Yarn Client refactor

2 files changed, 18 insertions, 358 deletions

diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index 51d9adb9d4..fef4702c66 100644
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -17,20 +17,10 @@
 
 package org.apache.spark.deploy.yarn
 
-import java.net.{InetAddress, UnknownHostException, URI}
 import java.nio.ByteBuffer
 
-import scala.collection.JavaConversions._
-import scala.collection.mutable.HashMap
-import scala.collection.mutable.Map
-
 import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.fs.{FileContext, FileStatus, FileSystem, Path, FileUtil}
-import org.apache.hadoop.fs.permission.FsPermission;
 import org.apache.hadoop.io.DataOutputBuffer
-import org.apache.hadoop.mapred.Master
-import org.apache.hadoop.net.NetUtils
-import org.apache.hadoop.security.UserGroupInformation
 import org.apache.hadoop.yarn.api._
 import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
 import org.apache.hadoop.yarn.api.protocolrecords._
@@ -41,8 +31,6 @@ import org.apache.hadoop.yarn.ipc.YarnRPC
 import org.apache.hadoop.yarn.util.{Apps, Records}
 
 import org.apache.spark.{Logging, SparkConf}
-import org.apache.spark.util.Utils
-import org.apache.spark.deploy.SparkHadoopUtil
 
 
 /**
@@ -50,24 +38,19 @@ import org.apache.spark.deploy.SparkHadoopUtil
  * Client submits an application to the global ResourceManager to launch Spark's ApplicationMaster,
  * which will launch a Spark master process and negotiate resources throughout its duration.
  */
-class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf)
-  extends YarnClientImpl with Logging {
+class Client(clientArgs: ClientArguments, hadoopConf: Configuration, spConf: SparkConf)
+  extends YarnClientImpl with ClientBase with Logging {
 
-  def this(args: ClientArguments, sparkConf: SparkConf) =
-    this(args, new Configuration(), sparkConf)
+  def this(clientArgs: ClientArguments, spConf: SparkConf) =
+    this(clientArgs, new Configuration(), spConf)
 
-  def this(args: ClientArguments) = this(args, new SparkConf())
+  def this(clientArgs: ClientArguments) = this(clientArgs, new SparkConf())
 
+  val args = clientArgs
+  val conf = hadoopConf
+  val sparkConf = spConf
   var rpc: YarnRPC = YarnRPC.create(conf)
   val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
-  val credentials = UserGroupInformation.getCurrentUser().getCredentials()
-  private val SPARK_STAGING: String = ".sparkStaging"
-  private val distCacheMgr = new ClientDistributedCacheManager()
-
-  // Staging directory is private! -> rwx--------
-  val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700: Short)
-  // App files are world-wide readable and owner writable -> rw-r--r--
-  val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644: Short)
 
   def runApp(): ApplicationId = {
     validateArgs()
@@ -117,29 +100,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf)
     System.exit(0)
   }
 
