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https://issues.apache.org/jira/browse/SPARK-4085?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kay Ousterhout updated SPARK-4085:
----------------------------------
    Priority: Critical  (was: Major)

Upgraded to critical on [~pwendell]'s request

> Job will fail if a shuffle file that's read locally gets deleted
> ----------------------------------------------------------------
>
>                 Key: SPARK-4085
>                 URL: https://issues.apache.org/jira/browse/SPARK-4085
>             Project: Spark
>          Issue Type: Bug
>    Affects Versions: 1.2.0
>            Reporter: Kay Ousterhout
>            Assignee: Reynold Xin
>            Priority: Critical
>
> This commit: 
> https://github.com/apache/spark/commit/665e71d14debb8a7fc1547c614867a8c3b1f806a
>  changed the behavior of fetching local shuffle blocks such that if a shuffle 
> block is not found locally, the shuffle block is no longer marked as failed, 
> and a fetch failed exception is not thrown (this is because the "catch" block 
> here won't ever be invoked: 
> https://github.com/apache/spark/commit/665e71d14debb8a7fc1547c614867a8c3b1f806a#diff-e6e1631fa01e17bf851f49d30d028823R202
>  because the exception called from getLocalFromDisk() doesn't get thrown 
> until next() gets called on the iterator).
> [~rxin] [~matei] it looks like you guys changed the test for this to catch 
> the new exception that gets thrown 
> (https://github.com/apache/spark/commit/665e71d14debb8a7fc1547c614867a8c3b1f806a#diff-9c2e1918319de967045d04caf813a7d1R93).
>   Was that intentional?  Because the new exception is a SparkException and 
> not a FetchFailedException, jobs with missing local shuffle data will now 
> fail, rather than having the map stage get retried.
> This problem is reproducible with this test case:
> {code}
>   test("hash shuffle manager recovers when local shuffle files get deleted") {
>     val conf = new SparkConf(false)
>     conf.set("spark.shuffle.manager", "hash")
>     sc = new SparkContext("local", "test", conf)
>     val rdd = sc.parallelize(1 to 10, 2).map((_, 1)).reduceByKey(_+_)
>     rdd.count()
>     // Delete one of the local shuffle blocks.
>     sc.env.blockManager.diskBlockManager.getFile(new ShuffleBlockId(0, 0, 
> 0)).delete()
>     rdd.count()
>   }
> {code}
> which will fail on the second rdd.count().
> This is a regression from 1.1.



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