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https://issues.apache.org/jira/browse/SPARK-13184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15227435#comment-15227435
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Takeshi Yamamuro commented on SPARK-13184:
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Seems we can handle this by "spark.sql.files.maxPartitionBytes" and
"spark.sql.files.openCostInBytes".
I'm not sure we need a newer option to do this.
> Support minPartitions parameter for JSON and CSV datasources as options
> -----------------------------------------------------------------------
>
> Key: SPARK-13184
> URL: https://issues.apache.org/jira/browse/SPARK-13184
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Hyukjin Kwon
> Priority: Minor
>
> After looking through the pull requests below at Spark CSV datasources,
> https://github.com/databricks/spark-csv/pull/256
> https://github.com/databricks/spark-csv/issues/141
> https://github.com/databricks/spark-csv/pull/186
> It looks Spark might need to be able to set {{minPartitions}}.
> {{repartition()}} or {{coalesce()}} can be alternatives but it looks it needs
> to shuffle the data for most cases.
> Although I am still not sure if it needs this, I will open this ticket just
> for discussion.
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