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https://issues.apache.org/jira/browse/SPARK-7230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14520479#comment-14520479
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Antonio Piccolboni commented on SPARK-7230:
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If you make a call  private, you break every single package that uses it. It's 
the same as erasing the code. What do you want me to do, to sprinkle my code 
with SparkR::: to make it work? Fork SparkR to maintain a different NAMESPACE 
file? The reasonable course here is to a) announce big changes in the API and 
call for proposals, discussion. check b) implement new API, say 1.5 c) retire 
old API. It looks to me you are applying an arbitrary permutation of those 
steps. 

> Make RDD API private in SparkR for Spark 1.4
> --------------------------------------------
>
>                 Key: SPARK-7230
>                 URL: https://issues.apache.org/jira/browse/SPARK-7230
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SparkR
>    Affects Versions: 1.4.0
>            Reporter: Shivaram Venkataraman
>            Assignee: Shivaram Venkataraman
>            Priority: Critical
>
> This ticket proposes making the RDD API in SparkR private for the 1.4 
> release. The motivation for doing so are discussed in a larger design 
> document aimed at a more top-down design of the SparkR APIs. A first cut that 
> discusses motivation and proposed changes can be found at http://goo.gl/GLHKZI
> The main points in that document that relate to this ticket are:
> - The RDD API requires knowledge of the distributed system and is pretty low 
> level. This is not very suitable for a number of R users who are used to more 
> high-level packages that work out of the box.
> - The RDD implementation in SparkR is not fully robust right now: we are 
> missing features like spilling for aggregation, handling partitions which 
> don't fit in memory etc. There are further limitations like lack of hashCode 
> for non-native types etc. which might affect user experience.
> The only change we will make for now is to not export the RDD functions as 
> public methods in the SparkR package and I will create another ticket for 
> discussing more details public API for 1.5



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