Yarn Client refactor

1 files changed, 411 insertions, 0 deletions

diff --git a/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala
new file mode 100644
index 0000000000..96e998ab61
--- /dev/null
+++ b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala
@@ -0,0 +1,411 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.net.{InetAddress, UnknownHostException, URI}
+import java.nio.ByteBuffer
+
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
+import scala.collection.mutable.Map
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs._
+import org.apache.hadoop.fs.permission.FsPermission;
+import org.apache.hadoop.io.DataOutputBuffer
+import org.apache.hadoop.mapred.Master
+import org.apache.hadoop.net.NetUtils
+import org.apache.hadoop.security.UserGroupInformation
+import org.apache.hadoop.yarn.api._
+import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
+import org.apache.hadoop.yarn.api.protocolrecords._
+import org.apache.hadoop.yarn.api.records._
+import org.apache.hadoop.yarn.conf.YarnConfiguration
+import org.apache.hadoop.yarn.ipc.YarnRPC
+import org.apache.hadoop.yarn.util.{Records, Apps}
+
+import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.util.Utils
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.hadoop.yarn.api.ApplicationConstants.Environment
+
+
+/**
+ * The entry point (starting in Client#main() and Client#run()) for launching Spark on YARN. The
+ * Client submits an application to the global ResourceManager to launch Spark's ApplicationMaster,
+ * which will launch a Spark master process and negotiate resources throughout its duration.
+ */
+trait ClientBase extends Logging {
+  val args: ClientArguments
+  val conf: Configuration
+  val sparkConf: SparkConf
+
+  //var rpc: YarnRPC = YarnRPC.create(conf)
+  val yarnConf: YarnConfiguration
+  val credentials = UserGroupInformation.getCurrentUser().getCredentials()
+  private val SPARK_STAGING: String = ".sparkStaging"
+  private val distCacheMgr = new ClientDistributedCacheManager()
+
+  // Staging directory is private! -> rwx--------
+  val STAGING_DIR_PERMISSION: FsPermission = FsPermission.createImmutable(0700: Short)
+  // App files are world-wide readable and owner writable -> rw-r--r--
+  val APP_FILE_PERMISSION: FsPermission = FsPermission.createImmutable(0644: Short)
+
+  // TODO(harvey): This could just go in ClientArguments.
+  def validateArgs() = {
+    Map(
+      (System.getenv("SPARK_JAR") == null) -> "Error: You must set SPARK_JAR environment variable!",
+      (args.userJar == null) -> "Error: You must specify a user jar!",
+      (args.userClass == null) -> "Error: You must specify a user class!",
+      (args.numWorkers <= 0) -> "Error: You must specify at least 1 worker!",
+      (args.amMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: AM memory size must be" +
+        "greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD),
+      (args.workerMemory <= YarnAllocationHandler.MEMORY_OVERHEAD) -> ("Error: Worker memory size" +
+        "must be greater than: " + YarnAllocationHandler.MEMORY_OVERHEAD.toString)
+    ).foreach { case(cond, errStr) =>
+      if (cond) {
+        logError(errStr)
+        args.printUsageAndExit(1)
+      }
+    }
+  }
+
+  def getAppStagingDir(appId: ApplicationId): String = {
+    SPARK_STAGING + Path.SEPARATOR + appId.toString() + Path.SEPARATOR
+  }
+
+  def verifyClusterResources(app: GetNewApplicationResponse) = {
+    val maxMem = app.getMaximumResourceCapability().getMemory()
+    logInfo("Max mem capabililty of a single resource in this cluster " + maxMem)
+
+    // If we have requested more then the clusters max for a single resource then exit.
+    if (args.workerMemory > maxMem) {
+      logError("Required worker memory (%d MB), is above the max threshold (%d MB) of this cluster.".
+        format(args.workerMemory, maxMem))
+      System.exit(1)
+    }
+    val amMem = args.amMemory + YarnAllocationHandler.MEMORY_OVERHEAD
+    if (amMem > maxMem) {
+      logError("Required AM memory (%d) is above the max threshold (%d) of this cluster".
