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From "Wenchen Fan (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-21972) Allow users to control input data persistence in ML Estimators via a handlePersistence ml.Param
Date Mon, 10 Sep 2018 14:31:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21972?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Wenchen Fan updated SPARK-21972:
--------------------------------
    Target Version/s:   (was: 2.4.0)

> Allow users to control input data persistence in ML Estimators via a handlePersistence
ml.Param
> -----------------------------------------------------------------------------------------------
>
>                 Key: SPARK-21972
>                 URL: https://issues.apache.org/jira/browse/SPARK-21972
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, MLlib
>    Affects Versions: 2.2.0
>            Reporter: Siddharth Murching
>            Priority: Major
>
> Several Spark ML algorithms (LogisticRegression, LinearRegression, KMeans, etc) call
{{cache()}} on uncached input datasets to improve performance.
> Unfortunately, these algorithms a) check input persistence inaccurately ([SPARK-18608|https://issues.apache.org/jira/browse/SPARK-18608])
and b) check the persistence level of the input dataset but not any of its parents. These
issues can result in unwanted double-caching of input data & degraded performance (see
[SPARK-21799|https://issues.apache.org/jira/browse/SPARK-21799]).
> This ticket proposes adding a boolean {{handlePersistence}} param (org.apache.spark.ml.param)
so that users can specify whether an ML algorithm should try to cache un-cached input data.
{{handlePersistence}} will be {{true}} by default, corresponding to existing behavior (always
persisting uncached input), but users can achieve finer-grained control over input persistence
by setting {{handlePersistence}} to {{false}}.



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