consumed
+ // All consumed
remainingContainers = null
}
else if (requiredRackCount > 0) {
// container list has more containers than we need for data locality.
- // Split into two : data local container count of (remainingContainers.size - requiredRackCount)
- // and rest as remainingContainer
- val (rackLocal, remaining) = remainingContainers.splitAt(remainingContainers.size - requiredRackCount)
- val existingRackLocal = rackLocalContainers.getOrElseUpdate(rack, new ArrayBuffer[Container]())
+ // Split into two : data local container count of (remainingContainers.size -
+ // requiredRackCount) and rest as remainingContainer
+ val (rackLocal, remaining) = remainingContainers.splitAt(
+ remainingContainers.size - requiredRackCount)
+ val existingRackLocal = rackLocalContainers.getOrElseUpdate(rack,
+ new ArrayBuffer[Container]())
existingRackLocal ++= rackLocal
remainingContainers = remaining
@@ -185,8 +210,8 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
// Now that we have split the containers into various groups, go through them in order :
// first host local, then rack local and then off rack (everything else).
- // Note that the list we create below tries to ensure that not all containers end up within a host
- // if there are sufficiently large number of hosts/containers.
+ // Note that the list we create below tries to ensure that not all containers end up within a
+ // host if there are sufficiently large number of hosts/containers.
val allocatedContainers = new ArrayBuffer[Container](_allocatedContainers.size)
allocatedContainers ++= ClusterScheduler.prioritizeContainers(dataLocalContainers)
@@ -199,33 +224,39 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
val workerHostname = container.getNodeId.getHost
val containerId = container.getId
- assert (container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD))
+ assert(
+ container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD))
if (numWorkersRunningNow > maxWorkers) {
- logInfo("Ignoring container " + containerId + " at host " + workerHostname +
- " .. we already have required number of containers")
+ logInfo("""Ignoring container %s at host %s, since we already have the required number of
+ containers for it.""".format(containerId, workerHostname))
releasedContainerList.add(containerId)
// reset counter back to old value.
numWorkersRunning.decrementAndGet()
}
else {
- // deallocate + allocate can result in reusing id's wrongly - so use a different counter (workerIdCounter)
+ // Deallocate + allocate can result in reusing id's wrongly - so use a different counter
+ // (workerIdCounter)
val workerId = workerIdCounter.incrementAndGet().toString
val driverUrl = "akka://spark@%s:%s/user/%s".format(
System.getProperty("spark.driver.host"), System.getProperty("spark.driver.port"),
CoarseGrainedSchedulerBackend.ACTOR_NAME)
logInfo("launching container on " + containerId + " host " + workerHostname)
- // just to be safe, simply remove it from pendingReleaseContainers. Should not be there, but ..
+ // Just to be safe, simply remove it from pendingReleaseContainers.
+ // Should not be there, but ..
pendingReleaseContainers.remove(containerId)
val rack = YarnAllocationHandler.lookupRack(conf, workerHostname)
allocatedHostToContainersMap.synchronized {
- val containerSet = allocatedHostToContainersMap.getOrElseUpdate(workerHostname, new HashSet[ContainerId]())
+ val containerSet = allocatedHostToContainersMap.getOrElseUpdate(workerHostname,
+ new HashSet[ContainerId]())
containerSet += containerId
allocatedContainerToHostMap.put(containerId, workerHostname)
- if (rack != null) allocatedRackCount.put(rack, allocatedRackCount.getOrElse(rack, 0) + 1)
+ if (rack != null) {
+ allocatedRackCount.put(rack, allocatedRackCount.getOrElse(rack, 0) + 1)
+ }
}
new Thread(
@@ -234,17 +265,23 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
).start()
}
}
- logDebug("After allocated " + allocatedContainers.size + " containers (orig : " +
- _allocatedContainers.size + "), current count " + numWorkersRunning.get() +
- ", to-be-released " + releasedContainerList + ", pendingReleaseContainers : " + pendingReleaseContainers)
+ logDebug("""
+ Finished processing %d containers.
