tgravescs commented on a change in pull request #27223:
[SPARK-30511][SPARK-28403][CORE] Don't treat failed/killed speculative tasks as
pending in Spark scheduler
URL: https://github.com/apache/spark/pull/27223#discussion_r370674267
##########
File path: core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
##########
@@ -614,18 +614,24 @@ private[spark] class ExecutorAllocationManager(
stageAttemptToNumRunningTask -= stageAttempt
}
}
- // If the task failed, we expect it to be resubmitted later. To ensure
we have
- // enough resources to run the resubmitted task, we need to mark the
scheduler
- // as backlogged again if it's not already marked as such (SPARK-8366)
- if (taskEnd.reason != Success) {
- if (totalPendingTasks() == 0) {
- allocationManager.onSchedulerBacklogged()
- }
- if (taskEnd.taskInfo.speculative) {
- stageAttemptToSpeculativeTaskIndices.get(stageAttempt).foreach
{_.remove(taskIndex)}
- } else {
- stageAttemptToTaskIndices.get(stageAttempt).foreach
{_.remove(taskIndex)}
- }
+
+ if (taskEnd.taskInfo.speculative) {
+ stageAttemptToSpeculativeTaskIndices.get(stageAttempt).foreach
{_.remove{taskIndex}}
+ stageAttemptToNumSpeculativeTasks(stageAttempt) -= 1
Review comment:
thanks for the explanation, its been a while since I looked at the
speculative handling in the scheduler. I think the failed task case with
speculative is ok. I think the problem is the scheduler isn't tracking those
task as speculative or not after the initial launch. I would rather error on
the side of asking for to many and the failure case should be less frequent.
that is a lot more complex case along with making the dynamic allocation
manager smarter about it. If you can file that other jira I mentioned above to
follow up, if you could put those details in there as well that would be great.
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