-  // TODO(harvey): This could just go in ClientArguments.
-  def validateArgs() = {
-    Map(
-      (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!",
-      (args.userJar == null) -> "Error: You must specify a user jar!",
-      (args.userClass == null) -> "Error: You must specify a user class!",
-      (args.numWorkers <= 0) -> "Error: You must specify at least 1 worker!",
-      (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be" +
-        "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD),
-      (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size" +
-        "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString)
-    ).foreach { case(cond, errStr) =>
-      if (cond) {
-        logError(errStr)
-        args.printUsageAndExit(1)
-      }
-    }
-  }
-
-  def getAppStagingDir(appId: ApplicationId): String = {
-    SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR
-  }
-
   def logClusterResourceDetails() {
     val clusterMetrics: YarnClusterMetrics = super.getYarnClusterMetrics
     logInfo("Got Cluster metric info from ApplicationsManager (ASM), number of NodeManagers: " +
@@ -148,292 +108,27 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf)
     val queueInfo: QueueInfo = super.getQueueInfo(args.amQueue)
     logInfo( """Queue info ... queueName: %s, queueCurrentCapacity: %s, queueMaxCapacity: %s,
       queueApplicationCount = %s, queueChildQueueCount = %s""".format(
-        queueInfo.getQueueName,
-        queueInfo.getCurrentCapacity,
-        queueInfo.getMaximumCapacity,
-        queueInfo.getApplications.size,
-        queueInfo.getChildQueues.size))
-  }
-
-  def verifyClusterResources(app: GetNewApplicationResponse) = {
-    val maxMem = app.getMaximumResourceCapability().getMemory()
-    logInfo("Max mem capabililty of a single resource in this cluster " + maxMem)
-
-    // If we have requested more then the clusters max for a single resource then exit.
-    if (args.workerMemory > maxMem) {
-      logError("Required worker memory (%d MB), is above the max threshold (%d MB) of this cluster.".
-        format(args.workerMemory, maxMem))
-      System.exit(1)
-    }
-    val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD
-    if (amMem > maxMem) {
-      logError("Required AM memory (%d) is above the max threshold (%d) of this cluster".
-        format(args.amMemory, maxMem))
-      System.exit(1)
-    }
-
-    // We could add checks to make sure the entire cluster has enough resources but that involves
-    // getting all the node reports and computing ourselves.
-  }
-
-  /** See if two file systems are the same or not. */
-  private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = {
-    val srcUri = srcFs.getUri()
-    val dstUri = destFs.getUri()
-    if (srcUri.getScheme() == null) {
-      return false
-    }
-    if (!srcUri.getScheme().equals(dstUri.getScheme())) {
-      return false
-    }
-    var srcHost = srcUri.getHost()
-    var dstHost = dstUri.getHost()
-    if ((srcHost != null) && (dstHost != null)) {
-      try {
-        srcHost = InetAddress.getByName(srcHost).getCanonicalHostName()
-        dstHost = InetAddress.getByName(dstHost).getCanonicalHostName()
-      } catch {
-        case e: UnknownHostException =>
-          return false
-      }
-      if (!srcHost.equals(dstHost)) {
-        return false
-      }
-    } else if (srcHost == null && dstHost != null) {
-      return false
-    } else if (srcHost != null && dstHost == null) {
-      return false
-    }
-    //check for ports
-    if (srcUri.getPort() != dstUri.getPort()) {
-      return false
-    }
-
-    true
+      queueInfo.getQueueName,
+      queueInfo.getCurrentCapacity,
+      queueInfo.getMaximumCapacity,
+      queueInfo.getApplications.size,
+      queueInfo.getChildQueues.size))
   }
 
