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Posted to issues@spark.apache.org by "Felix Cheung (JIRA)" <ji...@apache.org> on 2017/01/22 00:46:26 UTC

[jira] [Commented] (SPARK-16693) Remove R deprecated methods

    [ https://issues.apache.org/jira/browse/SPARK-16693?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15833206#comment-15833206 ] 

Felix Cheung commented on SPARK-16693:
--------------------------------------

I want to bring this up again and potentially to discuss in dev@, now that we are on Spark 2.2.

Not only having these are harder to work with, making it harder to add new parameter (eg. numPartitions) and so on, but more importantly, the wrapper/stub methods (e.g createDataFrame.default) shows up in auto-complete, tooltips, help doc and so on and create confusion.

Moreover, on a slightly orthogonal note, we should also consider removing all the internal RDD methods, or at least making them non-export S3 methods. Right now every time we are adding a new method having the same name of the existing, internal-only RDD method in R we would need to update the generic, and rename the existing method (by appending "RDD" to its name), and all its call sites, otherwise we would get a check-cran warning of lacking documentation. And by adding such method to the NAMESPACE file the existing RDD-only will get exposed as well (again showing up in auto-complete etc.), unless it is renamed. Since we are renaming the existing method to fix this, we are also breaking backward compatibility anyway (although the method was not public so strictly speaking there has not been any guarantee).

But I could scope this JIRA to only sqlContext methods and leave this 2nd issue to a different JIRA.


> Remove R deprecated methods
> ---------------------------
>
>                 Key: SPARK-16693
>                 URL: https://issues.apache.org/jira/browse/SPARK-16693
>             Project: Spark
>          Issue Type: Bug
>          Components: SparkR
>    Affects Versions: 2.0.0
>            Reporter: Felix Cheung
>
> For methods deprecated in Spark 2.0.0, we should remove them in 2.1.0



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