Github user kayousterhout commented on a diff in the pull request: https://github.com/apache/spark/pull/15213#discussion_r80845128 --- Diff: core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala --- @@ -2105,6 +2107,59 @@ class DAGSchedulerSuite extends SparkFunSuite with LocalSparkContext with Timeou assert(scheduler.getShuffleDependencies(rddE) === Set(shuffleDepA, shuffleDepC)) } + test("After one stage is aborted for too many failed attempts, subsequent stages" + + "still behave correctly on fetch failures") { + def fetchFailJob: Unit = { + val rdd1 = sc.makeRDD(Array(1, 2, 3, 4), 2).map(x => (x, 1)).groupByKey() + val shuffleHandle = + rdd1.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleHandle + rdd1.map { + case (x, _) if (x == 1) => + throw new FetchFailedException( + BlockManagerId("1", "1", 1), shuffleHandle.shuffleId, 0, 0, "test") + case (x, _) => x + }.count() + } + + def successJob: Unit = { + object FailThisAttempt { + val _fail = new AtomicBoolean(true) + } + val rdd1 = sc.makeRDD(Array(1, 2, 3, 4), 2).map(x => (x, 1)).groupByKey() + val shuffleHandle = + rdd1.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleHandle + rdd1.map { + case (x, _) if (x == 1) && FailThisAttempt._fail.getAndSet(false) => + throw new FetchFailedException( + BlockManagerId("1", "1", 1), shuffleHandle.shuffleId, 0, 0, "test") + } + } + + failAfter(60.seconds) { + val e = intercept[SparkException] { + fetchFailJob + } + assert(e.getMessage.contains("org.apache.spark.shuffle.FetchFailedException")) + } + + // The following job that fails due to fetching failure will hang without + // the fix for SPARK-17644 + failAfter(60.seconds) { --- End diff -- I think a shorter timeout would be appropriate here to avoid slow-ness when this fails...maybe 10 seconds? That still seems plenty conservative since the resubmit timeout is 200 millis.
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