[SPARK-2933] [yarn] Refactor and cleanup Yarn AM code.

This change modifies the Yarn module so that all the logic related
to running the ApplicationMaster is localized. Instead of, previously,
4 different classes with mostly identical code, now we have:

- A single, shared ApplicationMaster class, which can operate both in
  client and cluster mode, and substitutes the old ApplicationMaster
  (for cluster mode) and ExecutorLauncher (for client mode).

The benefit here is that all different execution modes for all supported
yarn versions use the same shared code for monitoring executor allocation,
setting up configuration, and monitoring the process's lifecycle.

- A new YarnRMClient interface, which defines basic RM functionality needed
  by the ApplicationMaster. This interface has concrete implementations for
  each supported Yarn version.

- A new YarnAllocator interface, which just abstracts the existing interface
  of the YarnAllocationHandler class. This is to avoid having to touch the
  allocator code too much in this change, although it might benefit from a
  similar effort in the future.

The end result is much easier to understand code, with much less duplication,
making it much easier to fix bugs, add features, and test everything knowing
that all supported versions will behave the same.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #2020 from vanzin/SPARK-2933 and squashes the following commits:

3bbf3e7 [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
ff389ed [Marcelo Vanzin] Do not interrupt reporter thread from within itself.
3a8ed37 [Marcelo Vanzin] Remote stale comment.
0f5142c [Marcelo Vanzin] Review feedback.
41f8c8a [Marcelo Vanzin] Fix app status reporting.
c0794be [Marcelo Vanzin] Correctly clean up staging directory.
92770cc [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
ecaf332 [Marcelo Vanzin] Small fix to shutdown code.
f02d3f8 [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
f581122 [Marcelo Vanzin] Review feedback.
557fdeb [Marcelo Vanzin] Cleanup a couple more constants.
be6068d [Marcelo Vanzin] Restore shutdown hook to clean up staging dir.
5150993 [Marcelo Vanzin] Some more cleanup.
b6289ab [Marcelo Vanzin] Move cluster/client code to separate methods.
ecb23cd [Marcelo Vanzin] More trivial cleanup.
34f1e63 [Marcelo Vanzin] Fix some questionable error handling.
5657c7d [Marcelo Vanzin] Finish app if SparkContext initialization times out.
0e4be3d [Marcelo Vanzin] Keep "ExecutorLauncher" as the main class for client-mode AM.
91beabb [Marcelo Vanzin] Fix UI filter registration.
8c72239 [Marcelo Vanzin] Trivial cleanups.
99a52d5 [Marcelo Vanzin] Changes to the yarn-alpha project to use common AM code.
848ca6d [Marcelo Vanzin] [SPARK-2933] [yarn] Refactor and cleanup Yarn AM code.

