Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/6352#discussion_r31065901
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala ---
@@ -342,6 +342,35 @@ class DAGSchedulerSuite
assert(locs === Seq(Seq("hostA", "hostB"), Seq("hostB", "hostC"),
Seq("hostC", "hostD")))
}
+ /**
+ * +---+ shuffle +---+ +---+
+ * | A |<--------| B |<---| C |<--+
+ * +---+ +---+ +---+ | +---+
+ * +--| E |
+ * +---+ | +---+
+ * | D |<--+
+ * +---+
+ * Here, E has one-to-one dependencies on C and D. C is derived from A
by performing a shuffle
+ * and then a map. If we're trying to determine which ancestor stages
need to be computed in
+ * order to compute E, we need to figure out whether the shuffle A -> B
should be performed.
+ * If the RDD C, which has only one ancestor via a narrow dependency, is
cached, then we won't
+ * need to compute A, even if it has some unavailable output partitions.
The same goes for B:
+ * if B is 100% cached, then we can avoid the shuffle on A.
+ */
+ test("SPARK-7826: regression test for getMissingParentStages") {
+ val rddA = new MyRDD(sc, 1, Nil)
+ val rddB = new MyRDD(sc, 1, List(new ShuffleDependency(rddA, null)))
+ val rddC = new MyRDD(sc, 1, List(new OneToOneDependency(rddB))).cache()
+ val rddD = new MyRDD(sc, 1, Nil)
+ val rddE = new MyRDD(sc, 1,
+ List(new OneToOneDependency(rddC), new OneToOneDependency(rddD)))
+ cacheLocations(rddC.id -> 0) =
+ Seq(makeBlockManagerId("hostA"), makeBlockManagerId("hostB"))
+ val jobId = submit(rddE, Array(0))
+ val finalStage = scheduler.jobIdToActiveJob(jobId).finalStage
+ assert(scheduler.getMissingParentStages(finalStage).size === 0)
--- End diff --
Since there's a one-to-one dependency from D to E, won't D and E be
computed in the same stage?
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