Spark2.3（四十三）：Spark Broadcast总结

为什么要使用广播(broadcast)变量？

Spark中因为算子中的真正逻辑是发送到Executor中去运行的，所以当Executor中需要引用外部变量时，需要使用广播变量。
进一步解释：

• 如果executor端用到了Driver的变量，如果不使用广播变量在Executor有多少task就有多少Driver端的变量副本。
• 如果Executor端用到了Driver的变量，如果使用广播变量在每个Executor中只有一份Driver端的变量副本。

Spark中Broadcast定义

官网定义：

A broadcast variable. Broadcast variables allow the programmer to keep a read-only variable cached on each machine rather than shipping a copy of it with tasks. They can be used, for example, to give every node a copy of a large input dataset in an efficient manner. Spark also attempts to distribute broadcast variables using efficient broadcast algorithms to reduce communication cost.
Broadcast variables are created from a variable v by calling SparkContext.broadcast(T, scala.reflect.ClassTag<T>). The broadcast variable is a wrapper around v, and its value can be accessed by calling the value method. The interpreter session below shows this:
[翻译]它是一个广播变量。广播变量允许程序员在每台计算机上缓存只读变量，而不是将其副本与任务一起发送。例如，它们可以有效地为每个节点提供一个大型输入数据集的副本。Spark还尝试使用有效的广播算法来分配广播变量，以降低通信成本。
广播变量是通过调用sparkcontext.broadcast（t，scala.reflect.classtag<t>）从变量v创建的。广播变量是围绕v的包装器，它的值可以通过调用value方法来访问。下面的口译员会话显示了这一点：

     scala> val broadcastVar = sc.broadcast(Array(1, 2, 3))
     broadcastVar: org.apache.spark.broadcast.Broadcast[Array[Int} = Broadcast(0)

     scala> broadcastVar.value
     res0: Array[Int] = Array(1, 2, 3)

After the broadcast variable is created, it should be used instead of the value v in any functions run on the cluster so that v is not shipped to the nodes more than once. In addition, the object v should not be modified after it is broadcast in order to ensure that all nodes get the same value of the broadcast variable (e.g. if the variable is shipped to a new node later).
[翻译]创建广播变量后，应在集群上运行的任何函数中使用它，而不是使用值v，这样V就不会多次发送到节点。此外，对象v在广播后不应进行修改，以确保所有节点都获得广播变量的相同值（例如，如果变量稍后被发送到新节点）。

Broadcast.scala类定义：

package org.apache.spark.broadcast

import java.io.Serializable

import scala.reflect.ClassTag

import org.apache.spark.SparkException
import org.apache.spark.internal.Logging
import org.apache.spark.util.Utils

/**
 * A broadcast variable. 
 * 。。。。。。
 * @param id A unique identifier for the broadcast variable.
 * @tparam T Type of the data contained in the broadcast variable.
 */
abstract class Broadcast[T: ClassTag](val id: Long) extends Serializable with Logging {

  /**
   * Flag signifying whether the broadcast variable is valid(that is, not already destroyed) or not.
   * 指示广播变量是否有效的标志（即，尚未销毁）或未销毁。
   */
  @volatile private var _isValid = true

  private var _destroySite = ""

  /** Get the broadcasted value. */
  def value: T = {
    assertValid()
    getValue()
  }

  /**
   * Asynchronously delete cached copies of this broadcast on the executors. If the broadcast is used after this is called, it will need to be re-sent to each executor.
   * 异步删除执行器上此广播的缓存副本。如果在调用后使用广播，则需要将其重新发送给每个执行者。 
   */
  def unpersist() {
    unpersist(blocking = false)
  }

  /**
   * Delete cached copies of this broadcast on the executors. If the broadcast is used after this is called, it will need to be re-sent to each executor.
   * 删除执行器上此广播的缓存副本。如果在调用后使用广播，则需要将其重新发送给每个执行者。
   * @param blocking Whether to block until unpersisting has completed 是否阻止直到unpersist完成
   */
  def unpersist(blocking: Boolean) {
    assertValid()
    doUnpersist(blocking)
  }


  /**
   * Destroy all data and metadata related to this broadcast variable. Use this with caution; once a broadcast variable has been destroyed, it cannot be used again. This method blocks until destroy has completed
   * 销毁与此广播变量相关的所有数据和元数据。小心使用；广播变量一旦被销毁，就不能再使用。此方法在销毁完成之前阻止
   */
  def destroy() {
    destroy(blocking = true)
  }

  /**
   * Destroy all data and metadata related to this broadcast variable. Use this with caution; once a broadcast variable has been destroyed, it cannot be used again.
   * 销毁与此广播变量相关的所有数据和元数据。小心使用；广播变量一旦被销毁，就不能再使用。
   * @param blocking Whether to block until destroy has completed 是否阻止直到销毁完成
   */
  private[spark] def destroy(blocking: Boolean) {
    assertValid()
    _isValid = false
    _destroySite = Utils.getCallSite().shortForm
    logInfo("Destroying %s (from %s)".format(toString, _destroySite))
    doDestroy(blocking)
  }

  /**
   * Whether this Broadcast is actually usable. This should be false once persisted state is removed from the driver.
   * 广播变量是否实际可用。一旦持久化状态从driver中被移除将会返回false.
   */
  private[spark] def isValid: Boolean = {
    _isValid
  }

  /**
   * Actually get the broadcasted value. Concrete implementations of Broadcast class must define their own way to get the value.
   * 实际获取广播值。广播类的具体实现必须定义自己的方法来获取值。
   */
  protected def getValue(): T

  /**
   * Actually unpersist the broadcasted value on the executors. Concrete implementations of Broadcast class must define their own logic to unpersist their own data.
   */
  protected def doUnpersist(blocking: Boolean)

  /**
   * Actually destroy all data and metadata related to this broadcast variable. Implementation of Broadcast class must define their own logic to destroy their own state.
   */
  protected def doDestroy(blocking: Boolean)

  /** Check if this broadcast is valid. If not valid, exception is thrown. */
  protected def assertValid() {
    if (!_isValid) {
      throw new SparkException("Attempted to use %s after it was destroyed (%s) ".format(toString, _destroySite))
    }
  }

  override def toString: String = "Broadcast(" + id + ")"
}

其中隐含的概念:
1）broadcast的定义必须在Driver端，不能再executor端定义；
2）调用unpersist()，unpersist(boolean blocking),destroy(),distroy(boolean blocking)方法这些方法必须在driver端调用。
3）在Driver端可以修改广播变量的值，在Executor端无法修改广播变量的值。

具体操作步骤：
a.在driver端调用unpersist(true)方法；
b.对该broadcast实例对象进行重新赋值。
参考《Spark2.2（三十三）：Spark Streaming和Spark Structured Streaming更新broadcast总结（一）》、《Spark2.3（四十二）：Spark Streaming和Spark Structured Streaming更新broadcast总结（二）》

Broadcast工作流程

Broadcast使用时注意事项

注意事项
1、能不能将一个RDD使用广播变量广播出去？
   不能，因为RDD是不存储数据的。可以将RDD的结果广播出去。
2、广播变量只能在Driver端定义，不能在Executor端定义。
3、在Driver端可以修改广播变量的值，在Executor端无法修改广播变量的值。
4、如果executor端用到了Driver的变量，如果不使用广播变量在Executor有多少task就有多少Driver端的变量副本。
5、如果Executor端用到了Driver的变量，如果使用广播变量在每个Executor中只有一份Driver端的变量副本。

参考《【Spark篇】---Spark中广播变量和累加器》