+ Current number of workers running: %d,
+ releasedContainerList: %s,
+ pendingReleaseContainers: %s
+ """.format(
+ allocatedContainers.size,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers))
}
val completedContainers = amResp.getCompletedContainersStatuses()
if (completedContainers.size > 0){
- logDebug("Completed " + completedContainers.size + " containers, current count " + numWorkersRunning.get() +
- ", to-be-released " + releasedContainerList + ", pendingReleaseContainers : " + pendingReleaseContainers)
-
+ logDebug("Completed %d containers, to-be-released: %s".format(
+ completedContainers.size, releasedContainerList))
for (completedContainer <- completedContainers){
val containerId = completedContainer.getContainerId
@@ -253,16 +290,17 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
pendingReleaseContainers.remove(containerId)
}
else {
- // simply decrement count - next iteration of ReporterThread will take care of allocating !
+ // Simply decrement count - next iteration of ReporterThread will take care of allocating.
numWorkersRunning.decrementAndGet()
- logInfo("Container completed not by us ? nodeId: " + containerId + ", state " + completedContainer.getState +
- " httpaddress: " + completedContainer.getDiagnostics + " exit status: " + completedContainer.getExitStatus())
-
+ logInfo("Completed container %s (state: %s, exit status: %s)".format(
+ containerId,
+ completedContainer.getState,
+ completedContainer.getExitStatus()))
// Hadoop 2.2.X added a ContainerExitStatus we should switch to use
// there are some exit status' we shouldn't necessarily count against us, but for
// now I think its ok as none of the containers are expected to exit
if (completedContainer.getExitStatus() != 0) {
- logInfo("Container marked as failed: " + containerId)
+ logInfo("Container marked as failed: " + containerId)
numWorkersFailed.incrementAndGet()
}
}
@@ -281,7 +319,7 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
allocatedContainerToHostMap -= containerId
- // doing this within locked context, sigh ... move to outside ?
+ // Doing this within locked context, sigh ... move to outside ?
val rack = YarnAllocationHandler.lookupRack(conf, host)
if (rack != null) {
val rackCount = allocatedRackCount.getOrElse(rack, 0) - 1
@@ -291,9 +329,16 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
}
}
}
- logDebug("After completed " + completedContainers.size + " containers, current count " +
- numWorkersRunning.get() + ", to-be-released " + releasedContainerList +
- ", pendingReleaseContainers : " + pendingReleaseContainers)
+ logDebug("""
+ Finished processing %d completed containers.
+ Current number of workers running: %d,
+ releasedContainerList: %s,
+ pendingReleaseContainers: %s
+ """.format(
+ completedContainers.size,
+ numWorkersRunning.get(),
+ releasedContainerList,
+ pendingReleaseContainers))
}
}
@@ -347,7 +392,7 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
// default.
if (numWorkers <= 0 || preferredHostToCount.isEmpty) {
- logDebug("numWorkers: " + numWorkers + ", host preferences ? " + preferredHostToCount.isEmpty)
+ logDebug("numWorkers: " + numWorkers + ", host preferences: " + preferredHostToCount.isEmpty)
resourceRequests = List(
createResourceRequest(AllocationType.ANY, null, numWorkers, YarnAllocationHandler.PRIORITY))
}
@@ -360,17 +405,24 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
val requiredCount = candidateCount - allocatedContainersOnHost(candidateHost)
if (requiredCount > 0) {
- hostContainerRequests +=
- createResourceRequest(AllocationType.HOST, candidateHost, requiredCount, YarnAllocationHandler.PRIORITY)
+ hostContainerRequests += createResourceRequest(
+ AllocationType.HOST,
+ candidateHost,
+ requiredCount,
+ YarnAllocationHandler.PRIORITY)
}
}
- val rackContainerRequests: List[ResourceRequest] = createRackResourceRequests(hostContainerRequests.toList)
+ val rackContainerRequests: List[ResourceRequest] = createRackResourceRequests(
+ hostContainerRequests.toList)
- val anyContainerRequests: ResourceRequest =
- createResourceRequest(AllocationType.ANY, null, numWorkers, YarnAllocationHandler.PRIORITY)
+ val anyContainerRequests: ResourceRequest = createResourceRequest(
+ AllocationType.ANY,
+ resource = null,
+ numWorkers,
+ YarnAllocationHandler.PRIORITY)
- val containerRequests: ArrayBuffer[ResourceRequest] =
- new ArrayBuffer[ResourceRequest](hostContainerRequests.size() + rackContainerRequests.size() + 1)
+ val containerRequests: ArrayBuffer[ResourceRequest] = new ArrayBuffer[ResourceRequest](
+ hostContainerRequests.size + rackContainerRequests.size + 1)
containerRequests ++= hostContainerRequests
containerRequests ++= rackContainerRequests
@@ -389,52 +441,59 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
req.addAllReleases(releasedContainerList)
if (numWorkers > 0) {
- logInfo("Allocating " + numWorkers + " worker containers with " + (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD) + " of memory each.")
