Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/5636#discussion_r29690461
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala ---
@@ -475,7 +475,148 @@ class DAGSchedulerSuite
assert(results === Map(0 -> 42, 1 -> 43))
assertDataStructuresEmpty()
}
+
+ test("Multiple consecutive stage failures should lead to stage being
aborted.") {
+ // Create a new Listener to confirm that the listenerBus sees the
JobEnd message
+ // when we abort the stage. This message will also be consumed by the
EventLoggingListener
+ // so this will propagate up to the user.
+ var ended = false
+ var jobResult : JobResult = null
+ class EndListener extends SparkListener {
+ override def onJobEnd(jobEnd: SparkListenerJobEnd): Unit = {
+ jobResult = jobEnd.jobResult
+ ended = true
+ }
+ }
+
+ sc.listenerBus.addListener(new EndListener())
+
+ val shuffleMapRdd = new MyRDD(sc, 2, Nil)
+ val shuffleDep = new ShuffleDependency(shuffleMapRdd, null)
+ val shuffleId = shuffleDep.shuffleId
+ val reduceRdd = new MyRDD(sc, 2, List(shuffleDep))
+ submit(reduceRdd, Array(0, 1))
+
+ complete(taskSets(0), Seq(
+ (Success, makeMapStatus("hostA", 1)),
+ (Success, makeMapStatus("hostB", 1))))
+
+ for (x <- 1 to Stage.MAX_STAGE_FAILURES) {
+ // the 2nd ResultTask failed
+ complete(taskSets(1), Seq(
--- End diff --
each time a stage is failed and re-attempted, we create a new taskSet. so
we're actually just sending these events for the same attempt over and over,
we're not having multiple attempts fail w/ `FetchFailed`. (This is why you
see the `attemptId` as `0` all the time.)
each failure will trigger a new attempt for stage 0, which we should
complete successfully, and then it will submit a new attempt for stage 1, which
we should fail again.
What I still don't understand is how we are passing the checks in the
`else` branch below ...
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