-  /** Copy the file into HDFS if needed. */
-  private def copyRemoteFile(
-      dstDir: Path,
-      originalPath: Path,
-      replication: Short,
-      setPerms: Boolean = false): Path = {
-    val fs = FileSystem.get(conf)
-    val remoteFs = originalPath.getFileSystem(conf)
-    var newPath = originalPath
-    if (! compareFs(remoteFs, fs)) {
-      newPath = new Path(dstDir, originalPath.getName())
-      logInfo("Uploading " + originalPath + " to " + newPath)
-      FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf)
-      fs.setReplication(newPath, replication)
-      if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION))
-    }
-    // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific
-    // version shows the specific version in the distributed cache configuration
-    val qualPath = fs.makeQualified(newPath)
-    val fc = FileContext.getFileContext(qualPath.toUri(), conf)
-    val destPath = fc.resolvePath(qualPath)
-    destPath
-  }
-
-  def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = {
-    logInfo("Preparing Local resources")
-    // Upload Spark and the application JAR to the remote file system if necessary. Add them as
-    // local resources to the application master.
-    val fs = FileSystem.get(conf)
-
-    val delegTokenRenewer = Master.getMasterPrincipal(conf)
-    if (UserGroupInformation.isSecurityEnabled()) {
-      if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) {
-        logError("Can't get Master Kerberos principal for use as renewer")
-        System.exit(1)
-      }
-    }
-    val dst = new Path(fs.getHomeDirectory(), appStagingDir)
-    val replication = sparkConf.getInt("spark.yarn.submit.file.replication", 3).toShort
-
-    if (UserGroupInformation.isSecurityEnabled()) {
-      val dstFs = dst.getFileSystem(conf)
-      dstFs.addDelegationTokens(delegTokenRenewer, credentials)
-    }
-
-    val localResources = HashMap[String, LocalResource]()
-    FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION))
-
-    val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
-
-    Map(
-      Client.SPARK_JAR -> System.getenv("SPARK_JAR"), Client.APP_JAR -> args.userJar,
-      Client.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF")
-    ).foreach { case(destName, _localPath) =>
-      val localPath: String = if (_localPath != null) _localPath.trim() else ""
-      if (! localPath.isEmpty()) {
-        var localURI = new URI(localPath)
-        // If not specified assume these are in the local filesystem to keep behavior like Hadoop
-        if (localURI.getScheme() == null) {
-          localURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(localPath)).toString)
-        }
-        val setPermissions = if (destName.equals(Client.APP_JAR)) true else false
-        val destPath = copyRemoteFile(dst, new Path(localURI), replication, setPermissions)
-        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
-          destName, statCache)
-      }
-    }
-
-    // Handle jars local to the ApplicationMaster.
-    if ((args.addJars != null) && (!args.addJars.isEmpty())){
-      args.addJars.split(',').foreach { case file: String =>
-        val localURI = new URI(file.trim())
-        val localPath = new Path(localURI)
-        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
-        val destPath = copyRemoteFile(dst, localPath, replication)
-        // Only add the resource to the Spark ApplicationMaster.
-        val appMasterOnly = true
-        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
-          linkname, statCache, appMasterOnly)
-      }
-    }
-
-    // Handle any distributed cache files
-    if ((args.files != null) && (!args.files.isEmpty())){
-      args.files.split(',').foreach { case file: String =>
-        val localURI = new URI(file.trim())
-        val localPath = new Path(localURI)
-        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
-        val destPath = copyRemoteFile(dst, localPath, replication)
-        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
-          linkname, statCache)
-      }
-    }
-
-    // Handle any distributed cache archives
-    if ((args.archives != null) && (!args.archives.isEmpty())) {
-      args.archives.split(',').foreach { case file:String =>
-        val localURI = new URI(file.trim())
-        val localPath = new Path(localURI)
-        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
-        val destPath = copyRemoteFile(dst, localPath, replication)
-        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE,
-          linkname, statCache)
-      }
-    }
-
-    UserGroupInformation.getCurrentUser().addCredentials(credentials)
-    localResources
-  }
-
-  def setupLaunchEnv(
-      localResources: HashMap[String, LocalResource],
-      stagingDir: String): HashMap[String, String] = {
-    logInfo("Setting up the launch environment")
-    val log4jConfLocalRes = localResources.getOrElse(Client.LOG4J_PROP, null)
-
-    val env = new HashMap[String, String]()
-
-    Client.populateClasspath(yarnConf, sparkConf, log4jConfLocalRes != null, env)
-    env("SPARK_YARN_MODE") = "true"
-    env("SPARK_YARN_STAGING_DIR") = stagingDir
-
-    // Set the environment variables to be passed on to the Workers.
-    distCacheMgr.setDistFilesEnv(env)
-    distCacheMgr.setDistArchivesEnv(env)
-
-    // Allow users to specify some environment variables.
-    Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
-
-    // Add each SPARK_* key to the environment.
-    System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
-
-    env
-  }
-
-  def userArgsToString(clientArgs: ClientArguments): String = {
-    val prefix = " --args "
-    val args = clientArgs.userArgs
-    val retval = new StringBuilder()
-    for (arg <- args) {
-      retval.append(prefix).append(" '").append(arg).append("' ")
-    }
-    retval.toString
-  }
-
-  def createContainerLaunchContext(
-      newApp: GetNewApplicationResponse,
-      localResources: HashMap[String, LocalResource],
-      env: HashMap[String, String]): ContainerLaunchContext = {
-    logInfo("Setting up container launch context")
-    val amContainer = Records.newRecord(classOf[ContainerLaunchContext])
-    amContainer.setLocalResources(localResources)
-    amContainer.setEnvironment(env)
-
+  def calculateAMMemory(newApp: GetNewApplicationResponse) :Int = {
     // TODO: Need a replacement for the following code to fix -Xmx?
     // val minResMemory: Int = newApp.getMinimumResourceCapability().getMemory()
     // var amMemory = ((args.amMemory / minResMemory) * minResMemory) +
     //  ((if ((args.amMemory % minResMemory) == 0) 0 else minResMemory) -
     //    YarnAllocationHandler.MEMORY_OVERHEAD)
+    args.amMemory
+  }
 
