启动过程分析

上述的各个模块由SparkEnv来创建，创建过程在SparkEnv.create中完成

    val blockManagerMaster = new BlockManagerMaster(

<span style="white-space:pre">	</span>registerOrLookup("BlockManagerMaster",<span style="font-family: Verdana, Arial, Helvetica, sans-serif;">new BlockManagerMasterActor(isLocal, conf)), </span>

<span style="white-space:pre">	</span>conf)
    val blockManager = new BlockManager(executorId, actorSystem, blockManagerMaster, serializer, conf)
    val connectionManager = blockManager.connectionManager
    val broadcastManager = new BroadcastManager(isDriver, conf)
    val cacheManager = new CacheManager(blockManager)

这段代码容易让人疑惑，看起来像是在所有的cluster node上都创建了BlockManagerMasterActor，其实不然，仔细看registerOrLookup函数的实现。如果当前节点是driver则创建这个actor，否则建立到driver的连接。

 def registerOrLookup(name: String, newActor: => Actor): ActorRef = {
      if (isDriver) {
        logInfo("Registering " + name)
        actorSystem.actorOf(Props(newActor), name = name)
      } else {
        val driverHost: String = conf.get("spark.driver.host", "localhost")
        val driverPort: Int = conf.getInt("spark.driver.port", 7077)
        Utils.checkHost(driverHost, "Expected hostname")
        val url = s"akka.tcp://spark@$driverHost:$driverPort/user/$name"
        val timeout = AkkaUtils.lookupTimeout(conf)
        logInfo(s"Connecting to $name: $url")
        Await.result(actorSystem.actorSelection(url).resolveOne(timeout), timeout)
      }
    }

初始化过程中一个主要的动作就是BlockManager需要向BlockManagerMaster发起注册

数据写入过程分析(*重要*)

数据写入的简要流程

1. RDD.iterator是与storage子系统交互的入口
2. CacheManager.getOrCompute调用BlockManager的put接口来写入数据
3. 数据优先写入到MemoryStore即内存，如果MemoryStore中的数据已满则将最近使用次数不频繁的数据写入到磁盘
4. 通知BlockManagerMaster有新的数据写入，在BlockManagerMaster中保存元数据
5. 将写入的数据与其它slave worker进行同步，一般来说在本机写入的数据，都会另先一台机器来进行数据的备份，即replicanumber=1

数据读取过程分析

 def get(blockId: BlockId): Option[Iterator[Any]] = {
    val local = getLocal(blockId)
    if (local.isDefined) {
      logInfo("Found block %s locally".format(blockId))
      return local
    }
    val remote = getRemote(blockId)
    if (remote.isDefined) {
      logInfo("Found block %s remotely".format(blockId))
      return remote
    }
    None
  }

远程读取

远程获取调用路径， getRemote->doGetRemote, 在doGetRemote中最主要的就是调用BlockManagerWorker.syncGetBlock来从远程获得数据

def syncGetBlock(msg: GetBlock, toConnManagerId: ConnectionManagerId): ByteBuffer = {
    val blockManager = blockManagerWorker.blockManager
    val connectionManager = blockManager.connectionManager
    val blockMessage = BlockMessage.fromGetBlock(msg)
    val blockMessageArray = new BlockMessageArray(blockMessage)
    val responseMessage = connectionManager.sendMessageReliablySync(
        toConnManagerId, blockMessageArray.toBufferMessage)
    responseMessage match {
      case Some(message) => {
        val bufferMessage = message.asInstanceOf[BufferMessage]
        logDebug("Response message received " + bufferMessage)
        BlockMessageArray.fromBufferMessage(bufferMessage).foreach(blockMessage => {
            logDebug("Found " + blockMessage)
            return blockMessage.getData
          })
      }
      case None => logDebug("No response message received")
    }
    null
  }

上述这段代码中最有意思的莫过于sendMessageReliablySync，远程数据读取毫无疑问是一个异步i/o操作，这里的代码怎么写起来就像是在进行同步的操作一样呢。也就是说如何知道对方发送回来响应的呢？

别急，继续去看看sendMessageReliablySync的定义

def sendMessageReliably(connectionManagerId: ConnectionManagerId, message: Message)
      : Future[Option[Message]] = {
    val promise = Promise[Option[Message]]
    val status = new MessageStatus(
      message, connectionManagerId, s => promise.success(s.ackMessage))
    messageStatuses.synchronized {
      messageStatuses += ((message.id, status))
    }
    sendMessage(connectionManagerId, message)
    promise.future
  }

要是我说秘密在这里，你肯定会说我在扯淡，但确实在此处。注意到关键字Promise和Future没。

如果这个future执行完毕，返回s.ackMessage。我们再看看这个ackMessage是在什么地方被写入的呢。看一看ConnectionManager.handleMessage中的代码片段

case bufferMessage: BufferMessage => {
        if (authEnabled) {
          val res = handleAuthentication(connection, bufferMessage)
          if (res == true) {
            // message was security negotiation so skip the rest
            logDebug("After handleAuth result was true, returning")
            return
          }
        }
        if (bufferMessage.hasAckId) {
          val sentMessageStatus = messageStatuses.synchronized {
            messageStatuses.get(bufferMessage.ackId) match {
              case Some(status) => {
                messageStatuses -= bufferMessage.ackId
                status
              }
              case None => {
                throw new Exception("Could not find reference for received ack message " +
                  message.id)
                null
              }
            }
          }
          sentMessageStatus.synchronized {
            sentMessageStatus.ackMessage = Some(message)
            sentMessageStatus.attempted = true
            sentMessageStatus.acked = true
            sentMessageStaus.markDone()
          }

注意，此处的所调用的sentMessageStatus.markDone就会调用在sendMessageReliablySync中定义的promise.Success.
不妨看看MessageStatus的定义。

 class MessageStatus(
      val message: Message,
      val connectionManagerId: ConnectionManagerId,
      completionHandler: MessageStatus => Unit) {

    var ackMessage: Option[Message] = None
    var attempted = false
    var acked = false

    def markDone() { completionHandler(this) }
  }

我想至此调用关系搞清楚了，scala中的Future和Promise理解起来还有有点费劲。

TachyonStore值得关注的项目（分布式内存文件系统）