4 files changed, 111 insertions, 850 deletions

diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
deleted file mode 100644
index 1c4005fd8e..0000000000
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ /dev/null
@@ -1,413 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.deploy.yarn
-
-import java.io.IOException
-import java.util.concurrent.CopyOnWriteArrayList
-import java.util.concurrent.atomic.AtomicReference
-
-import scala.collection.JavaConversions._
-
-import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.fs.{FileSystem, Path}
-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.util.ConverterUtils
-import org.apache.hadoop.yarn.webapp.util.WebAppUtils
-
-import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext}
-import org.apache.spark.deploy.SparkHadoopUtil
-import org.apache.spark.util.{SignalLogger, Utils}
-
-
-/**
- * An application master that runs the user's driver program and allocates executors.
- */
-class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration,
-                        sparkConf: SparkConf) extends Logging {
-
-  def this(args: ApplicationMasterArguments, sparkConf: SparkConf) =
-    this(args, new Configuration(), sparkConf)
-
-  def this(args: ApplicationMasterArguments) = this(args, new SparkConf())
-
-  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 var uiHistoryAddress: 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 numExecutors * 2, with minimum of 3
-  private val maxNumExecutorFailures = sparkConf.getInt("spark.yarn.max.executor.failures",
-    sparkConf.getInt("spark.yarn.max.worker.failures", math.max(args.numExecutors * 2, 3)))
-
-  private var registered = false
-
-  def run() {
-    // Set the web ui port to be ephemeral for yarn so we don't conflict with
-    // other spark processes running on the same box
-    System.setProperty("spark.ui.port", "0")
-
-    // When running the AM, the Spark master is always "yarn-cluster"
-    System.setProperty("spark.master", "yarn-cluster")
-
-    // Use priority 30 as it's higher than HDFS. It's the same priority MapReduce is using.
-    ShutdownHookManager.get().addShutdownHook(new AppMasterShutdownHook(this), 30)
-
-    appAttemptId = ApplicationMaster.getApplicationAttemptId()
-    logInfo("ApplicationAttemptId: " + appAttemptId)
-    isLastAMRetry = appAttemptId.getAttemptId() >= maxAppAttempts
-    amClient = AMRMClient.createAMRMClient()
-    amClient.init(yarnConf)
-    amClient.start()
-
-    // setup AmIpFilter for the SparkUI - do this before we start the UI
-    addAmIpFilter()
-
-    ApplicationMaster.register(this)
-
-    // Call this to force generation of secret so it gets populated into the
-    // Hadoop UGI. This has to happen before the startUserClass which does a
-    // doAs in order for the credentials to be passed on to the executor containers.
-    val securityMgr = new SecurityManager(sparkConf)
-
-    // 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.
-    waitForSparkContextInitialized()
-
-    // Do this after Spark master is up and SparkContext is created so that we can register UI Url.
-    synchronized {
-      if (!isFinished) {
-        registerApplicationMaster()
-        registered = true
-      }
-    }
-
-    // Allocate all containers
-    allocateExecutors()
-
-    // Launch thread that will heartbeat to the RM so it won't think the app has died.
-    launchReporterThread()
-
-    // Wait for the user class to finish
-    userThread.join()
-
-    System.exit(0)
-  }
-
-  // add the yarn amIpFilter that Yarn requires for properly securing the UI
-  private def addAmIpFilter() {
-    val amFilter = "org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter"
-    System.setProperty("spark.ui.filters", amFilter)
-    val proxy = WebAppUtils.getProxyHostAndPort(conf)
-    val parts : Array[String] = proxy.split(":")
-    val uriBase = "http://" + proxy +
-      System.getenv(ApplicationConstants.APPLICATION_WEB_PROXY_BASE_ENV)
-
-    val params = "PROXY_HOST=" + parts(0) + "," + "PROXY_URI_BASE=" + uriBase
-    System.setProperty(
-      "spark.org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter.params", params)
-  }
-
-  private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
-    logInfo("Registering the ApplicationMaster")
-    amClient.registerApplicationMaster(Utils.localHostName(), 0, uiAddress)
-  }
-
-  private def startUserClass(): Thread = {
-    logInfo("Starting the user JAR in a separate Thread")
-    System.setProperty("spark.executor.instances", args.numExecutors.toString)
-    val mainMethod = Class.forName(
-      args.userClass,
-      false,
-      Thread.currentThread.getContextClassLoader).getMethod("main", classOf[Array[String]])
-    val t = new Thread {
-      override def run() {
-        var succeeded = false
-        try {
-          // Copy
-          val mainArgs = new Array[String](args.userArgs.size)
