[jira] [Resolved] (SPARK-14671) Pipeline.setStages needs to handle Array non-covariance

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-14671.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.6.2
                   2.0.0

Issue resolved by pull request 12430
[https://github.com/apache/spark/pull/12430]

> Pipeline.setStages needs to handle Array non-covariance
> -------------------------------------------------------
>
>                 Key: SPARK-14671
>                 URL: https://issues.apache.org/jira/browse/SPARK-14671
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 1.6.1, 2.0.0
>            Reporter: Joseph K. Bradley
>            Assignee: Joseph K. Bradley
>            Priority: Minor
>             Fix For: 2.0.0, 1.6.2
>
>
> The following code worked for Spark 1.5 but fails for 1.6 (using the {{WritableStage, UnWritableStage}} classes in PipelineSuite):
> {code}
> val stages0 = Array(new UnWritableStage("b"))
> val stages1 = Array(new WritableStage("a"))
> val steps = stages0 ++ stages1
> val p = new Pipeline().setStages(steps)
> p.stages.w(steps)
> new ParamPair(p.stages, steps)
> {code}
> This also occurs with a mix of transformers from ml.feature.  It is because Java Arrays are non-covariant and the addition of MLWritable to some transformers means the {{stages0/1}} arrays above are not of type {{Array[PipelineStage]}}.



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