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From "Shivaram Venkataraman (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-16519) Handle SparkR RDD generics that create warnings in R CMD check
Date Tue, 16 Aug 2016 18:28:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-16519?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Shivaram Venkataraman updated SPARK-16519:
------------------------------------------
    Assignee: Felix Cheung

> 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
>            Assignee: Felix Cheung
>             Fix For: 2.0.1, 2.1.0
>
>
> 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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