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From "Marcelo Vanzin (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-3174) Provide elastic scaling within a Spark application
Date Tue, 14 Oct 2014 21:42:34 GMT

    [ https://issues.apache.org/jira/browse/SPARK-3174?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14171580#comment-14171580
] 

Marcelo Vanzin commented on SPARK-3174:
---------------------------------------

[~andrewor14] still regarding the shuffle service, your plan is not to use the existing ShuffleService
in Hadoop, but still deploy spark's shuffle service as a node manager aux service (in the
case of Yarn), correct? Or is that API not generic enough for Spark's needs?

> Provide elastic scaling within a Spark application
> --------------------------------------------------
>
>                 Key: SPARK-3174
>                 URL: https://issues.apache.org/jira/browse/SPARK-3174
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core, YARN
>    Affects Versions: 1.0.2
>            Reporter: Sandy Ryza
>            Assignee: Andrew Or
>         Attachments: SPARK-3174design.pdf, SparkElasticScalingDesignB.pdf, dynamic-scaling-executors-10-6-14.pdf
>
>
> A common complaint with Spark in a multi-tenant environment is that applications have
a fixed allocation that doesn't grow and shrink with their resource needs.  We're blocked
on YARN-1197 for dynamically changing the resources within executors, but we can still allocate
and discard whole executors.
> It would be useful to have some heuristics that
> * Request more executors when many pending tasks are building up
> * Discard executors when they are idle
> See the latest design doc for more information.



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