[jira] [Resolved] (SPARK-9310) Spark shuffle performance degrades significantly with an increased number of tasks

["Jem Tucker (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-9310?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jem Tucker resolved SPARK-9310.
-------------------------------
    Resolution: Fixed

> Spark shuffle performance degrades significantly with an increased number of tasks
> ----------------------------------------------------------------------------------
>
>                 Key: SPARK-9310
>                 URL: https://issues.apache.org/jira/browse/SPARK-9310
>             Project: Spark
>          Issue Type: Bug
>          Components: Shuffle
>    Affects Versions: 1.2.0
>         Environment: 2 node cluster - CDH 5.3.2 on CentOS 
>            Reporter: Jem Tucker
>              Labels: performance
>
> When running a large number of complex stages on high volumes of data shuffle duration increased by a factor of 3 when the parallelism was increased by a factor of 5 from 2000 to 10000. 
> In both cases tasks run for over a minute (to process approximately 2MB of data with initial parallelisation) so I ruled out any task overhead that could be causing this.
> Monitoring IO and network traffic showed that neither were at more than 10% of their potential max during shuffles and CPU utilization seemed worryingly low as well, neither are we experiencing a concerning level of garbage collection.
> Is performance of shuffles expected to be so heavily influenced by the number of tasks?  If so, is there an effective way to tune the number of partitions at run-time for different inputs? 



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