+ logInfo("Allocating %d worker containers with %d of memory each.".format(numWorkers,
+ workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD))
}
else {
logDebug("Empty allocation req .. release : " + releasedContainerList)
}
- for (req <- resourceRequests) {
- logInfo("rsrcRequest ... host : " + req.getHostName + ", numContainers : " + req.getNumContainers +
- ", p = " + req.getPriority().getPriority + ", capability: " + req.getCapability)
+ for (request <- resourceRequests) {
+ logInfo("ResourceRequest (host : %s, num containers: %d, priority = %s , capability : %s)".
+ format(
+ request.getHostName,
+ request.getNumContainers,
+ request.getPriority,
+ request.getCapability))
}
resourceManager.allocate(req)
}
- private def createResourceRequest(requestType: AllocationType.AllocationType,
- resource:String, numWorkers: Int, priority: Int): ResourceRequest = {
+ private def createResourceRequest(
+ requestType: AllocationType.AllocationType,
+ resource:String,
+ numWorkers: Int,
+ priority: Int): ResourceRequest = {
// If hostname specified, we need atleast two requests - node local and rack local.
// There must be a third request - which is ANY : that will be specially handled.
requestType match {
case AllocationType.HOST => {
- assert (YarnAllocationHandler.ANY_HOST != resource)
-
+ assert(YarnAllocationHandler.ANY_HOST != resource)
val hostname = resource
val nodeLocal = createResourceRequestImpl(hostname, numWorkers, priority)
- // add to host->rack mapping
+ // Add to host->rack mapping
YarnAllocationHandler.populateRackInfo(conf, hostname)
nodeLocal
}
-
case AllocationType.RACK => {
val rack = resource
createResourceRequestImpl(rack, numWorkers, priority)
}
-
- case AllocationType.ANY => {
- createResourceRequestImpl(YarnAllocationHandler.ANY_HOST, numWorkers, priority)
- }
-
- case _ => throw new IllegalArgumentException("Unexpected/unsupported request type .. " + requestType)
+ case AllocationType.ANY => createResourceRequestImpl(
+ YarnAllocationHandler.ANY_HOST, numWorkers, priority)
+ case _ => throw new IllegalArgumentException(
+ "Unexpected/unsupported request type: " + requestType)
}
}
- private def createResourceRequestImpl(hostname:String, numWorkers: Int, priority: Int): ResourceRequest = {
+ private def createResourceRequestImpl(
+ hostname:String,
+ numWorkers: Int,
+ priority: Int): ResourceRequest = {
val rsrcRequest = Records.newRecord(classOf[ResourceRequest])
val memCapability = Records.newRecord(classOf[Resource])
@@ -455,11 +514,11 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
def createReleasedContainerList(): ArrayBuffer[ContainerId] = {
val retval = new ArrayBuffer[ContainerId](1)
- // iterator on COW list ...
+ // Iterator on COW list ...
for (container <- releasedContainerList.iterator()){
retval += container
}
- // remove from the original list.
+ // Remove from the original list.
if (! retval.isEmpty) {
releasedContainerList.removeAll(retval)
for (v <- retval) pendingReleaseContainers.put(v, true)
@@ -474,14 +533,14 @@ private[yarn] class YarnAllocationHandler(val conf: Configuration, val resourceM
object YarnAllocationHandler {
val ANY_HOST = "*"
- // all requests are issued with same priority : we do not (yet) have any distinction between
+ // All requests are issued with same priority : we do not (yet) have any distinction between
// request types (like map/reduce in hadoop for example)
val PRIORITY = 1
// Additional memory overhead - in mb
val MEMORY_OVERHEAD = 384
- // host to rack map - saved from allocation requests
+ // Host to rack map - saved from allocation requests
// We are expecting this not to change.
// Note that it is possible for this to change : and RM will indicate that to us via update
// response to allocate. But we are punting on handling that for now.