-          args.userArgs.copyToArray(mainArgs, 0, args.userArgs.size)
-          mainMethod.invoke(null, mainArgs)
-          // Some apps have "System.exit(0)" at the end.  The user thread will stop here unless
-          // it has an uncaught exception thrown out.  It needs a shutdown hook to set SUCCEEDED.
-          succeeded = true
-        } finally {
-          logDebug("Finishing main")
-          isLastAMRetry = true
-          if (succeeded) {
-            ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
-          } else {
-            ApplicationMaster.this.finishApplicationMaster(FinalApplicationStatus.FAILED)
-          }
-        }
-      }
-    }
-    t.setName("Driver")
-    t.start()
-    t
-  }
-
-  // This needs to happen before allocateExecutors()
-  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 = sparkConf.getInt("spark.yarn.applicationMaster.waitTries", 10)
-        while (ApplicationMaster.sparkContextRef.get() == null && numTries < maxNumTries
-            && !isFinished) {
-          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.appUIHostPort
-          uiHistoryAddress = YarnSparkHadoopUtil.getUIHistoryAddress(sparkContext, sparkConf)
-          this.yarnAllocator = YarnAllocationHandler.newAllocator(
-            yarnConf,
-            amClient,
-            appAttemptId,
-            args,
-            sparkContext.preferredNodeLocationData,
-            sparkContext.getConf)
-        } else {
-          logWarning("Unable to retrieve SparkContext in spite of waiting for %d, maxNumTries = %d".
-            format(numTries * waitTime, maxNumTries))
-          this.yarnAllocator = YarnAllocationHandler.newAllocator(
-            yarnConf,
-            amClient,
-            appAttemptId,
-            args,
-            sparkContext.getConf)
-        }
-      }
-    }
-  }
-
-  private def allocateExecutors() {
-    try {
-      logInfo("Requesting" + args.numExecutors + " executors.")
-      // Wait until all containers have launched
-      yarnAllocator.addResourceRequests(args.numExecutors)
-      yarnAllocator.allocateResources()
-      // Exits the loop if the user thread exits.
-
-      while (yarnAllocator.getNumExecutorsRunning < args.numExecutors && userThread.isAlive
-          && !isFinished) {
-        checkNumExecutorsFailed()
-        allocateMissingExecutor()
-        yarnAllocator.allocateResources()
-        Thread.sleep(ApplicationMaster.ALLOCATE_HEARTBEAT_INTERVAL)
-      }
-    }
-    logInfo("All executors have launched.")
-  }
-
-  private def allocateMissingExecutor() {
-    val missingExecutorCount = args.numExecutors - yarnAllocator.getNumExecutorsRunning -
-      yarnAllocator.getNumPendingAllocate
-    if (missingExecutorCount > 0) {
-      logInfo("Allocating %d containers to make up for (potentially) lost containers".
-        format(missingExecutorCount))
-      yarnAllocator.addResourceRequests(missingExecutorCount)
-    }
-  }
-
-  private def checkNumExecutorsFailed() {
-    if (yarnAllocator.getNumExecutorsFailed >= maxNumExecutorFailures) {
-      logInfo("max number of executor failures reached")
-      finishApplicationMaster(FinalApplicationStatus.FAILED,
-        "max number of executor failures reached")
-      // make sure to stop the user thread
-      val sparkContext = ApplicationMaster.sparkContextRef.get()
-      if (sparkContext != null) {
-        logInfo("Invoking sc stop from checkNumExecutorsFailed")
-        sparkContext.stop()
-      } else {
-        logError("sparkContext is null when should shutdown")
-      }
-    }
-  }
-
-  private def launchReporterThread(): Thread = {
-    // Ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapses.
-    val expiryInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000)
-
-    // we want to be reasonably responsive without causing too many requests to RM.
-    val schedulerInterval =
-      sparkConf.getLong("spark.yarn.scheduler.heartbeat.interval-ms", 5000)
-
-    // must be <= timeoutInterval / 2.
-    val interval = math.max(0, math.min(expiryInterval / 2, schedulerInterval))
-
-    val t = new Thread {
-      override def run() {
-        while (userThread.isAlive && !isFinished) {
-          checkNumExecutorsFailed()
-          allocateMissingExecutor()
-          logDebug("Sending progress")
-          yarnAllocator.allocateResources()
-          Thread.sleep(interval)
-        }
-      }
-    }
-    // Setting to daemon status, though this is usually not a good idea.
-    t.setDaemon(true)
-    t.start()
-    logInfo("Started progress reporter thread - heartbeat interval : " + interval)
-    t
-  }
-
-  def finishApplicationMaster(status: FinalApplicationStatus, diagnostics: String = "") {
-    synchronized {
-      if (isFinished) {
-        return
-      }
-      isFinished = true
-
-      logInfo("Unregistering ApplicationMaster with " + status)
