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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:44:15 UTC
[jira] [Resolved] (SPARK-23704) PySpark access of individual trees
in random forest is slow
[ https://issues.apache.org/jira/browse/SPARK-23704?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-23704.
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Resolution: Incomplete
> PySpark access of individual trees in random forest is slow
> -----------------------------------------------------------
>
> Key: SPARK-23704
> URL: https://issues.apache.org/jira/browse/SPARK-23704
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 2.2.1
> Environment: PySpark 2.2.1 / Windows 10
> Reporter: Julian King
> Priority: Minor
> Labels: bulk-closed
>
> Making predictions from a randomForestClassifier PySpark is much faster than making predictions from an individual tree contained within the .trees attribute.
> In fact, the model.transform call without an action is more than 10x slower for an individual tree vs the model.transform call for the random forest model.
> See [https://stackoverflow.com/questions/49297470/slow-individual-tree-access-for-random-forest-in-pyspark] for example with timing.
> Ideally:
> * Getting a prediction from a single tree should be comparable to or faster than getting predictions from the whole tree
> * Getting all the predictions from all the individual trees should be comparable in speed to getting the predictions from the random forest
>
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