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https://issues.apache.org/jira/browse/SPARK-4585?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14224244#comment-14224244
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Sean Owen commented on SPARK-4585:
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Given the discussion in SPARK-3174, it seems like this behavior is actually
more desirable for Hive. At least there's a good argument for it, so I am not
sure selecting the minimum is better. It's not a bug in any event; is there a
smarter heuristic available and proposed here?
> Spark dynamic scaling executors use upper limit value as default.
> -----------------------------------------------------------------
>
> Key: SPARK-4585
> URL: https://issues.apache.org/jira/browse/SPARK-4585
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, YARN
> Affects Versions: 1.1.0
> Reporter: Chengxiang Li
>
> With SPARK-3174, one can configure a minimum and maximum number of executors
> for a Spark application on Yarn. However, the application always starts with
> the maximum. It seems more reasonable, at least for Hive on Spark, to start
> from the minimum and scale up as needed up to the maximum.
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