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Posted to issues@spark.apache.org by "Saurabh Agrawal (JIRA)" <ji...@apache.org> on 2017/08/23 10:45:00 UTC
[jira] [Comment Edited] (SPARK-21476) RandomForest classification
model not using broadcast in transform
[ https://issues.apache.org/jira/browse/SPARK-21476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16138214#comment-16138214 ]
Saurabh Agrawal edited comment on SPARK-21476 at 8/23/17 10:44 AM:
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[~peng.meng@intel.com] Under what circumstances will using broadcast hamper the performance? Is there an intuitive explanation why it might affect the performance negatively?
was (Author: sagraw):
[~peng.meng@intel.com] Under what circumstances will using broadcast hamper the performance?
> RandomForest classification model not using broadcast in transform
> ------------------------------------------------------------------
>
> Key: SPARK-21476
> URL: https://issues.apache.org/jira/browse/SPARK-21476
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.2.0
> Reporter: Saurabh Agrawal
>
> I notice significant task deserialization latency while running prediction with pipelines using RandomForestClassificationModel. While digging into the source, found that the transform method in RandomForestClassificationModel binds to its parent ProbabilisticClassificationModel and the only concrete definition that RandomForestClassificationModel provides and which is actually used in transform is that of predictRaw. Broadcasting is not being used in predictRaw.
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