[ https://issues.apache.org/jira/browse/SPARK-18808?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-18808: ------------------------------ Priority: Minor (was: Major) > 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 > Assignee: Sean Owen > Priority: Minor > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org