-    // Extra options for the JVM
-    var JAVA_OPTS = ""
-
-    // Add Xmx for AM memory
-    JAVA_OPTS += "-Xmx" + args.amMemory + "m"
-
-    val tmpDir = new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR)
-    JAVA_OPTS += " -Djava.io.tmpdir=" + tmpDir
-
-    // TODO: Remove once cpuset version is pushed out.
-    // The context is, default gc for server class machines ends up using all cores to do gc -
-    // hence if there are multiple containers in same node, Spark GC affects all other containers'
-    // performance (which can be that of other Spark containers)
-    // Instead of using this, rely on cpusets by YARN to enforce "proper" Spark behavior in
-    // multi-tenant environments. Not sure how default Java GC behaves if it is limited to subset
-    // of cores on a node.
-    val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") &&
-      java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))
-    if (useConcurrentAndIncrementalGC) {
-      // In our expts, using (default) throughput collector has severe perf ramifications in
-      // multi-tenant machines
-      JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
-      JAVA_OPTS += " -XX:+CMSIncrementalMode "
-      JAVA_OPTS += " -XX:+CMSIncrementalPacing "
-      JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 "
-      JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 "
-    }
-
-    if (env.isDefinedAt("SPARK_JAVA_OPTS")) {
-      JAVA_OPTS += " " + env("SPARK_JAVA_OPTS")
-    }
-
-    // Command for the ApplicationMaster
-    var javaCommand = "java"
-    val javaHome = System.getenv("JAVA_HOME")
-    if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) {
-      javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
-    }
-
-    val commands = List[String](
-      javaCommand +
-      " -server " +
-      JAVA_OPTS +
-      " " + args.amClass +
-      " --class " + args.userClass +
-      " --jar " + args.userJar +
-      userArgsToString(args) +
-      " --worker-memory " + args.workerMemory +
-      " --worker-cores " + args.workerCores +
-      " --num-workers " + args.numWorkers +
-      " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" +
-      " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
-
-    logInfo("Command for starting the Spark ApplicationMaster: " + commands(0))
-    amContainer.setCommands(commands)
-
+  def setupSecurityToken(amContainer :ContainerLaunchContext) = {
     // Setup security tokens.
     val dob = new DataOutputBuffer()
     credentials.writeTokenStorageToStream(dob)
     amContainer.setTokens(ByteBuffer.wrap(dob.getData()))
-
-    amContainer
   }
 
   def submitApp(appContext: ApplicationSubmissionContext) = {
@@ -477,9 +172,6 @@ class Client(args: ClientArguments, conf: Configuration, sparkConf: SparkConf)
 }
 
 object Client {
-  val SPARK_JAR: String = "spark.jar"
-  val APP_JAR: String = "app.jar"
-  val LOG4J_PROP: String = "log4j.properties"
 
   def main(argStrings: Array[String]) {
     // Set an env variable indicating we are running in YARN mode.
@@ -492,36 +184,4 @@ object Client {
     new Client(args, sparkConf).run()
   }
 
-  // Based on code from org.apache.hadoop.mapreduce.v2.util.MRApps
-  def populateHadoopClasspath(conf: Configuration, env: HashMap[String, String]) {
-    for (c <- conf.getStrings(YarnConfiguration.YARN_APPLICATION_CLASSPATH)) {
-      Apps.addToEnvironment(env, Environment.CLASSPATH.name, c.trim)
-    }
-  }
-
-  def populateClasspath(conf: Configuration, sparkConf: SparkConf, addLog4j: Boolean, env: HashMap[String, String]) {
-    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
-    // If log4j present, ensure ours overrides all others
-    if (addLog4j) {
-      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
-        Path.SEPARATOR + LOG4J_PROP)
-    }
-    // Normally the users app.jar is last in case conflicts with spark jars
-    val userClasspathFirst = sparkConf.get("spark.yarn.user.classpath.first", "false")
-      .toBoolean
-    if (userClasspathFirst) {
-      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
-        Path.SEPARATOR + APP_JAR)
-    }
-    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
-      Path.SEPARATOR + SPARK_JAR)
-    Client.populateHadoopClasspath(conf, env)
-
-    if (!userClasspathFirst) {
-      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
-        Path.SEPARATOR + APP_JAR)
-    }
-    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
-      Path.SEPARATOR + "*")
-  }
 }
diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
index b7699050bb..06d40dfe7f 100644
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
+++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
@@ -198,7 +198,7 @@ class WorkerRunnable(
   def prepareEnvironment: HashMap[String, String] = {
     val env = new HashMap[String, String]()
 
-    Client.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env)
+    ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env)
 
     // Allow users to specify some environment variables
     Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))