Spark-PRC.md

title	date	tags
Spark PRC	2018-12-19 02:30:33 -0800	Spark BigData

• receive：接收消息并处理，但不需要给客户端回复。
• receiveAndReply：接收消息并处理，需要给客户端回复。回复是通过 RpcCall-Context来实现的。

/**
 * An end point for the RPC that defines what functions to trigger given a message.
 *
 * It is guaranteed that `onStart`, `receive` and `onStop` will be called in sequence.
 *
 * The life-cycle of an endpoint is:
 *
 * constructor -> onStart -> receive* -> onStop
 *
 * Note: `receive` can be called concurrently. If you want `receive` to be thread-safe, please use
 * [[ThreadSafeRpcEndpoint]]
 *
 * If any error is thrown from one of [[RpcEndpoint]] methods except `onError`, `onError` will be
 * invoked with the cause. If `onError` throws an error, [[RpcEnv]] will ignore it.
 */
private[spark] trait RpcEndpoint {

  /**
   * The [[RpcEnv]] that this [[RpcEndpoint]] is registered to.
   */
  val rpcEnv: RpcEnv

  /**
   * The [[RpcEndpointRef]] of this [[RpcEndpoint]]. `self` will become valid when `onStart` is
   * called. And `self` will become `null` when `onStop` is called.
   *
   * Note: Because before `onStart`, [[RpcEndpoint]] has not yet been registered and there is not
   * valid [[RpcEndpointRef]] for it. So don't call `self` before `onStart` is called.
   */
  final def self: RpcEndpointRef = {
    require(rpcEnv != null, "rpcEnv has not been initialized")
    rpcEnv.endpointRef(this)
  }

  /**
   * Process messages from [[RpcEndpointRef.send]] or [[RpcCallContext.reply)]]. If receiving a
   * unmatched message, [[SparkException]] will be thrown and sent to `onError`.
   */
  def receive: PartialFunction[Any, Unit] = {
    case _ => throw new SparkException(self + " does not implement 'receive'")
  }

  /**
   * Process messages from [[RpcEndpointRef.ask]]. If receiving a unmatched message,
   * [[SparkException]] will be thrown and sent to `onError`.
   */
  def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
    case _ => context.sendFailure(new SparkException(self + " won't reply anything"))
  }

  /**
   * Invoked when any exception is thrown during handling messages.
   */
  def onError(cause: Throwable): Unit = {
    // By default, throw e and let RpcEnv handle it
    throw cause
  }

  /**
   * Invoked when `remoteAddress` is connected to the current node.
   */
  def onConnected(remoteAddress: RpcAddress): Unit = {
    // By default, do nothing.
  }

  /**
   * Invoked when `remoteAddress` is lost.
   */
  def onDisconnected(remoteAddress: RpcAddress): Unit = {
    // By default, do nothing.
  }

  /**
   * Invoked when some network error happens in the connection between the current node and
   * `remoteAddress`.
   */
  def onNetworkError(cause: Throwable, remoteAddress: RpcAddress): Unit = {
    // By default, do nothing.
  }

  /**
   * Invoked before [[RpcEndpoint]] starts to handle any message.
   */
  def onStart(): Unit = {
    // By default, do nothing.
  }

  /**
   * Invoked when [[RpcEndpoint]] is stopping. `self` will be `null` in this method and you cannot
   * use it to send or ask messages.
   */
  def onStop(): Unit = {
    // By default, do nothing.
  }

  /**
   * A convenient method to stop [[RpcEndpoint]].
   */
  final def stop(): Unit = {
    val _self = self
    if (_self != null) {
      rpcEnv.stop(_self)
    }
  }
}

在Akka中只要你持有了⼀个Actor的引⽤ ActorRef，那么你就可以使⽤此ActorRef向远端的Actor发起请求。 RpcEndpointRef也具有同等的效⽤，要向⼀个远端的RpcEndpoint发起请 求，你就必须持有这个RpcEndpoint的RpcEndpointRef。

