attilapiros commented on code in PR #50630:
URL: https://github.com/apache/spark/pull/50630#discussion_r2072347515
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core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
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@@ -2337,10 +2344,8 @@ private[spark] class DAGScheduler(
"checkpointing the RDD before repartition and try again."
}
- activeJobs.foreach(job => collectStagesToRollback(job.finalStage :: Nil))
-
// The stages will be rolled back after checking
- val rollingBackStages = HashSet[Stage](mapStage)
+ val rollingBackStages = HashSet[Stage]()
Review Comment:
This was the case even before this PR, is not it?
But this makes me wonder why we materialize the missing partitions
containing the exact missing partitions itself?
We already have a `numAvailableOutputs` which is based on a counter in
`MapOutputTracker`:
https://github.com/apache/spark/blob/db59634edaf8e1dc587077edd5a2bc7955b3f357/core/src/main/scala/org/apache/spark/MapOutputTracker.scala#L143-L148
When `numAvailableOutputs` is nonzero we need to roll it back.
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