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https://issues.apache.org/jira/browse/SPARK-21082?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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DjvuLee updated SPARK-21082:
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Affects Version/s: (was: 2.2.1)
2.3.0
> Consider Executor's memory usage when scheduling task
> ------------------------------------------------------
>
> Key: SPARK-21082
> URL: https://issues.apache.org/jira/browse/SPARK-21082
> Project: Spark
> Issue Type: Improvement
> Components: Scheduler, Spark Core
> Affects Versions: 2.3.0
> Reporter: DjvuLee
>
> Spark Scheduler do not consider the memory usage during dispatch tasks, this
> can lead to Executor OOM if the RDD is cached sometimes, because Spark can
> not estimate the memory usage well enough(especially when the RDD type is not
> flatten), scheduler may dispatch so many tasks on one Executor.
> We can offer a configuration for user to decide whether scheduler will
> consider the memory usage.
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