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Posted to issues@spark.apache.org by "yuhao yang (JIRA)" <ji...@apache.org> on 2016/06/14 15:26:01 UTC
[jira] [Commented] (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:comment-tabpanel&focusedCommentId=15329666#comment-15329666 ]
yuhao yang commented on SPARK-15944:
------------------------------------
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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