/**
 * A reference for a remote [[RpcEndpoint]]. [[RpcEndpointRef]] is thread-safe.
 */
private[spark] abstract class RpcEndpointRef(conf: SparkConf)
  extends Serializable with Logging {

  private[this] val maxRetries = RpcUtils.numRetries(conf)
  private[this] val retryWaitMs = RpcUtils.retryWaitMs(conf)
  private[this] val defaultAskTimeout = RpcUtils.askRpcTimeout(conf)

  /**
   * return the address for the [[RpcEndpointRef]]
   */
  def address: RpcAddress

  def name: String

  /**
   * Sends a one-way asynchronous message. Fire-and-forget semantics.
   */
  def send(message: Any): Unit

  /**
   * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a [[Future]] to
   * receive the reply within the specified timeout.
   *
   * This method only sends the message once and never retries.
   */
  def ask[T: ClassTag](message: Any, timeout: RpcTimeout): Future[T]

  /**
   * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a [[Future]] to
   * receive the reply within a default timeout.
   *
   * This method only sends the message once and never retries.
   */
  def ask[T: ClassTag](message: Any): Future[T] = ask(message, defaultAskTimeout)

  /**
   * Send a message to the corresponding [[RpcEndpoint]] and get its result within a default
   * timeout, or throw a SparkException if this fails even after the default number of retries.
   * The default `timeout` will be used in every trial of calling `sendWithReply`. Because this
   * method retries, the message handling in the receiver side should be idempotent.
   *
   * Note: this is a blocking action which may cost a lot of time,  so don't call it in a message
   * loop of [[RpcEndpoint]].
   *
   * @param message the message to send
   * @tparam T type of the reply message
   * @return the reply message from the corresponding [[RpcEndpoint]]
   */
  def askWithRetry[T: ClassTag](message: Any): T = askWithRetry(message, defaultAskTimeout)

  /**
   * Send a message to the corresponding [[RpcEndpoint.receive]] and get its result within a
   * specified timeout, throw a SparkException if this fails even after the specified number of
   * retries. `timeout` will be used in every trial of calling `sendWithReply`. Because this method
   * retries, the message handling in the receiver side should be idempotent.
   *
   * Note: this is a blocking action which may cost a lot of time, so don't call it in a message
   * loop of [[RpcEndpoint]].
   *
   * @param message the message to send
   * @param timeout the timeout duration
   * @tparam T type of the reply message
   * @return the reply message from the corresponding [[RpcEndpoint]]
   */
  def askWithRetry[T: ClassTag](message: Any, timeout: RpcTimeout): T = {
    // TODO: Consider removing multiple attempts
    var attempts = 0
    var lastException: Exception = null
    while (attempts < maxRetries) {
      attempts += 1
      try {
        val future = ask[T](message, timeout)
        val result = timeout.awaitResult(future)
        if (result == null) {
          throw new SparkException("RpcEndpoint returned null")
        }
        return result
      } catch {
        case ie: InterruptedException => throw ie
        case e: Exception =>
          lastException = e
          logWarning(s"Error sending message [message = $message] in $attempts attempts", e)
      }

      if (attempts < maxRetries) {
        Thread.sleep(retryWaitMs)
      }
    }

    throw new SparkException(
      s"Error sending message [message = $message]", lastException)
  }

}

• RpcEndpoint：RPC端点，即RPC分布式环境中⼀个具体的实例，其可 以对指定的消息进⾏处理。由于RpcEndpoint是⼀个特质，所以需要提供 RpcEndpoint的实现类。特质RpcEndpoint已在前⽂详细介绍，此处不再赘 述。

• RpcEndpointRef：RPC端点引⽤，即RPC分布式环境中⼀个具体实体 的引⽤，所谓引⽤实际是“spark://host:port/name”这种格式的地址。其中， host为端点所在RPC服务所在的主机IP，port是端点所在RPC服务的端⼜， name是端点实例的名称。抽象类RpcEndpointRef已在前⽂详细介绍，此处 不再赘述。