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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2016/06/16 21:30:05 UTC
[jira] [Commented] (SPARK-15947) Make pipeline components backward
compatible with old vector columns
[ https://issues.apache.org/jira/browse/SPARK-15947?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15334725#comment-15334725 ]
Xiangrui Meng commented on SPARK-15947:
---------------------------------------
Had an offline discussion with [~josephkb]. There would be lot of work to implement this feature and tests. A simpler choice is to ask users to manually convert the DataFrames at the beginning of the pipeline with tools implemented in SPARK-15945. Then we can update migration guide to include the error message and put this workaround there. So users can search on Google and find the solution.
I'm closing this ticket.
> Make pipeline components backward compatible with old vector columns
> --------------------------------------------------------------------
>
> Key: SPARK-15947
> URL: https://issues.apache.org/jira/browse/SPARK-15947
> Project: Spark
> Issue Type: Sub-task
> Components: ML, MLlib
> Affects Versions: 2.0.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
>
> After SPARK-15945, we should make ALL pipeline components accept old vector columns as input and do the conversion automatically (probably with a warning message), in order to smooth the migration to 2.0.
> --Note that this includes loading old saved models.-- SPARK-16000 handles backward compatibility in model loading.
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