Spark源码-Executor 源码解析

Executor 源码解析

Executor 是干嘛的

处理任务的执行器，是一个JVM进程 ，是一个以线程池实现的运行 Task 的进程。看一下官网和代码注释对 Executor 的说明

• 官网介绍

A process launched for an application on a worker node, that runs tasks and keeps data in memory or disk storage across them. Each application has its own executors.

• Executor 代码注释：Spark执行器，由线程池支持以运行任务。可以与Mesos、YARN和 standalone 调度程序一起使用。内部RPC接口可以与驱动程序通信，但不支持 Mesos细粒度模式

Spark executor, backed by a threadpool to run tasks.
This can be used with Mesos, YARN, and the standalone scheduler.
An internal RPC interface is used for communication with the driver,except in the case of Mesos fine-grained mode.

Executor

主要调用栈

• CoarseGrainedExecutorBackend

  • CoarseGrainedExecutorBackend#receive() :由 LaunchTask 类型的消息触发，以及 KillTask 类型的消息触发

    override def receive: PartialFunction[Any, Unit] = {
      case LaunchTask(data) =>
        if (executor == null) {
          exitExecutor(1, "Received LaunchTask command but executor was null")
        } else {
          val taskDesc = TaskDescription.decode(data.value)
          logInfo("Got assigned task " + taskDesc.taskId)
          executor.launchTask(this, taskDesc)
        }
  
      case KillTask(taskId, _, interruptThread, reason) =>
        if (executor == null) {
          exitExecutor(1, "Received KillTask command but executor was null")
        } else {
          executor.killTask(taskId, interruptThread, reason)
        }
    }
  

• LocalEndpoint

  • LocalEndpoint#receive ： 由 KillTask 类型的消息触发

      case KillTask(taskId, interruptThread, reason) =>
           executor.killTask(taskId, interruptThread, reason)
  

  • LocalEndpoint#receiveAndReply : 由 StopExecutor 类型的消息触发

    override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
      case StopExecutor =>
        executor.stop()
        context.reply(true)
    }
  

  • LocalEndpoint#reviveOffers

    def reviveOffers() {
      val offers = IndexedSeq(new WorkerOffer(localExecutorId, localExecutorHostname, freeCores,
        Some(rpcEnv.address.hostPort)))
      for (task <- scheduler.resourceOffers(offers).flatten) {
        freeCores -= scheduler.CPUS_PER_TASK
        executor.launchTask(executorBackend, task)
      }
    }
  

关键函数说明

• launchTask ：启动 Task ,通过线程池 threadPool 调度 TaskRunner，执行 TaskRunner#run()

    def launchTask(context: ExecutorBackend, taskDescription: TaskDescription): Unit = {
      val tr = new TaskRunner(context, taskDescription)
      runningTasks.put(taskDescription.taskId, tr)
      threadPool.execute(tr)
    }
  

• killTask : 通过 taskReaperPool 调度TaskReaper#run() -> TaskRunner#kill 或 直接调用 taskRunner#kill

    def killTask(taskId: Long, interruptThread: Boolean, reason: String): Unit = {
      val taskRunner = runningTasks.get(taskId)
      if (taskRunner != null) {
        if (taskReaperEnabled) {
          val maybeNewTaskReaper: Option[TaskReaper] = taskReaperForTask.synchronized {
            val shouldCreateReaper = taskReaperForTask.get(taskId) match {
              case None => true
              case Some(existingReaper) => interruptThread && !existingReaper.interruptThread
            }
            if (shouldCreateReaper) {
              val taskReaper = new TaskReaper(
                taskRunner, interruptThread = interruptThread, reason = reason)
              taskReaperForTask(taskId) = taskReaper
              Some(taskReaper)
            } else {
              None
            }
          }
          // Execute the TaskReaper from outside of the synchronized block.
          maybeNewTaskReaper.foreach(taskReaperPool.execute)
        } else {
          taskRunner.kill(interruptThread = interruptThread, reason = reason)
        }
      }
    }
  

