[GitHub] spark pull request #22288: [SPARK-22148][Scheduler] Acquire new executors to...

[Ngone51 <gi...@git.apache.org>]

Github user Ngone51 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/22288#discussion_r214719743
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala ---
    @@ -414,9 +425,54 @@ private[spark] class TaskSchedulerImpl(
                 launchedAnyTask |= launchedTaskAtCurrentMaxLocality
               } while (launchedTaskAtCurrentMaxLocality)
             }
    +
             if (!launchedAnyTask) {
    -          taskSet.abortIfCompletelyBlacklisted(hostToExecutors)
    -        }
    +          taskSet.getCompletelyBlacklistedTaskIfAny(hostToExecutors) match {
    +            case taskIndex: Some[Int] => // Returns the taskIndex which was unschedulable
    +              if (conf.getBoolean("spark.dynamicAllocation.enabled", false)) {
    +                // If the taskSet is unschedulable we kill the existing blacklisted executor/s and
    +                // kick off an abortTimer which after waiting will abort the taskSet if we were
    +                // unable to get new executors and couldn't schedule a task from the taskSet.
    +                // Note: We keep a track of schedulability on a per taskSet basis rather than on a
    +                // per task basis.
    +                if (!unschedulableTaskSetToExpiryTime.contains(taskSet)) {
    +                  hostToExecutors.valuesIterator.foreach(executors => executors.foreach({
    +                    executor =>
    +                      logDebug("Killing executor because of task unschedulability: " + executor)
    +                      blacklistTrackerOpt.foreach(blt => blt.killBlacklistedExecutor(executor))
    --- End diff --
    
    Seriously? You killed all executors ? What if other taskSets' tasks are running on them ?
    
    BTW, if you want to refresh executors, you have to enable `spark.blacklist.killBlacklistedExecutors`  also.


---

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