Spark版本定制第9天：Receiver在Driver的精妙实现全生命周期彻底研究和思考

本期内容：

1 Receiver生命周期

2 深度思考

　　一切不能进行实时流处理的数据都是无效的数据。在流处理时代，SparkStreaming有着强大吸引力，而且发展前景广阔，加之Spark的生态系统，Streaming可以方便调用其他的诸如SQL，MLlib等强大框架，它必将一统天下。

　　Spark Streaming运行时与其说是Spark Core上的一个流式处理框架，不如说是Spark Core上的一个最复杂的应用程序。如果可以掌握Spark streaming这个复杂的应用程序，那么其他的再复杂的应用程序都不在话下了。这里选择Spark Streaming作为版本定制的切入点也是大势所趋。

　　在SparkStreaming中，都是利用Reiceiver来接受数据的。而receiver在节点上都是通过receiverTracker来管理的。在receiverTracker中会调用start方法，来启动消息循环体ReceiverTrackerEndPoint进行通信。

def start(): Unit = synchronized {
  if (isTrackerStarted) {
    throw new SparkException("ReceiverTracker already started")
  } 

  if (!receiverInputStreams.isEmpty) {
    endpoint = ssc.env.rpcEnv.setupEndpoint(
      "ReceiverTracker", new ReceiverTrackerEndpoint(ssc.env.rpcEnv))
    if (!skipReceiverLaunch) launchReceivers()
    logInfo("ReceiverTracker started")
    trackerState = Started
  }
}

　　在start方法会发送消息启动Receiver

private def launchReceivers(): Unit = {
  val receivers = receiverInputStreams.map(nis => {
    val rcvr = nis.getReceiver()
    rcvr.setReceiverId(nis.id)
    rcvr
  }) 

  runDummySparkJob() 

  logInfo("Starting " + receivers.length + " receivers")
  endpoint.send(StartAllReceivers(receivers))
}

　　接下来会startAllReceivers，在这里通过消息循环体ReceiverTrackerEndPoint。

case StartAllReceivers(receivers) =>
  val scheduledLocations = schedulingPolicy.scheduleReceivers(receivers, getExecutors)
  for (receiver <- receivers) {
    val executors = scheduledLocations(receiver.streamId)
    updateReceiverScheduledExecutors(receiver.streamId, executors)
    receiverPreferredLocations(receiver.streamId) = receiver.preferredLocation
    startReceiver(receiver, executors)
  }

　　在此方法中，如果发生Receiver对应的Job结束了，可是ReceiverTracker还没有停止。它将会向ReceiverTrackerEndpoint发送一个ReStartReceiver的方法来重新启动reveiver，它被封装在future.onComplete中

 future.onComplete {
  case Success(_) =>
    if (!shouldStartReceiver) {
      onReceiverJobFinish(receiverId)
    } else {
      logInfo(s"Restarting Receiver $receiverId")
      self.send(RestartReceiver(receiver))
    }
  case Failure(e) =>
    if (!shouldStartReceiver) {
      onReceiverJobFinish(receiverId)
    } else {
      logError("Receiver has been stopped. Try to restart it.", e)
      logInfo(s"Restarting Receiver $receiverId")
      self.send(RestartReceiver(receiver))
    }
}(submitJobThreadPool)

备注：

资料来源于：DT_大数据梦工厂（Spark发行版本定制）

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