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https://issues.apache.org/jira/browse/SPARK-15944?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15329666#comment-15329666
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yuhao yang commented on SPARK-15944:
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This looks practical. Just want to check if this is a temporary behavior that
will be deprecated in this or next release. If so, we should add notes to
remind users.
> Make spark.ml package backward compatible with spark.mllib vectors
> ------------------------------------------------------------------
>
> Key: SPARK-15944
> URL: https://issues.apache.org/jira/browse/SPARK-15944
> Project: Spark
> Issue Type: Umbrella
> Components: ML, MLlib
> Affects Versions: 2.0.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
> Priority: Critical
>
> During QA, we found that it is not trivial to convert a DataFrame with old
> vector columns to new vector columns. So it would be easier for users to
> migrate their datasets and pipelines if we:
> 1) provide utils to convert DataFrames with vector columns
> 2) automatically detect and convert old vector columns in ML pipelines
> This is an umbrella JIRA to track the progress.
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