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https://issues.apache.org/jira/browse/SPARK-17020?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15417218#comment-15417218
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Roi Reshef commented on SPARK-17020:
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[~srowen] Should there be any effect on this if I cached and materialized the
DF befor I call on .rdd?
> Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data
> ------------------------------------------------------------------------------
>
> Key: SPARK-17020
> URL: https://issues.apache.org/jira/browse/SPARK-17020
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 1.6.1, 1.6.2, 2.0.0
> Reporter: Roi Reshef
> Priority: Critical
> Attachments: dataframe_cache.PNG, rdd_cache.PNG
>
>
> Calling DataFrame's lazy val .rdd results with a new RDD with a poor
> distribution of partitions across the cluster. Moreover, any attempt to
> repartition this RDD further will fail.
> Attached are a screenshot of the original DataFrame on cache and the
> resulting RDD on cache.
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