-      if (registered) {
-        amClient.unregisterApplicationMaster(status, diagnostics, uiHistoryAddress)
-      }
-    }
-  }
-
-  /**
-   * Clean up the staging directory.
-   */
-  private def cleanupStagingDir() {
-    var stagingDirPath: Path = null
-    try {
-      val preserveFiles = sparkConf.get("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 extends Logging {
-  // 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 ALLOCATE_HEARTBEAT_INTERVAL = 100
-
-  private val applicationMasters = new CopyOnWriteArrayList[ApplicationMaster]()
-
-  val sparkContextRef: AtomicReference[SparkContext] =
-    new AtomicReference[SparkContext](null)
-
-  def register(master: ApplicationMaster) {
-    applicationMasters.add(master)
-  }
-
-  /**
-   * Called from YarnClusterScheduler to notify the AM code that a SparkContext has been
-   * initialized in the user code.
-   */
-  def sparkContextInitialized(sc: SparkContext): Boolean = {
-    var modified = false
-    sparkContextRef.synchronized {
-      modified = sparkContextRef.compareAndSet(null, sc)
-      sparkContextRef.notifyAll()
-    }
-
-    // Add a shutdown hook - as a best 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 at least 'some' nodes to get allocated.
-    modified
-  }
-
-  def getApplicationAttemptId(): ApplicationAttemptId = {
-    val containerIdString = System.getenv(ApplicationConstants.Environment.CONTAINER_ID.name())
-    val containerId = ConverterUtils.toContainerId(containerIdString)
-    val appAttemptId = containerId.getApplicationAttemptId()
-    appAttemptId
-  }
-
-  def main(argStrings: Array[String]) {
-    SignalLogger.register(log)
-    val args = new ApplicationMasterArguments(argStrings)
-    SparkHadoopUtil.get.runAsSparkUser { () =>
-      new ApplicationMaster(args).run()
-    }
-  }
-}
diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ExecutorLauncher.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ExecutorLauncher.scala
deleted file mode 100644
index e093fe4ae6..0000000000
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/ExecutorLauncher.scala
+++ /dev/null
@@ -1,276 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.deploy.yarn
-
-import java.net.Socket
-import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.yarn.api.ApplicationConstants
-import org.apache.hadoop.yarn.api.records._
-import org.apache.hadoop.yarn.api.protocolrecords._
-import org.apache.hadoop.yarn.conf.YarnConfiguration
-import akka.actor._
-import akka.remote._
-import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkEnv}
-import org.apache.spark.util.{Utils, AkkaUtils}
-import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-import org.apache.spark.scheduler.SplitInfo
-import org.apache.hadoop.yarn.client.api.AMRMClient
-import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
-import org.apache.spark.deploy.SparkHadoopUtil
-import org.apache.hadoop.yarn.webapp.util.WebAppUtils
-
-/**
- * An application master that allocates executors on behalf of a driver that is running outside
- * the cluster.
- *
- * This is used only in yarn-client mode.
- */
-class ExecutorLauncher(args: ApplicationMasterArguments, conf: Configuration, sparkConf: SparkConf)
-  extends Logging {
-
-  def this(args: ApplicationMasterArguments, sparkConf: SparkConf) =
-    this(args, new Configuration(), sparkConf)
-
-  def this(args: ApplicationMasterArguments) = this(args, new SparkConf())
-
-  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 isFinished: Boolean = false
-  private var registered: Boolean = false
-
-  private var amClient: AMRMClient[ContainerRequest] = _
-
-  // Default to numExecutors * 2, with minimum of 3
-  private val maxNumExecutorFailures = sparkConf.getInt("spark.yarn.max.executor.failures",
-    sparkConf.getInt("spark.yarn.max.worker.failures", math.max(args.numExecutors * 2, 3)))
-
-  val securityManager = new SecurityManager(sparkConf)
-  val actorSystem: ActorSystem = AkkaUtils.createActorSystem("sparkYarnAM", Utils.localHostName, 0,
-    conf = sparkConf, securityManager = securityManager)._1
-  var actor: ActorRef = _
-
-  // This actor just working as a monitor to watch on Driver Actor.
-  class MonitorActor(driverUrl: String) extends Actor {
-
-    var driver: ActorSelection = _
-
-    override def preStart() {
-      logInfo("Listen to driver: " + driverUrl)
-      driver = context.actorSelection(driverUrl)
-      // Send a hello message to establish the connection, after which
-      // we can monitor Lifecycle Events.
-      driver ! "Hello"
-      context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent])
-    }
-
-    override def receive = {
-      case x: DisassociatedEvent =>
-        logInfo(s"Driver terminated or disconnected! Shutting down. $x")
-        driverClosed = true
-      case x: AddWebUIFilter =>
-        logInfo(s"Add WebUI Filter. $x")
