mridulm commented on code in PR #42950:
URL: https://github.com/apache/spark/pull/42950#discussion_r1334896106
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core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
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@@ -1903,13 +1903,20 @@ private[spark] class DAGScheduler(
case smt: ShuffleMapTask =>
val shuffleStage = stage.asInstanceOf[ShuffleMapStage]
- shuffleStage.pendingPartitions -= task.partitionId
+ // Ignore task completion for old attempt of indeterminate stage
+ val ignoreIndeterminate = stage.isIndeterminate &&
+ task.stageAttemptId < stage.latestInfo.attemptNumber()
+ if (!ignoreIndeterminate) {
+ shuffleStage.pendingPartitions -= task.partitionId
+ }
val status = event.result.asInstanceOf[MapStatus]
val execId = status.location.executorId
logDebug("ShuffleMapTask finished on " + execId)
if (executorFailureEpoch.contains(execId) &&
smt.epoch <= executorFailureEpoch(execId)) {
logInfo(s"Ignoring possibly bogus $smt completion from executor
$execId")
Review Comment:
So this is kind of funny - take a look at what the above replaced @cloud-fan
:
https://github.com/apache/spark/pull/16620/files#diff-85de35b2e85646ed499c545a3be1cd3ffd525a88aae835a9c621f877eebadcb6R1183
:-)
Both of these actually do not account for DETERMINATE/INDETERMINATE changes
we made subsequently.
IMO, for INDETERMINATE stages, we should ignore task completion events from
previous attempts - since we have already cancelled the stage attempt.
Having said that, I have not thought through the nuances here.
+CC @jiangxb1987 as well
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