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https://issues.apache.org/jira/browse/SPARK-16611?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15398346#comment-15398346
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Clark Fitzgerald commented on SPARK-16611:
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+1 for more direct access to the RDD's. This would be very helpful for me as I
try to implement general R objects using Spark as a backend for ddR
https://github.com/vertica/ddR
Longer term it might make sense to organize SparkR into separate packages
offering various levels of abstraction:
# dataframes - for most end users
# RDD's - for package authors or special applications
# Java objects - for directly invoking methods in Spark. This is what sparkapi
does.
For my application it would be much better to be working at this middle layer.
> Expose several hidden DataFrame/RDD functions
> ---------------------------------------------
>
> Key: SPARK-16611
> URL: https://issues.apache.org/jira/browse/SPARK-16611
> Project: Spark
> Issue Type: Improvement
> Components: SparkR
> Reporter: Oscar D. Lara Yejas
>
> Expose the following functions:
> - lapply or map
> - lapplyPartition or mapPartition
> - flatMap
> - RDD
> - toRDD
> - getJRDD
> - cleanup.jobj
> cc:
> [~javierluraschi] [~j...@rstudio.com] [~shivaram]
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