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Posted to issues@spark.apache.org by "Nicholas Chammas (Jira)" <ji...@apache.org> on 2021/12/20 19:37:00 UTC
[jira] (SPARK-5997) Increase partition count without performing a shuffle
[ https://issues.apache.org/jira/browse/SPARK-5997 ]
Nicholas Chammas deleted comment on SPARK-5997:
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was (Author: nchammas):
[~tenstriker] - I believe in your case you should be able to set {{spark.sql.files.maxRecordsPerFile}} to some number. Spark will not shuffle the data but it will still split up your output across multiple files.
> Increase partition count without performing a shuffle
> -----------------------------------------------------
>
> Key: SPARK-5997
> URL: https://issues.apache.org/jira/browse/SPARK-5997
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Reporter: Andrew Ash
> Priority: Major
>
> When decreasing partition count with rdd.repartition() or rdd.coalesce(), the user has the ability to choose whether or not to perform a shuffle. However when increasing partition count there is no option of whether to perform a shuffle or not -- a shuffle always occurs.
> This Jira is to create a {{rdd.repartition(largeNum, shuffle=false)}} call that performs a repartition to a higher partition count without a shuffle.
> The motivating use case is to decrease the size of an individual partition enough that the .toLocalIterator has significantly reduced memory pressure on the driver, as it loads a partition at a time into the driver.
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