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https://issues.apache.org/jira/browse/SPARK-16519?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15380512#comment-15380512
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Shivaram Venkataraman commented on SPARK-16519:
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Thanks - the only things to keep in mind here are that we use some of these RDD
functions to implement things like spark.lapply and createDataFrame. So we need
to keep those working maybe by using some renamed internal functions.
> Handle SparkR RDD generics that create warnings in R CMD check
> --------------------------------------------------------------
>
> Key: SPARK-16519
> URL: https://issues.apache.org/jira/browse/SPARK-16519
> Project: Spark
> Issue Type: Sub-task
> Components: SparkR
> Reporter: Shivaram Venkataraman
>
> One of the warnings we get from R CMD check is that RDD implementations of
> some of the generics are not documented. These generics are shared between
> RDD, DataFrames in SparkR. The list includes
> {quote}
> WARNING
> Undocumented S4 methods:
> generic 'cache' and siglist 'RDD'
> generic 'collect' and siglist 'RDD'
> generic 'count' and siglist 'RDD'
> generic 'distinct' and siglist 'RDD'
> generic 'first' and siglist 'RDD'
> generic 'join' and siglist 'RDD,RDD'
> generic 'length' and siglist 'RDD'
> generic 'partitionBy' and siglist 'RDD'
> generic 'persist' and siglist 'RDD,character'
> generic 'repartition' and siglist 'RDD'
> generic 'show' and siglist 'RDD'
> generic 'take' and siglist 'RDD,numeric'
> generic 'unpersist' and siglist 'RDD'
> {quote}
> As described in
> https://stat.ethz.ch/pipermail/r-devel/2003-September/027490.html this looks
> like a limitation of R where exporting a generic from a package also exports
> all the implementations of that generic.
> One way to get around this is to remove the RDD API or rename the methods in
> Spark 2.1
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