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https://issues.apache.org/jira/browse/SPARK-35677?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18004149#comment-18004149
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Ming Li commented on SPARK-35677:
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[~Qin Yao] hi, has there been any further progress on this PR? Is it possible
to dynamically adjust maxExecutors? :)
> Support dynamic executor range for dynamic allocation
> -----------------------------------------------------
>
> Key: SPARK-35677
> URL: https://issues.apache.org/jira/browse/SPARK-35677
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core, SQL
> Affects Versions: 3.2.0
> Reporter: Kent Yao 2
> Priority: Major
> Labels: pull-request-available
>
> Currently, Spark allows users to set scalability within a Spark application
> using dynamic allocation. spark.dynamicAllocation.minExecutors &
> spark.dynamicAllocation.maxExecutors are used for scaling up and down. Within
> an application，Spark tactfully use them to request executors from cluster
> manager according to the real-time workload. Once set, the range is fixed
> through the whole application lifecycle. This is not very convenient for
> long-running application when the range should be changeable for some cases,
> such as:
> 1. the cluster manager itself or the queue will scale up and down, which
> looks very likely to happen in modern cloud platforms
> 2. the application is long-running, but the timeliness, priority, e.t.c are
> not only determined by the workload with the application, but also by the
> traffic across the cluster manager or just different moments
> 3. e.t.c.
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