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https://issues.apache.org/jira/browse/SPARK-5997?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17462805#comment-17462805
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Nicholas Chammas commented on SPARK-5997:
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[~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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