BroadcastManager

Broadcast是分布式的数据共享，由BroadcastManager负责管理其创建或销毁。Broadcast一般用于处理共享的配置文件、通用Dataset、常用数据结构

1.1、创建

通过SparkContext.broadcast广播一个Broadcast, 实际调用的是SparkEnv的BroadManager来创建

  /**
   * Broadcast a read-only variable to the cluster, returning a
   * [[org.apache.spark.broadcast.Broadcast]] object for reading it in distributed functions.
   * The variable will be sent to each cluster only once.
   */
  def broadcast[T: ClassTag](value: T): Broadcast[T] = {
    assertNotStopped()
    require(!classOf[RDD[_]].isAssignableFrom(classTag[T].runtimeClass),
      "Can not directly broadcast RDDs; instead, call collect() and broadcast the result.")
    //使用SparkEnv.broadcastManager创建Broadcast
    val bc = env.broadcastManager.newBroadcast[T](value, isLocal)
    val callSite = getCallSite
    logInfo("Created broadcast " + bc.id + " from " + callSite.shortForm)
    cleaner.foreach(_.registerBroadcastForCleanup(bc))
    bc
  }

1.1.1、在SparkEnv中创建BroadcastManager，

// 此处只是声明， 只有调用initialize， 才会生效
val broadcastManager = new BroadcastManager(isDriver, conf, securityManager)

1.1.2、initialize

// Called by SparkContext or Executor before using Broadcast
  private def initialize() {
    synchronized {
      if (!initialized) {
        broadcastFactory = new TorrentBroadcastFactory
        broadcastFactory.initialize(isDriver, conf, securityManager)
        initialized = true
      }
    }
  }

1.1.3、 BoradcastManager操作BradCast实际是代理BroadcastFactory, 此处使用工厂模式

  def stop() {
    broadcastFactory.stop()
  }

  private val nextBroadcastId = new AtomicLong(0)

  def newBroadcast[T: ClassTag](value_ : T, isLocal: Boolean): Broadcast[T] = {
    broadcastFactory.newBroadcast[T](value_, isLocal, nextBroadcastId.getAndIncrement())
  }

  def unbroadcast(id: Long, removeFromDriver: Boolean, blocking: Boolean) {
    broadcastFactory.unbroadcast(id, removeFromDriver, blocking)
  }