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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/11/02 00:14:59 UTC

[jira] [Resolved] (SPARK-15944) Make spark.ml package backward compatible with spark.mllib vectors

     [ https://issues.apache.org/jira/browse/SPARK-15944?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-15944.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

> 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
>             Fix For: 2.1.0
>
>
> 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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