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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