-        driver ! x
-    }
-  }
-
-  def run() {
-    amClient = AMRMClient.createAMRMClient()
-    amClient.init(yarnConf)
-    amClient.start()
-
-    appAttemptId = ApplicationMaster.getApplicationAttemptId()
-    synchronized {
-      if (!isFinished) {
-        registerApplicationMaster()
-        registered = true
-      }
-    }
-
-    waitForSparkMaster()
-    addAmIpFilter()
-
-    // Allocate all containers
-    allocateExecutors()
-
-    // 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)
-    // 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)
-
-    reporterThread = launchReporterThread(interval)
-
-
-    // Wait for the reporter thread to Finish.
-    reporterThread.join()
-
-    finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
-    actorSystem.shutdown()
-
-    logInfo("Exited")
-    System.exit(0)
-  }
-
-  private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
-    val appUIAddress = sparkConf.get("spark.driver.appUIAddress", "")
-    logInfo(s"Registering the ApplicationMaster with appUIAddress: $appUIAddress")
-    amClient.registerApplicationMaster(Utils.localHostName(), 0, appUIAddress)
-  }
-
-  // add the yarn amIpFilter that Yarn requires for properly securing the UI
-  private def addAmIpFilter() {
-    val proxy = WebAppUtils.getProxyHostAndPort(conf)
-    val parts = proxy.split(":")
-    val proxyBase = System.getenv(ApplicationConstants.APPLICATION_WEB_PROXY_BASE_ENV)
-    val uriBase = "http://" + proxy + proxyBase
-    val amFilter = "PROXY_HOST=" + parts(0) + "," + "PROXY_URI_BASE=" + uriBase
-    val amFilterName = "org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter"
-    actor ! AddWebUIFilter(amFilterName, amFilter, proxyBase)
-  }
-
-  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)
-      }
-    }
-    sparkConf.set("spark.driver.host", driverHost)
-    sparkConf.set("spark.driver.port", driverPort.toString)
-
-    val driverUrl = "akka.tcp://%s@%s:%s/user/%s".format(
-      SparkEnv.driverActorSystemName,
-      driverHost,
-      driverPort.toString,
-      CoarseGrainedSchedulerBackend.ACTOR_NAME)
-
-    actor = actorSystem.actorOf(Props(new MonitorActor(driverUrl)), name = "YarnAM")
-  }
-
-
-  private def allocateExecutors() {
-    // TODO: 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,
-      sparkConf)
-
-    logInfo("Requesting " + args.numExecutors + " executors.")
-    // Wait until all containers have launched
-    yarnAllocator.addResourceRequests(args.numExecutors)
-    yarnAllocator.allocateResources()
-    while ((yarnAllocator.getNumExecutorsRunning < args.numExecutors) && (!driverClosed) &&
-        !isFinished) {
-      checkNumExecutorsFailed()
-      allocateMissingExecutor()
-      yarnAllocator.allocateResources()
-      Thread.sleep(100)
-    }
-
-    logInfo("All executors have launched.")
-  }
-
-  private def allocateMissingExecutor() {
-    val missingExecutorCount = args.numExecutors - yarnAllocator.getNumExecutorsRunning -
-      yarnAllocator.getNumPendingAllocate
-    if (missingExecutorCount > 0) {
-      logInfo("Allocating %d containers to make up for (potentially) lost containers".
-        format(missingExecutorCount))
-      yarnAllocator.addResourceRequests(missingExecutorCount)
-    }
-  }
-
-  private def checkNumExecutorsFailed() {
-    if (yarnAllocator.getNumExecutorsFailed >= maxNumExecutorFailures) {
-      finishApplicationMaster(FinalApplicationStatus.FAILED,
-        "max number of executor failures reached")
-    }
-  }
-
-  private def launchReporterThread(_sleepTime: Long): Thread = {
-    val sleepTime = if (_sleepTime <= 0) 0 else _sleepTime
-
-    val t = new Thread {
-      override def run() {
-        while (!driverClosed && !isFinished) {
-          checkNumExecutorsFailed()
-          allocateMissingExecutor()
-          logDebug("Sending progress")
-          yarnAllocator.allocateResources()
-          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
-  }
-
-  def finishApplicationMaster(status: FinalApplicationStatus, appMessage: String = "") {
-    synchronized {
-      if (isFinished) {
-        return
-      }
-      logInfo("Unregistering ApplicationMaster with " + status)
-      if (registered) {
-        val trackingUrl = sparkConf.get("spark.yarn.historyServer.address", "")
-        amClient.unregisterApplicationMaster(status, appMessage, trackingUrl)
-      }
-      isFinished = true
-    }
-  }
-
-}
-
-object ExecutorLauncher {
-  def main(argStrings: Array[String]) {
-    val args = new ApplicationMasterArguments(argStrings)
-    SparkHadoopUtil.get.runAsSparkUser { () =>
-      new ExecutorLauncher(args).run()
-    }
-  }
-}
diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
index 0a461749c8..4d51449899 100644
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
+++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
@@ -17,12 +17,9 @@
 
