[
https://issues.apache.org/jira/browse/SPARK-13184?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15227657#comment-15227657
]
koert kuipers commented on SPARK-13184:
---------------------------------------
i am not familiar with those settings.
are they respected by all data sources that are based on HadoopFsRelation (or
whatever is the successor of HadoopFsRelation)?
by lowering maxPartitionBytes can i increase the number of partitions? and this
is pushed down to the reading of the data, not a shuffle afterwards?
thanks! best, koert
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