+        format(args.amMemory, maxMem))
+      System.exit(1)
+    }
+
+    // We could add checks to make sure the entire cluster has enough resources but that involves
+    // getting all the node reports and computing ourselves.
+  }
+
+  /** See if two file systems are the same or not. */
+  private def compareFs(srcFs: FileSystem, destFs: FileSystem): Boolean = {
+    val srcUri = srcFs.getUri()
+    val dstUri = destFs.getUri()
+    if (srcUri.getScheme() == null) {
+      return false
+    }
+    if (!srcUri.getScheme().equals(dstUri.getScheme())) {
+      return false
+    }
+    var srcHost = srcUri.getHost()
+    var dstHost = dstUri.getHost()
+    if ((srcHost != null) && (dstHost != null)) {
+      try {
+        srcHost = InetAddress.getByName(srcHost).getCanonicalHostName()
+        dstHost = InetAddress.getByName(dstHost).getCanonicalHostName()
+      } catch {
+        case e: UnknownHostException =>
+          return false
+      }
+      if (!srcHost.equals(dstHost)) {
+        return false
+      }
+    } else if (srcHost == null && dstHost != null) {
+      return false
+    } else if (srcHost != null && dstHost == null) {
+      return false
+    }
+    //check for ports
+    if (srcUri.getPort() != dstUri.getPort()) {
+      return false
+    }
+    return true
+  }
+
+  /** Copy the file into HDFS if needed. */
+  private def copyRemoteFile(
+      dstDir: Path,
+      originalPath: Path,
+      replication: Short,
+      setPerms: Boolean = false): Path = {
+    val fs = FileSystem.get(conf)
+    val remoteFs = originalPath.getFileSystem(conf)
+    var newPath = originalPath
+    if (! compareFs(remoteFs, fs)) {
+      newPath = new Path(dstDir, originalPath.getName())
+      logInfo("Uploading " + originalPath + " to " + newPath)
+      FileUtil.copy(remoteFs, originalPath, fs, newPath, false, conf)
+      fs.setReplication(newPath, replication)
+      if (setPerms) fs.setPermission(newPath, new FsPermission(APP_FILE_PERMISSION))
+    }
+    // Resolve any symlinks in the URI path so using a "current" symlink to point to a specific
+    // version shows the specific version in the distributed cache configuration
+    val qualPath = fs.makeQualified(newPath)
+    val fc = FileContext.getFileContext(qualPath.toUri(), conf)
+    val destPath = fc.resolvePath(qualPath)
+    destPath
+  }
+
+  def qualifyForLocal(localURI : URI): Path = {
+    var qualifiedURI = localURI
+    // If not specified assume these are in the local filesystem to keep behavior like Hadoop
+    if (qualifiedURI.getScheme() == null) {
+      qualifiedURI = new URI(FileSystem.getLocal(conf).makeQualified(new Path(qualifiedURI)).toString)
+    }
+    val qualPath = new Path(qualifiedURI)
+    qualPath
+  }
+
+  def prepareLocalResources(appStagingDir: String): HashMap[String, LocalResource] = {
+    logInfo("Preparing Local resources")
+    // Upload Spark and the application JAR to the remote file system if necessary. Add them as
+    // local resources to the application master.
+    val fs = FileSystem.get(conf)
+
+    val delegTokenRenewer = Master.getMasterPrincipal(conf)
+    if (UserGroupInformation.isSecurityEnabled()) {
+      if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) {
+        logError("Can't get Master Kerberos principal for use as renewer")
+        System.exit(1)
+      }
+    }
+    val dst = new Path(fs.getHomeDirectory(), appStagingDir)
+    val replication = sparkConf.getInt("spark.yarn.submit.file.replication", 3).toShort
+
+    if (UserGroupInformation.isSecurityEnabled()) {
+      val dstFs = dst.getFileSystem(conf)
+      dstFs.addDelegationTokens(delegTokenRenewer, credentials)
+    }
+
+    val localResources = HashMap[String, LocalResource]()
+    FileSystem.mkdirs(fs, dst, new FsPermission(STAGING_DIR_PERMISSION))
+
+    val statCache: Map[URI, FileStatus] = HashMap[URI, FileStatus]()
+
+    Map(
+      ClientBase.SPARK_JAR -> System.getenv("SPARK_JAR"), ClientBase.APP_JAR -> args.userJar,
+      ClientBase.LOG4J_PROP -> System.getenv("SPARK_LOG4J_CONF")
+    ).foreach { case(destName, _localPath) =>
+      val localPath: String = if (_localPath != null) _localPath.trim() else ""
+      if (! localPath.isEmpty()) {
+        val localURI = new URI(localPath)
+        val setPermissions = if (destName.equals(ClientBase.APP_JAR)) true else false
+        val destPath = copyRemoteFile(dst, qualifyForLocal(localURI), replication, setPermissions)
+        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+          destName, statCache)
+      }
+    }
+
+    // Handle jars local to the ApplicationMaster.
