Github user ilganeli commented on a diff in the pull request:
https://github.com/apache/spark/pull/5636#discussion_r35719942
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala ---
@@ -473,6 +473,322 @@ class DAGSchedulerSuite
assertDataStructuresEmpty()
}
+ // Helper function to validate state when creating tests for task
failures
+ def checkStageId(stageId: Int, attempt: Int, stageAttempt: TaskSet) {
+ assert(stageAttempt.stageId === stageId)
+ assert(stageAttempt.stageAttemptId == attempt)
+ }
+
+ def makeCompletions(stageAttempt: TaskSet): Seq[(Success.type,
MapStatus)] = {
+ stageAttempt.tasks.zipWithIndex.map { case (task, idx) =>
+ (Success, makeMapStatus("host" + ('A' + idx).toChar,
stageAttempt.tasks.size))
--- End diff --
Ahh makes sense.
Thank you,
Ilya Ganelin
-----Original Message-----
From: Imran Rashid
[[email protected]<mailto:[email protected]>]
Sent: Tuesday, July 28, 2015 09:09 PM Eastern Standard Time
To: apache/spark
Cc: Ganelin, Ilya
Subject: Re: [spark] [SPARK-5945] Spark should not retry a stage infinitely
on a FetchFailedException (#5636)
In
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala<https://github.com/apache/spark/pull/5636#discussion_r35719826>:
> @@ -473,6 +473,322 @@ class DAGSchedulerSuite
> assertDataStructuresEmpty()
> }
>
> + // Helper function to validate state when creating tests for task
failures
> + def checkStageId(stageId: Int, attempt: Int, stageAttempt: TaskSet) {
> + assert(stageAttempt.stageId === stageId)
> + assert(stageAttempt.stageAttemptId == attempt)
> + }
> +
> + def makeCompletions(stageAttempt: TaskSet): Seq[(Success.type,
MapStatus)] = {
> + stageAttempt.tasks.zipWithIndex.map { case (task, idx) =>
> + (Success, makeMapStatus("host" + ('A' + idx).toChar,
stageAttempt.tasks.size))
the last arg to makeMapStatus is actually the number of partitions for the
next stage, so you can't just use stageAttempt.tasks.size. You need to add a
reduceParts arg to makeCompletions.
â
Reply to this email directly or view it on
GitHub<https://github.com/apache/spark/pull/5636/files#r35719826>.
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