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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Work logged] (BEAM-4783) Spark SourceRDD Not Designed With Dynamic Allocation In Mind
Date Fri, 24 Aug 2018 20:44:00 GMT

     [ https://issues.apache.org/jira/browse/BEAM-4783?focusedWorklogId=137965&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-137965
]

ASF GitHub Bot logged work on BEAM-4783:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 24/Aug/18 20:43
            Start Date: 24/Aug/18 20:43
    Worklog Time Spent: 10m 
      Work Description: apilloud commented on issue #6181: [BEAM-4783] Add bundleSize for
splitting BoundedSources.
URL: https://github.com/apache/beam/pull/6181#issuecomment-415877315
 
 
   Java PreCommits are failing due to unused imports. Can you run `./gradlew :beam-runners-spark:spotlessApply`?
   
   ping @chamikaramj 

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Issue Time Tracking
-------------------

    Worklog Id:     (was: 137965)
    Time Spent: 0.5h  (was: 20m)

> Spark SourceRDD Not Designed With Dynamic Allocation In Mind
> ------------------------------------------------------------
>
>                 Key: BEAM-4783
>                 URL: https://issues.apache.org/jira/browse/BEAM-4783
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-spark
>    Affects Versions: 2.5.0
>            Reporter: Kyle Winkelman
>            Assignee: Jean-Baptiste Onofré
>            Priority: Major
>              Labels: newbie
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> When the spark-runner is used along with the configuration spark.dynamicAllocation.enabled=true
the SourceRDD does not detect this. It then falls back to the value calculated in this description:
>       // when running on YARN/SparkDeploy it's the result of max(totalCores, 2).
>       // when running on Mesos it's 8.
>       // when running local it's the total number of cores (local = 1, local[N] = N,
>       // local[*] = estimation of the machine's cores).
>       // ** the configuration "spark.default.parallelism" takes precedence over all of
the above **
> So in most cases this default is quite small. This is an issue when using a very large
input file as it will only get split in half.
> I believe that when Dynamic Allocation is enable the SourceRDD should use the DEFAULT_BUNDLE_SIZE
and possibly expose a SparkPipelineOptions that allows you to change this DEFAULT_BUNDLE_SIZE.



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