• startDriverHeartbeater :启动心跳,调用 reportHeartBeat() 函数， 在初始化的时候被调用

    /**
     * Schedules a task to report heartbeat and partial metrics for active tasks to driver.
     */
    private def startDriverHeartbeater(): Unit = {
      val intervalMs = HEARTBEAT_INTERVAL_MS
  
      // Wait a random interval so the heartbeats don't end up in sync
      val initialDelay = intervalMs + (math.random * intervalMs).asInstanceOf[Int]
  
      val heartbeatTask = new Runnable() {
        override def run(): Unit = Utils.logUncaughtExceptions(reportHeartBeat())
      }
      heartbeater.scheduleAtFixedRate(heartbeatTask, initialDelay, intervalMs, TimeUnit.MILLISECONDS)
    }
  
  

• reportHeartBeat : 向 driver 定时汇报 心跳（heartbeat ) 和 度量（metrics)，由 startDriverHeartbeater() 函数定时调度。

    /** Reports heartbeat and metrics for active tasks to the driver. */
    private def reportHeartBeat(): Unit = {
      // list of (task id, accumUpdates) to send back to the driver
      val accumUpdates = new ArrayBuffer[(Long, Seq[AccumulatorV2[_, _]])]()
      val curGCTime = computeTotalGcTime()
  
      for (taskRunner <- runningTasks.values().asScala) {
        if (taskRunner.task != null) {
          taskRunner.task.metrics.mergeShuffleReadMetrics()
          taskRunner.task.metrics.setJvmGCTime(curGCTime - taskRunner.startGCTime)
          accumUpdates += ((taskRunner.taskId, taskRunner.task.metrics.accumulators()))
        }
      }
  
      val message = Heartbeat(executorId, accumUpdates.toArray, env.blockManager.blockManagerId)
      try {
        val response = heartbeatReceiverRef.askSync[HeartbeatResponse](
            message, new RpcTimeout(HEARTBEAT_INTERVAL_MS.millis, EXECUTOR_HEARTBEAT_INTERVAL.key))
        if (response.reregisterBlockManager) {
          logInfo("Told to re-register on heartbeat")
          env.blockManager.reregister()
        }
        heartbeatFailures = 0
      } catch {
        case NonFatal(e) =>
          logWarning("Issue communicating with driver in heartbeater", e)
          heartbeatFailures += 1
          if (heartbeatFailures >= HEARTBEAT_MAX_FAILURES) {
            logError(s"Exit as unable to send heartbeats to driver " +
              s"more than $HEARTBEAT_MAX_FAILURES times")
            System.exit(ExecutorExitCode.HEARTBEAT_FAILURE)
          }
      }
    }
  
  

• computeTotalGcTime ： 计算本jvm进程花在GC上的总时间

    /** Returns the total amount of time this JVM process has spent in garbage collection. */
    private def computeTotalGcTime(): Long = {
      ManagementFactory.getGarbageCollectorMXBeans.asScala.map(_.getCollectionTime).sum
    }
  

成员变量说明

• threadPool : 使用 Executors.newCachedThreadPool方式创建的 ThreadPoolExecutor，用此线程池运行以"Executor task launch worker"为前缀的 TaskRunner 线程

• taskReaperPool ：使用 Executors.newCachedThreadPool方式创建的 ThreadPoolExecutor，此线程池执行的线程用于监督 Task 的 kill 和 cancel 。

• runningTasks : 用于维护正在运行的Task的身份标识(taskId)与TaskRunner之间的映射关系。

• heartbeater : 只有一个线程的 ScheduledThreadPoolExecutor（线程池调度器），此线程池运行以driver-heartbeater作为名称的线程。该调度器 以 spark.executor.heartbeatInterval
  毫秒的频率定时被调起 执行 reportHeartBeat()，将 active状态 task 的 心跳 (heartbeat)和 度量 ( metrics ) 向 driver 汇报

• heartbeatReceiverRef : HeartbeatReceiver 的 RpcEndpointRef，通过调用RpcEnv的setupEndpointRef方法获得。

• executorId ：当前Executor的身份标识

内部类说明

• TaskRunner ：是一个实现 java.lang.Runnable 的类

• TaskReaper :