 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}
 
@@ -32,20 +29,13 @@ import org.apache.spark.scheduler.cluster.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.{Container, ContainerId}
 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 {
-  type AllocationType = Value
-  val HOST, RACK, ANY = Value
-}
+import org.apache.hadoop.yarn.util.Records
 
 // TODO:
 // Too many params.
@@ -61,16 +51,14 @@ object AllocationType extends Enumeration {
  * Acquires resources for executors from a ResourceManager and launches executors in new containers.
  */
 private[yarn] class YarnAllocationHandler(
-    val conf: Configuration,
-    val amClient: AMRMClient[ContainerRequest],
-    val appAttemptId: ApplicationAttemptId,
-    val maxExecutors: Int,
-    val executorMemory: Int,
-    val executorCores: Int,
-    val preferredHostToCount: Map[String, Int], 
-    val preferredRackToCount: Map[String, Int],
-    val sparkConf: SparkConf)
-  extends Logging {
+    conf: Configuration,
+    sparkConf: SparkConf,
+    amClient: AMRMClient[ContainerRequest],
+    appAttemptId: ApplicationAttemptId,
+    args: ApplicationMasterArguments,
+    preferredNodes: collection.Map[String, collection.Set[SplitInfo]])
+  extends YarnAllocator with Logging {
+
   // These three are locked on allocatedHostToContainersMap. Complementary data structures
   // allocatedHostToContainersMap : containers which are running : host, Set<containerid>
   // allocatedContainerToHostMap: container to host mapping.
@@ -92,7 +80,7 @@ private[yarn] class YarnAllocationHandler(
 
   // Additional memory overhead - in mb.
   private def memoryOverhead: Int = sparkConf.getInt("spark.yarn.executor.memoryOverhead",
-    YarnAllocationHandler.MEMORY_OVERHEAD)
+    YarnSparkHadoopUtil.DEFAULT_MEMORY_OVERHEAD)
 
   // Number of container requests that have been sent to, but not yet allocated by the
   // ApplicationMaster.
@@ -103,11 +91,15 @@ private[yarn] class YarnAllocationHandler(
   private val lastResponseId = new AtomicInteger()
   private val numExecutorsFailed = new AtomicInteger()
 
-  def getNumPendingAllocate: Int = numPendingAllocate.intValue
+  private val maxExecutors = args.numExecutors
+  private val executorMemory = args.executorMemory
+  private val executorCores = args.executorCores
+  private val (preferredHostToCount, preferredRackToCount) =
+    generateNodeToWeight(conf, preferredNodes)
 
-  def getNumExecutorsRunning: Int = numExecutorsRunning.intValue
+  override def getNumExecutorsRunning: Int = numExecutorsRunning.intValue
 
-  def getNumExecutorsFailed: Int = numExecutorsFailed.intValue
+  override def getNumExecutorsFailed: Int = numExecutorsFailed.intValue
 
   def isResourceConstraintSatisfied(container: Container): Boolean = {
     container.getResource.getMemory >= (executorMemory + memoryOverhead)
@@ -119,7 +111,9 @@ private[yarn] class YarnAllocationHandler(
     amClient.releaseAssignedContainer(containerId)
   }
 
-  def allocateResources() {
+  override def allocateResources() = {
+    addResourceRequests(maxExecutors - numPendingAllocate.get() - numExecutorsRunning.get())
+
     // 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
@@ -204,7 +198,7 @@ private[yarn] class YarnAllocationHandler(
 
         // For rack local containers
         if (remainingContainers != null) {
-          val rack = YarnAllocationHandler.lookupRack(conf, candidateHost)
+          val rack = YarnSparkHadoopUtil.lookupRack(conf, candidateHost)
           if (rack != null) {
             val maxExpectedRackCount = preferredRackToCount.getOrElse(rack, 0)
             val requiredRackCount = maxExpectedRackCount - allocatedContainersOnRack(rack) -
@@ -273,7 +267,7 @@ private[yarn] class YarnAllocationHandler(
           // To be safe, remove the container from `pendingReleaseContainers`.
           pendingReleaseContainers.remove(containerId)
 
