Michel Lemay created SPARK-18808:
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Summary: ml.KMeansModel.transform is very inefficient
Key: SPARK-18808
URL: https://issues.apache.org/jira/browse/SPARK-18808
Project: Spark
Issue Type: Bug
Components: ML
Affects Versions: 2.0.2
Reporter: Michel Lemay
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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