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From ilganeli <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-5945] Spark should not retry a stage in...
Date Tue, 28 Jul 2015 00:54:45 GMT
Github user ilganeli commented on a diff in the pull request:

    https://github.com/apache/spark/pull/5636#discussion_r35605388
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/Stage.scala ---
    @@ -76,6 +76,33 @@ private[spark] abstract class Stage(
        */
       private var _latestInfo: StageInfo = StageInfo.fromStage(this, nextAttemptId)
     
    +  /**
    +   * Spark is resilient to executors dying by retrying stages on FetchFailures. Here,
we keep track
    +   * of the number of stage failures to prevent endless stage retries.
    +   */
    +  private var failedStageCount = 0
    +
    +  private[scheduler] def clearFailures() : Unit = {
    +    failedStageCount = 0
    +  }
    +
    +  /**
    +   * Check whether we should abort the failedStage due to multiple failures.
    +   * This method updates the running count of failures for a particular stage and returns
    +   * true if the number of failures exceeds the allowable number of failures.
    +   */
    +  private[scheduler] def failAndShouldAbort(): Boolean = {
    +    // We increment the failure count on the first attempt for a particular Stage
    +    if (_latestInfo.attemptId == 0)
    +    {
    +      failedStageCount += 1
    +    }
    --- End diff --
    
    That's what I had a few commits prior, as I understood it, we wanted a set since at that
time we were concerned about multiple concurrent attempts (and thus failures) per stage. From
the test harness though, I guess what we really need is to track failures per stageId.


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