-          val rack = YarnAllocationHandler.lookupRack(conf, executorHostname)
+          val rack = YarnSparkHadoopUtil.lookupRack(conf, executorHostname)
           allocatedHostToContainersMap.synchronized {
             val containerSet = allocatedHostToContainersMap.getOrElseUpdate(executorHostname,
               new HashSet[ContainerId]())
@@ -360,7 +354,7 @@ private[yarn] class YarnAllocationHandler(
             allocatedContainerToHostMap.remove(containerId)
 
             // TODO: Move this part outside the synchronized block?
-            val rack = YarnAllocationHandler.lookupRack(conf, host)
+            val rack = YarnSparkHadoopUtil.lookupRack(conf, host)
             if (rack != null) {
               val rackCount = allocatedRackCount.getOrElse(rack, 0) - 1
               if (rackCount > 0) {
@@ -393,9 +387,9 @@ private[yarn] class YarnAllocationHandler(
 
     for (container <- hostContainers) {
       val candidateHost = container.getNodes.last
-      assert(YarnAllocationHandler.ANY_HOST != candidateHost)
+      assert(YarnSparkHadoopUtil.ANY_HOST != candidateHost)
 
-      val rack = YarnAllocationHandler.lookupRack(conf, candidateHost)
+      val rack = YarnSparkHadoopUtil.lookupRack(conf, candidateHost)
       if (rack != null) {
         var count = rackToCounts.getOrElse(rack, 0)
         count += 1
@@ -409,7 +403,7 @@ private[yarn] class YarnAllocationHandler(
         AllocationType.RACK,
         rack,
         count,
-        YarnAllocationHandler.PRIORITY)
+        YarnSparkHadoopUtil.RM_REQUEST_PRIORITY)
     }
 
     requestedContainers
@@ -431,7 +425,7 @@ private[yarn] class YarnAllocationHandler(
     retval
   }
 
-  def addResourceRequests(numExecutors: Int) {
+  private def addResourceRequests(numExecutors: Int) {
     val containerRequests: List[ContainerRequest] =
       if (numExecutors <= 0 || preferredHostToCount.isEmpty) {
         logDebug("numExecutors: " + numExecutors + ", host preferences: " +
@@ -440,9 +434,9 @@ private[yarn] class YarnAllocationHandler(
           AllocationType.ANY,
           resource = null,
           numExecutors,
-          YarnAllocationHandler.PRIORITY).toList
+          YarnSparkHadoopUtil.RM_REQUEST_PRIORITY).toList
       } else {
-        // Request for all hosts in preferred nodes and for numExecutors - 
+        // Request for all hosts in preferred nodes and for numExecutors -
         // candidates.size, request by default allocation policy.
         val hostContainerRequests = new ArrayBuffer[ContainerRequest](preferredHostToCount.size)
         for ((candidateHost, candidateCount) <- preferredHostToCount) {
@@ -453,7 +447,7 @@ private[yarn] class YarnAllocationHandler(
               AllocationType.HOST,
               candidateHost,
               requiredCount,
-              YarnAllocationHandler.PRIORITY)
+              YarnSparkHadoopUtil.RM_REQUEST_PRIORITY)
           }
         }
         val rackContainerRequests: List[ContainerRequest] = createRackResourceRequests(
@@ -463,7 +457,7 @@ private[yarn] class YarnAllocationHandler(
           AllocationType.ANY,
           resource = null,
           numExecutors,
-          YarnAllocationHandler.PRIORITY)
+          YarnSparkHadoopUtil.RM_REQUEST_PRIORITY)
 
         val containerRequestBuffer = new ArrayBuffer[ContainerRequest](
           hostContainerRequests.size + rackContainerRequests.size() + anyContainerRequests.size)
@@ -512,7 +506,7 @@ private[yarn] class YarnAllocationHandler(
     // 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(YarnSparkHadoopUtil.ANY_HOST != resource)
         val hostname = resource
         val nodeLocal = constructContainerRequests(
           Array(hostname),
@@ -521,7 +515,7 @@ private[yarn] class YarnAllocationHandler(
           priority)
 