@@ -489,38 +548,69 @@ object YarnAllocationHandler {
private val rackToHostSet = new ConcurrentHashMap[String, JSet[String]]()
- def newAllocator(conf: Configuration,
- resourceManager: AMRMProtocol, appAttemptId: ApplicationAttemptId,
- args: ApplicationMasterArguments): YarnAllocationHandler = {
-
- new YarnAllocationHandler(conf, resourceManager, appAttemptId, args.numWorkers,
- args.workerMemory, args.workerCores, Map[String, Int](), Map[String, Int]())
+ def newAllocator(
+ conf: Configuration,
+ resourceManager: AMRMProtocol,
+ appAttemptId: ApplicationAttemptId,
+ args: ApplicationMasterArguments): YarnAllocationHandler = {
+
+ new YarnAllocationHandler(
+ conf,
+ resourceManager,
+ appAttemptId,
+ args.numWorkers,
+ args.workerMemory,
+ args.workerCores,
+ Map[String, Int](),
+ Map[String, Int]())
}
- def newAllocator(conf: Configuration,
- resourceManager: AMRMProtocol, appAttemptId: ApplicationAttemptId,
- args: ApplicationMasterArguments,
- map: collection.Map[String, collection.Set[SplitInfo]]): YarnAllocationHandler = {
+ def newAllocator(
+ conf: Configuration,
+ resourceManager: AMRMProtocol,
+ appAttemptId: ApplicationAttemptId,
+ args: ApplicationMasterArguments,
+ map: collection.Map[String,
+ collection.Set[SplitInfo]]): YarnAllocationHandler = {
val (hostToCount, rackToCount) = generateNodeToWeight(conf, map)
-
- new YarnAllocationHandler(conf, resourceManager, appAttemptId, args.numWorkers,
- args.workerMemory, args.workerCores, hostToCount, rackToCount)
+ new YarnAllocationHandler(
+ conf,
+ resourceManager,
+ appAttemptId,
+ args.numWorkers,
+ args.workerMemory,
+ args.workerCores,
+ hostToCount,
+ rackToCount)
}
- def newAllocator(conf: Configuration,
- resourceManager: AMRMProtocol, appAttemptId: ApplicationAttemptId,
- maxWorkers: Int, workerMemory: Int, workerCores: Int,
- map: collection.Map[String, collection.Set[SplitInfo]]): YarnAllocationHandler = {
+ def newAllocator(
+ conf: Configuration,
+ resourceManager: AMRMProtocol,
+ appAttemptId: ApplicationAttemptId,
+ maxWorkers: Int,
+ workerMemory: Int,
+ workerCores: Int,
+ map: collection.Map[String, collection.Set[SplitInfo]]): YarnAllocationHandler = {
val (hostToCount, rackToCount) = generateNodeToWeight(conf, map)
- new YarnAllocationHandler(conf, resourceManager, appAttemptId, maxWorkers,
- workerMemory, workerCores, hostToCount, rackToCount)
+ new YarnAllocationHandler(
+ conf,
+ resourceManager,
+ appAttemptId,
+ maxWorkers,
+ workerMemory,
+ workerCores,
+ hostToCount,
+ rackToCount)
}
// A simple method to copy the split info map.
- private def generateNodeToWeight(conf: Configuration, input: collection.Map[String, collection.Set[SplitInfo]]) :
+ private def generateNodeToWeight(
+ conf: Configuration,
+ input: collection.Map[String, collection.Set[SplitInfo]]) :
// host to count, rack to count
(Map[String, Int], Map[String, Int]) = {
@@ -544,7 +634,7 @@ object YarnAllocationHandler {
}
def lookupRack(conf: Configuration, host: String): String = {
- if (! hostToRack.contains(host)) populateRackInfo(conf, host)
+ if (!hostToRack.contains(host)) populateRackInfo(conf, host)
hostToRack.get(host)
}
@@ -567,10 +657,12 @@ object YarnAllocationHandler {
val rack = rackInfo.getNetworkLocation
hostToRack.put(hostname, rack)
if (! rackToHostSet.containsKey(rack)) {
- rackToHostSet.putIfAbsent(rack, Collections.newSetFromMap(new ConcurrentHashMap[String, JBoolean]()))
+ rackToHostSet.putIfAbsent(rack,
+ Collections.newSetFromMap(new ConcurrentHashMap[String, JBoolean]()))
}
rackToHostSet.get(rack).add(hostname)
+ // TODO(harvey): Figure out this comment...
// Since RackResolver caches, we are disabling this for now ...
} /* else {
// right ? Else we will keep calling rack resolver in case we cant resolve rack info ...