spark源碼閱讀RDD中WithScope是什麼？

    withScope是最近的發現版中新增加的一個模塊，它是用來做DAG可視化的（DAG visualization on SparkUI）

以前的sparkUI中只有stage的執行情況，也就是說我們不可以看到上個RDD到下個RDD的具體信息。於是爲了在

sparkUI中能展示更多的信息。所以把所有創建的RDD的方法都包裹起來，同時用RDDOperationScope 記錄 RDD 的操作歷史和關聯，就能達成目標。下面就是一張WordCount的DAG visualization on SparkUI

記錄關係的RDDOperationScope源碼如下：

/**
 * A collection of utility methods to construct a hierarchical representation of RDD scopes.
 * An RDD scope tracks the series of operations that created a given RDD.
 */
private[spark] object RDDOperationScope extends Logging {
  private val jsonMapper = new ObjectMapper().registerModule(DefaultScalaModule)
  private val scopeCounter = new AtomicInteger(0)

 <span style="color:#ff0000;"> def fromJson(s: String): RDDOperationScope = {
    jsonMapper.readValue(s, classOf[RDDOperationScope])
  }</span>


  //返回一個全局獨一無二的scopeID
  def nextScopeId(): Int = scopeCounter.getAndIncrement

  /**
   * Execute the given body such that all RDDs created in this body will have the same scope.
   * The name of the scope will be the first method name in the stack trace that is not the
   * same as this method's.
   *
   * Note: Return statements are NOT allowed in body.
   */
  private[spark] def withScope[T](
      sc: SparkContext,
      allowNesting: Boolean = false)(body: => T): T = {
    //設置跟蹤堆的軌跡的scope名字
    val ourMethodName = "withScope"
    val callerMethodName = Thread.currentThread.getStackTrace()
      .dropWhile(_.getMethodName != ourMethodName)
      .find(_.getMethodName != ourMethodName)
      .map(_.getMethodName)
      .getOrElse {
        // Log a warning just in case, but this should almost certainly never happen
        logWarning("No valid method name for this RDD operation scope!")
        "N/A"
      }
    withScope[T](sc, callerMethodName, allowNesting, ignoreParent = false)(body)
  }

  /**
   * Execute the given body such that all RDDs created in this body will have the same scope.
   *
   * If nesting is allowed, any subsequent calls to this method in the given body will instantiate
   * child scopes that are nested within our scope. Otherwise, these calls will take no effect.
   *
   * Additionally, the caller of this method may optionally ignore the configurations and scopes
   * set by the higher level caller. In this case, this method will ignore the parent caller's
   * intention to disallow nesting, and the new scope instantiated will not have a parent. This
   * is useful for scoping physical operations in Spark SQL, for instance.
   *
   * Note: Return statements are NOT allowed in body.
   */
  private[spark] def withScope[T](
      sc: SparkContext,
      name: String,
      allowNesting: Boolean,
      ignoreParent: Boolean)(body: => T): T = {
    // Save the old scope to restore it later
    //先保存老的scope，之後恢復它
    val scopeKey = SparkContext.RDD_SCOPE_KEY
    val noOverrideKey = SparkContext.RDD_SCOPE_NO_OVERRIDE_KEY
    val oldScopeJson = sc.getLocalProperty(scopeKey)
    val oldScope = Option(oldScopeJson).map(RDDOperationScope.fromJson)
    val oldNoOverride = sc.getLocalProperty(noOverrideKey)
    try {
      if (ignoreParent) {
        //ignoreParent: Boolean：當ignorePatent設置爲true的時候，那麼回忽略之前的全部設置和scope
        //從新我們自己的scope
        sc.setLocalProperty(scopeKey, <span style="color:#ff0000;">new RDDOperationScope(name).toJson</span>)
      } else if (sc.getLocalProperty(noOverrideKey) == null) {
        // Otherwise, set the scope only if the higher level caller allows us to do so
        sc.setLocalProperty(scopeKey, <span style="color:#ff0000;">new RDDOperationScope(name, oldScope).toJson</span>)
      }
      //可選：不讓我們的新的子RDD放入我們的scope中
      if (!allowNesting) {
        sc.setLocalProperty(noOverrideKey, "true")
      }
      body
    } finally {
      //把所有的新狀態恢復放在一起
      sc.setLocalProperty(scopeKey, <span style="color:#ff0000;">oldScopeJson</span>)
      sc.setLocalProperty(noOverrideKey, oldNoOverride)
    }
  }
}