[jira] [Commented] (SPARK-14450) Python OneVsRest should train multiple models at once

["fanlu (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-14450?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15653309#comment-15653309 ] 

fanlu commented on SPARK-14450:
-------------------------------

Why scala version does not need to use parallelization

> Python OneVsRest should train multiple models at once
> -----------------------------------------------------
>
>                 Key: SPARK-14450
>                 URL: https://issues.apache.org/jira/browse/SPARK-14450
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, PySpark
>            Reporter: Joseph K. Bradley
>
> [SPARK-7861] adds a Python wrapper for OneVsRest.  Because of possible issues related to using existing libraries like {{multiprocessing}}, we are not training multiple models in parallel initially.
> This issue is for prototyping, testing, and implementing a way to train multiple models at once.  Speaking with [~joshrosen], a good option might be the concurrent.futures package:
> * Python 3.x: [https://docs.python.org/3/library/concurrent.futures.html#module-concurrent.futures]
> * Python 2.x: [https://pypi.python.org/pypi/futures]
> We will *not* add this for Spark 2.0, but it will be good to investigate for 2.1.



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