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https://issues.apache.org/jira/browse/SPARK-7230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14520635#comment-14520635
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Patrick Wendell commented on SPARK-7230:
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Yes - removing API's is really difficult for existing users. That's why the
proposal here will limit the number of exposed API's substantially, because
otherwise we will never be able to remove them. Part of merging into the
upstream project is looking at which API's the commitership are comfortable
supporting in the long term. As it stands, there isn't widespread support in
the committership for supporting low level ETL code in R in the long term. We'd
rather have narrower and simpler API's.
Of course we'll make a good faith effort to support API's that are useful to
existing projects.
> 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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