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https://issues.apache.org/jira/browse/SPARK-11278?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15614954#comment-15614954
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Vivek Gupta commented on SPARK-11278:
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We are facing an issue with Spark 1.6.0 whereby performance degrades severely
(with extensive Shuffle spill) using the Unified Memory Manager
(spark.memory.fraction = 0.9 and spark.memory.storageFraction = 0.0).
However same application works with improved performance having switched to
legacy mode (spark.memory.useLegacyMode=true, spark.shuffle.memoryFraction=0.9,
spark.storage.memoryFraction=0.0).
Is this something related with this issue?
> PageRank fails with unified memory manager
> ------------------------------------------
>
> Key: SPARK-11278
> URL: https://issues.apache.org/jira/browse/SPARK-11278
> Project: Spark
> Issue Type: Bug
> Components: GraphX, Spark Core
> Affects Versions: 1.5.1
> Reporter: Nishkam Ravi
> Assignee: Andrew Or
> Priority: Critical
> Attachments: executor_log_legacyModeTrue.html,
> executor_logs_legacyModeFalse.html
>
>
> PageRank (6-nodes, 32GB input) runs very slow and eventually fails with
> ExecutorLostFailure. Traced it back to the 'unified memory manager' commit
> from Oct 13th. Took a quick look at the code and couldn't see the problem
> (changes look pretty good). cc'ing [~andrewor14][~vanzin] who may be able to
> spot the problem quickly. Can be reproduced by running PageRank on a large
> enough input dataset if needed. Sorry for not being of much help here.
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