[jira] [Resolved] (SPARK-17090) Make tree aggregation level in linear/logistic regression configurable

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

     [ https://issues.apache.org/jira/browse/SPARK-17090?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

DB Tsai resolved SPARK-17090.
-----------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

Issue resolved by pull request 14717
[https://github.com/apache/spark/pull/14717]

> Make tree aggregation level in linear/logistic regression configurable
> ----------------------------------------------------------------------
>
>                 Key: SPARK-17090
>                 URL: https://issues.apache.org/jira/browse/SPARK-17090
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML
>            Reporter: Seth Hendrickson
>            Priority: Minor
>             Fix For: 2.1.0
>
>
> Linear/logistic regression use treeAggregate with default aggregation depth for collecting coefficient gradient updates to the driver. For high dimensional problems, this can case OOM error on the driver. We should make it configurable, perhaps via an expert param, so that users can avoid this problem if their data has many features.



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