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https://issues.apache.org/jira/browse/SPARK-35022?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-35022:
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Assignee: L. C. Hsieh (was: Apache Spark)
> Task Scheduling Plugin in Spark
> -------------------------------
>
> Key: SPARK-35022
> URL: https://issues.apache.org/jira/browse/SPARK-35022
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 3.2.0
> Reporter: L. C. Hsieh
> Assignee: L. C. Hsieh
> Priority: Major
>
> Spark scheduler schedules tasks to executors in an arbitrary way. The
> schedule schedules the tasks by itself. Although there is locality
> configuration, the configuration is used for data locality purposes.
> Generally we cannot suggest the scheduler where a task should be scheduled
> to. Normally it is not a problem because the general task is
> executor-agnostic. But for special tasks, for example stateful tasks in
> Structured Streaming, state store is maintained at the executor side.
> Changing task location means reloading checkpoint data from the last batch.
> It has disadvantages from the performance perspective and also casts some
> limitations when we want to implement advanced features in Structured
> Streaming.
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