Github user xuanyuanking commented on a diff in the pull request:
https://github.com/apache/spark/pull/20930#discussion_r184276403
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala ---
@@ -2399,6 +2399,84 @@ class DAGSchedulerSuite extends SparkFunSuite with
LocalSparkContext with TimeLi
}
}
+ /**
+ * This tests the case where origin task success after speculative task
got FetchFailed
+ * before.
+ */
+ test("SPARK-23811: ShuffleMapStage failed by FetchFailed should ignore
following " +
+ "successful tasks") {
+ // 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)
+ // The second result task self success soon.
+ runEvent(makeCompletionEvent(
+ taskSets(1).tasks(1), Success, makeMapStatus("hostB", 2)))
+ // Missing partition number should not change, otherwise it will cause
child stage
+ // never succeed.
+
assert(mapOutputTracker.findMissingPartitions(shuffleDepB.shuffleId).get.size
=== 1)
+ }
+
+ test("SPARK-23811: check ResultStage failed by FetchFailed can ignore
following " +
+ "successful tasks") {
+ 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)
+ submit(rddB, 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 of rddB success
+ assert(taskSets(1).tasks(0).isInstanceOf[ResultTask[_, _]])
+ 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))
+ // Make sure failedStage is not empty now
+ assert(scheduler.failedStages.nonEmpty)
+ // The second result task self success soon.
+ assert(taskSets(1).tasks(1).isInstanceOf[ResultTask[_, _]])
+ runEvent(makeCompletionEvent(
+ taskSets(1).tasks(1), Success, makeMapStatus("hostB", 2)))
--- End diff --
Yep, you're right. The success completely event in UT was treated as normal
success task. I fixed this by ignore this event at the beginning of
handleTaskCompletion.
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