+    if ((args.addJars != null) && (!args.addJars.isEmpty())){
+      args.addJars.split(',').foreach { case file: String =>
+        val localURI = new URI(file.trim())
+        val localPath = new Path(localURI)
+        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+        val destPath = copyRemoteFile(dst, localPath, replication)
+        // Only add the resource to the Spark ApplicationMaster.
+        val appMasterOnly = true
+        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+          linkname, statCache, appMasterOnly)
+      }
+    }
+
+    // Handle any distributed cache files
+    if ((args.files != null) && (!args.files.isEmpty())){
+      args.files.split(',').foreach { case file: String =>
+        val localURI = new URI(file.trim())
+        val localPath = new Path(localURI)
+        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+        val destPath = copyRemoteFile(dst, localPath, replication)
+        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.FILE,
+          linkname, statCache)
+      }
+    }
+
+    // Handle any distributed cache archives
+    if ((args.archives != null) && (!args.archives.isEmpty())) {
+      args.archives.split(',').foreach { case file:String =>
+        val localURI = new URI(file.trim())
+        val localPath = new Path(localURI)
+        val linkname = Option(localURI.getFragment()).getOrElse(localPath.getName())
+        val destPath = copyRemoteFile(dst, localPath, replication)
+        distCacheMgr.addResource(fs, conf, destPath, localResources, LocalResourceType.ARCHIVE,
+          linkname, statCache)
+      }
+    }
+
+    UserGroupInformation.getCurrentUser().addCredentials(credentials)
+    localResources
+  }
+
+  def setupLaunchEnv(
+      localResources: HashMap[String, LocalResource],
+      stagingDir: String): HashMap[String, String] = {
+    logInfo("Setting up the launch environment")
+    val log4jConfLocalRes = localResources.getOrElse(ClientBase.LOG4J_PROP, null)
+
+    val env = new HashMap[String, String]()
+
+    ClientBase.populateClasspath(yarnConf, sparkConf, log4jConfLocalRes != null, env)
+    env("SPARK_YARN_MODE") = "true"
+    env("SPARK_YARN_STAGING_DIR") = stagingDir
+
+    // Set the environment variables to be passed on to the Workers.
+    distCacheMgr.setDistFilesEnv(env)
+    distCacheMgr.setDistArchivesEnv(env)
+
+    // Allow users to specify some environment variables.
+    Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))
+
+    // Add each SPARK_* key to the environment.
+    System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
+
+    env
+  }
+
+  def userArgsToString(clientArgs: ClientArguments): String = {
+    val prefix = " --args "
+    val args = clientArgs.userArgs
+    val retval = new StringBuilder()
+    for (arg <- args) {
+      retval.append(prefix).append(" '").append(arg).append("' ")
+    }
+    retval.toString
+  }
+
+  def calculateAMMemory(newApp: GetNewApplicationResponse) :Int
+
+  def setupSecurityToken(amContainer :ContainerLaunchContext)
+
+  def createContainerLaunchContext(
+        newApp: GetNewApplicationResponse,
+        localResources: HashMap[String, LocalResource],
+        env: HashMap[String, String]): ContainerLaunchContext = {
+    logInfo("Setting up container launch context")
+    val amContainer = Records.newRecord(classOf[ContainerLaunchContext])
+    amContainer.setLocalResources(localResources)
+    amContainer.setEnvironment(env)
+
+    val amMemory = calculateAMMemory(newApp)
+
+    var JAVA_OPTS = ""
+
+    // Add Xmx for AM memory
+    JAVA_OPTS += "-Xmx" + amMemory + "m"
+
+    val tmpDir = new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR)
+    JAVA_OPTS += " -Djava.io.tmpdir=" + tmpDir
+
+    // TODO: Remove once cpuset version is pushed out.
