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https://issues.apache.org/jira/browse/SPARK-3174?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14160914#comment-14160914
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Andrew Or commented on SPARK-3174:
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Hi all, I have attached an updated design doc that details the various
components of the proposed solution. It summarizes the considerations in each
component and explains why we have chosen the approaches outlined in the doc.
The re-organization of this issue corresponds to the main components of the
design as follows:
(1) Heuristics for scaling executors (SPARK-3795)
(2) Mechanism for scaling executors (SPARK-3822)
(3) Graceful decommission of executors (SPARK-3796 / SPARK-3797)
Let me know if you have any questions or feedback.
> 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,
> 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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