[GitHub] spark pull request #20940: [SPARK-23429][CORE] Add executor memory metrics t...

[squito <gi...@git.apache.org>]

Github user squito commented on a diff in the pull request:

    https://github.com/apache/spark/pull/20940#discussion_r179795171
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala ---
    @@ -234,8 +244,22 @@ private[spark] class EventLoggingListener(
         }
       }
     
    -  // No-op because logging every update would be overkill
    -  override def onExecutorMetricsUpdate(event: SparkListenerExecutorMetricsUpdate): Unit = { }
    +  /**
    +   * Log if there is a new peak value for one of the memory metrics for the given executor.
    +   * Metrics are cleared out when a new stage is started in onStageSubmitted, so this will
    +   * log new peak memory metric values per executor per stage.
    +   */
    +  override def onExecutorMetricsUpdate(event: SparkListenerExecutorMetricsUpdate): Unit = {
    --- End diff --
    
    I wouldn't think you'd want to log for every new peak, as I'd expect it would be natural for the peak to keep growing, so you'd just end up with a lot of logs.  I'd expect you'd just log the peak when the stage ended, or when the executor died.
    
    the downside of that approach is that you never log a peak if the driver dies ... but then you've got to figure out the driver issue anyway.


---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org