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https://issues.apache.org/jira/browse/SPARK-14671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley resolved SPARK-14671.
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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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