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Posted to issues@spark.apache.org by "Andrew Or (JIRA)" <ji...@apache.org> on 2015/01/21 19:50:35 UTC
[jira] [Closed] (SPARK-4759) Deadlock in complex spark job in local
mode
[ https://issues.apache.org/jira/browse/SPARK-4759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Andrew Or closed SPARK-4759.
----------------------------
Resolution: Fixed
Fix Version/s: 1.2.0
> Deadlock in complex spark job in local mode
> -------------------------------------------
>
> Key: SPARK-4759
> URL: https://issues.apache.org/jira/browse/SPARK-4759
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.1.1, 1.2.0, 1.3.0
> Environment: Java version "1.7.0_51"
> Java(TM) SE Runtime Environment (build 1.7.0_51-b13)
> Java HotSpot(TM) 64-Bit Server VM (build 24.51-b03, mixed mode)
> Mac OSX 10.10.1
> Using local spark context
> Reporter: Davis Shepherd
> Assignee: Andrew Or
> Priority: Critical
> Labels: backport-needed
> Fix For: 1.3.0, 1.1.2, 1.2.0
>
> Attachments: SparkBugReplicator.scala
>
>
> The attached test class runs two identical jobs that perform some iterative computation on an RDD[(Int, Int)]. This computation involves
> # taking new data merging it with the previous result
> # caching and checkpointing the new result
> # rinse and repeat
> The first time the job is run, it runs successfully, and the spark context is shut down. The second time the job is run with a new spark context in the same process, the job hangs indefinitely, only having scheduled a subset of the necessary tasks for the final stage.
> Ive been able to produce a test case that reproduces the issue, and I've added some comments where some knockout experimentation has left some breadcrumbs as to where the issue might be.
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