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https://issues.apache.org/jira/browse/SPARK-13184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15262299#comment-15262299
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koert kuipers commented on SPARK-13184:
---------------------------------------
my only reservation is that these are spark-wide settings, while i think we
need to be able to set this per source. basically i would want to be able to
say something like:
{noformat}
sqlContext
.read
.format("csv")
.option("maxPartitionBytes", "1000000")
.load("/some/path")
{noformat}
> 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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