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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/12/30 10:40:58 UTC
[jira] [Resolved] (SPARK-18808) ml.KMeansModel.transform is very
inefficient
[ https://issues.apache.org/jira/browse/SPARK-18808?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-18808.
-------------------------------
Resolution: Fixed
Fix Version/s: 2.2.0
Issue resolved by pull request 16328
[https://github.com/apache/spark/pull/16328]
> ml.KMeansModel.transform is very inefficient
> --------------------------------------------
>
> Key: SPARK-18808
> URL: https://issues.apache.org/jira/browse/SPARK-18808
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.0.2
> Reporter: Michel Lemay
> Fix For: 2.2.0
>
>
> The function ml.KMeansModel.transform will call the parentModel.predict(features) method on each row which in turns will normalize all clusterCenters from mllib.KMeansModel.clusterCentersWithNorm every time!
> This is a serious waste of resources! In my profiling, clusterCentersWithNorm represent 99% of the sampling!
> This should have been implemented with a broadcast variable as it is done in other functions like computeCost.
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