dongjoon-hyun commented on code in PR #37924:
URL: https://github.com/apache/spark/pull/37924#discussion_r973809002
##########
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala:
##########
@@ -1140,6 +1146,38 @@ class DAGSchedulerSuite extends SparkFunSuite with
TempLocalSparkContext with Ti
assertDataStructuresEmpty()
}
+ test("SPARK-40481: Multiple consecutive stage fetch failures should not fail
job " +
+ "when ignoreOnDecommissionFetchFailure is enabled.") {
+ conf.set(config.STAGE_IGNORE_DECOMMISSION_FETCH_FAILURE.key, "true")
+
+ setupStageAbortTest(sc)
+ val parts = 2
+ val shuffleMapRdd = new MyRDD(sc, parts, Nil)
+ val shuffleDep = new ShuffleDependency(shuffleMapRdd, new
HashPartitioner(parts))
+ val reduceRdd = new MyRDD(sc, parts, List(shuffleDep), tracker =
mapOutputTracker)
+ submit(reduceRdd, (0 until parts).toArray)
+
+ for (attempt <- 0 until scheduler.maxConsecutiveStageAttempts) {
+ // Complete all the tasks for the current attempt of stage 0 successfully
+ completeShuffleMapStageSuccessfully(0, attempt, numShufflePartitions =
parts,
+ Seq("hostA", "hostB"))
+
+ taskScheduler.executorDecommission("hostA-exec",
ExecutorDecommissionInfo(""))
+ // Now we should have a new taskSet, for a new attempt of stage 1.
+ // Fail all these tasks with FetchFailure
+ completeNextStageWithFetchFailure(1, attempt, shuffleDep)
+
+ // this will trigger a resubmission of stage 0, since we've lost some of
its
+ // map output, for the next iteration through the loop
+ scheduler.resubmitFailedStages()
+ }
+
+ // Confirm job finished successfully
+ sc.listenerBus.waitUntilEmpty()
+ assert(scheduler.runningStages.nonEmpty)
+ assert(!ended)
+
Review Comment:
Shall we clean up this redundant empty line?
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