Github user xuanyuanking commented on the issue:
https://github.com/apache/spark/pull/20930
The scenario can be reproduced by below test case added in
`DAGSchedulerSuite`
```scala
/**
* This tests the case where origin task success after speculative task
got FetchFailed
* before.
*/
test("[SPARK-23811] Fetch failed task should kill other attempt") {
// Create 3 RDDs with shuffle dependencies on each other: rddA <---
rddB <--- rddC
val rddA = new MyRDD(sc, 2, Nil)
val shuffleDepA = new ShuffleDependency(rddA, new HashPartitioner(2))
val shuffleIdA = shuffleDepA.shuffleId
val rddB = new MyRDD(sc, 2, List(shuffleDepA), tracker =
mapOutputTracker)
val shuffleDepB = new ShuffleDependency(rddB, new HashPartitioner(2))
val rddC = new MyRDD(sc, 2, List(shuffleDepB), tracker =
mapOutputTracker)
submit(rddC, Array(0, 1))
// Complete both tasks in rddA.
assert(taskSets(0).stageId === 0 && taskSets(0).stageAttemptId === 0)
complete(taskSets(0), Seq(
(Success, makeMapStatus("hostA", 2)),
(Success, makeMapStatus("hostB", 2))))
// The first task success
runEvent(makeCompletionEvent(
taskSets(1).tasks(0), Success, makeMapStatus("hostB", 2)))
// The second task's speculative attempt fails first, but task self
still running.
// This may caused by ExecutorLost.
runEvent(makeCompletionEvent(
taskSets(1).tasks(1),
FetchFailed(makeBlockManagerId("hostA"), shuffleIdA, 0, 0, "ignored"),
null))
// Check currently missing partition
assert(mapOutputTracker.findMissingPartitions(shuffleDepB.shuffleId).get.size
=== 1)
val missingPartition =
mapOutputTracker.findMissingPartitions(shuffleDepB.shuffleId).get(0)
// The second result task self success soon
runEvent(makeCompletionEvent(
taskSets(1).tasks(1), Success, makeMapStatus("hostB", 2)))
// No missing partitions here, this will cause child stage never succeed
assert(mapOutputTracker.findMissingPartitions(shuffleDepB.shuffleId).get.size
=== 0)
}
```
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