+    // The context is, default gc for server class machines ends up using all cores to do gc -
+    // hence if there are multiple containers in same node, Spark GC affects all other containers'
+    // performance (which can be that of other Spark containers)
+    // Instead of using this, rely on cpusets by YARN to enforce "proper" Spark behavior in
+    // multi-tenant environments. Not sure how default Java GC behaves if it is limited to subset
+    // of cores on a node.
+    val useConcurrentAndIncrementalGC = env.isDefinedAt("SPARK_USE_CONC_INCR_GC") &&
+      java.lang.Boolean.parseBoolean(env("SPARK_USE_CONC_INCR_GC"))
+    if (useConcurrentAndIncrementalGC) {
+      // In our expts, using (default) throughput collector has severe perf ramifications in
+      // multi-tenant machines
+      JAVA_OPTS += " -XX:+UseConcMarkSweepGC "
+      JAVA_OPTS += " -XX:+CMSIncrementalMode "
+      JAVA_OPTS += " -XX:+CMSIncrementalPacing "
+      JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 "
+      JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 "
+    }
+
+    if (env.isDefinedAt("SPARK_JAVA_OPTS")) {
+      JAVA_OPTS += " " + env("SPARK_JAVA_OPTS")
+    }
+
+    // Command for the ApplicationMaster
+    var javaCommand = "java"
+    val javaHome = System.getenv("JAVA_HOME")
+    if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) {
+      javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
+    }
+
+    val commands = List[String](
+      javaCommand +
+        " -server " +
+        JAVA_OPTS +
+        " " + args.amClass +
+        " --class " + args.userClass +
+        " --jar " + args.userJar +
+        userArgsToString(args) +
+        " --worker-memory " + args.workerMemory +
+        " --worker-cores " + args.workerCores +
+        " --num-workers " + args.numWorkers +
+        " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" +
+        " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr")
+
+    logInfo("Command for starting the Spark ApplicationMaster: " + commands(0))
+    amContainer.setCommands(commands)
+
+    setupSecurityToken(amContainer)
+    amContainer
+  }
+}
+
+object ClientBase {
+  val SPARK_JAR: String = "spark.jar"
+  val APP_JAR: String = "app.jar"
+  val LOG4J_PROP: String = "log4j.properties"
+
+  // Based on code from org.apache.hadoop.mapreduce.v2.util.MRApps
+  def populateHadoopClasspath(conf: Configuration, env: HashMap[String, String]) {
+    for (c <- conf.getStrings(YarnConfiguration.YARN_APPLICATION_CLASSPATH)) {
+      Apps.addToEnvironment(env, Environment.CLASSPATH.name, c.trim)
+    }
+  }
+
+  def populateClasspath(conf: Configuration, sparkConf: SparkConf, addLog4j: Boolean, env: HashMap[String, String]) {
+    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
+    // If log4j present, ensure ours overrides all others
+    if (addLog4j) {
+      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+        Path.SEPARATOR + LOG4J_PROP)
+    }
+    // Normally the users app.jar is last in case conflicts with spark jars
+    val userClasspathFirst = sparkConf.get("spark.yarn.user.classpath.first", "false")
+      .toBoolean
+    if (userClasspathFirst) {
+      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+        Path.SEPARATOR + APP_JAR)
+    }
+    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+      Path.SEPARATOR + SPARK_JAR)
+    ClientBase.populateHadoopClasspath(conf, env)
+
+    if (!userClasspathFirst) {
+      Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+        Path.SEPARATOR + APP_JAR)
+    }
+    Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+      Path.SEPARATOR + "*")
+  }
+}