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https://issues.apache.org/jira/browse/SPARK-32112?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Noritaka Sekiyama updated SPARK-32112:
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Summary: Easier way to repartition/coalesce DataFrames based on the number
of parallel tasks that Spark can process at the same time (was: Add a method
to calculate the number of parallel tasks that Spark can process at the same
time)
> Easier way to repartition/coalesce DataFrames based on the number of parallel
> tasks that Spark can process at the same time
> ---------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-32112
> URL: https://issues.apache.org/jira/browse/SPARK-32112
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Noritaka Sekiyama
> Priority: Major
>
> Repartition/coalesce is very important to optimize Spark application's
> performance, however, a lot of users are struggling with determining the
> number of partitions.
> This issue is to add a method to calculate the number of parallel tasks that
> Spark can process at the same time.
> It will help Spark users to determine the optimal number of partitions.
> Expected use-cases:
> - repartition with the calculated parallel tasks
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