         // Add `hostname` to the global (singleton) host->rack mapping in YarnAllocationHandler.
-        YarnAllocationHandler.populateRackInfo(conf, hostname)
+        YarnSparkHadoopUtil.populateRackInfo(conf, hostname)
         nodeLocal
       }
       case AllocationType.RACK => {
@@ -554,88 +548,6 @@ private[yarn] class YarnAllocationHandler(
     }
     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,
-      sparkConf: SparkConf
-    ): YarnAllocationHandler = {
-    new YarnAllocationHandler(
-      conf,
-      amClient,
-      appAttemptId,
-      args.numExecutors, 
-      args.executorMemory,
-      args.executorCores,
-      Map[String, Int](),
-      Map[String, Int](),
-      sparkConf)
-  }
-
-  def newAllocator(
-      conf: Configuration,
-      amClient: AMRMClient[ContainerRequest],
-      appAttemptId: ApplicationAttemptId,
-      args: ApplicationMasterArguments,
-      map: collection.Map[String,
-      collection.Set[SplitInfo]],
-      sparkConf: SparkConf
-    ): YarnAllocationHandler = {
-    val (hostToSplitCount, rackToSplitCount) = generateNodeToWeight(conf, map)
-    new YarnAllocationHandler(
-      conf,
-      amClient,
-      appAttemptId,
-      args.numExecutors, 
-      args.executorMemory,
-      args.executorCores,
-      hostToSplitCount,
-      rackToSplitCount,
-      sparkConf)
-  }
-
-  def newAllocator(
-      conf: Configuration,
-      amClient: AMRMClient[ContainerRequest],
-      appAttemptId: ApplicationAttemptId,
-      maxExecutors: Int,
-      executorMemory: Int,
-      executorCores: Int,
-      map: collection.Map[String, collection.Set[SplitInfo]],
-      sparkConf: SparkConf
-    ): YarnAllocationHandler = {
-    val (hostToCount, rackToCount) = generateNodeToWeight(conf, map)
-    new YarnAllocationHandler(
-      conf,
-      amClient,
-      appAttemptId,
-      maxExecutors,
-      executorMemory,
-      executorCores,
-      hostToCount,
-      rackToCount,
-      sparkConf)
-  }
 
   // A simple method to copy the split info map.
   private def generateNodeToWeight(
@@ -654,7 +566,7 @@ object YarnAllocationHandler {
       val hostCount = hostToCount.getOrElse(host, 0)
       hostToCount.put(host, hostCount + splits.size)
 
-      val rack = lookupRack(conf, host)
+      val rack = YarnSparkHadoopUtil.lookupRack(conf, host)
       if (rack != null){
         val rackCount = rackToCount.getOrElse(host, 0)
         rackToCount.put(host, rackCount + splits.size)
@@ -664,42 +576,4 @@ object YarnAllocationHandler {
     (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/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala
new file mode 100644
index 0000000000..e8b8d9bc72
--- /dev/null
+++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF 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.{Map, Set}
+
+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.util.ConverterUtils
+import org.apache.hadoop.yarn.webapp.util.WebAppUtils
+
+import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.scheduler.SplitInfo
+import org.apache.spark.util.Utils
+
+
+/**
+ * YarnRMClient implementation for the Yarn stable API.
+ */
+private class YarnRMClientImpl(args: ApplicationMasterArguments) extends YarnRMClient with Logging {
+
+  private var amClient: AMRMClient[ContainerRequest] = _
+  private var uiHistoryAddress: String = _
+
+  override def register(
+      conf: YarnConfiguration,
+      sparkConf: SparkConf,
+      preferredNodeLocations: Map[String, Set[SplitInfo]],
+      uiAddress: String,
+      uiHistoryAddress: String) = {
+    amClient = AMRMClient.createAMRMClient()
+    amClient.init(conf)
+    amClient.start()
+    this.uiHistoryAddress = uiHistoryAddress
+
+    logInfo("Registering the ApplicationMaster")
+    amClient.registerApplicationMaster(Utils.localHostName(), 0, uiAddress)
+    new YarnAllocationHandler(conf, sparkConf, amClient, getAttemptId(), args,
+      preferredNodeLocations)
+  }
+
+  override def shutdown(status: FinalApplicationStatus, diagnostics: String = "") =
+    amClient.unregisterApplicationMaster(status, diagnostics, uiHistoryAddress)
+
+  override def getAttemptId() = {
+    val containerIdString = System.getenv(ApplicationConstants.Environment.CONTAINER_ID.name())
+    val containerId = ConverterUtils.toContainerId(containerIdString)
+    val appAttemptId = containerId.getApplicationAttemptId()
+    appAttemptId
+  }
+
+  override def getProxyHostAndPort(conf: YarnConfiguration) = WebAppUtils.getProxyHostAndPort(conf)
+
+  override def getMaxRegAttempts(conf: YarnConfiguration) =
+    conf.getInt(YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS)
+
+}