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Posted to issues@spark.apache.org by "coneyliu (JIRA)" <ji...@apache.org> on 2017/06/21 08:02:00 UTC
[jira] [Comment Edited] (SPARK-19293) Spark 2.1.x unstable with
spark.speculation=true
[ https://issues.apache.org/jira/browse/SPARK-19293?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16057127#comment-16057127 ]
coneyliu edited comment on SPARK-19293 at 6/21/17 8:01 AM:
-----------------------------------------------------------
Have you tried the latest code? The exceptions you give are all about `InterruptedException` and `RuntimeException`, those seems have been fixed in recently patch, such as SPARK-20358 and more.
was (Author: coneyliu):
Have you tried the latest code? The exceptions you give are all about `InterruptedException` and `RuntimeException`, those seems have been fixed in recently path, such as #SPARK-20358 and more.
> Spark 2.1.x unstable with spark.speculation=true
> ------------------------------------------------
>
> Key: SPARK-19293
> URL: https://issues.apache.org/jira/browse/SPARK-19293
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0, 2.1.1
> Reporter: Damian Momot
> Priority: Critical
>
> After upgrading from Spark 2.0.2 to 2.1.0 we've observed that jobs are often failing when speculative mode is enabled.
> In 2.0.2 speculative tasks were simply skipped if they were not used for result (i.e. other instance finished earlier) - and it was clearly visible in UI that those tasks were not counted as failures.
> In 2.1.0 many tasks are being marked failed/killed when speculative tasks start to run (that is at the end of stage when there are spare executors to use) which also leads to entire stage/job failures.
> Disabling spark.speculation solves failing problem - but speculative mode is very useful especially when different executors run on machines with varying load (for example in YARN)
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