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https://issues.apache.org/jira/browse/SPARK-4708?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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DB Tsai updated SPARK-4708:
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Summary: Make k-mean runs two/three times faster with dense/sparse sample
(was: k-mean runs two/three times faster with dense/sparse sample)
> Make k-mean runs two/three times faster with dense/sparse sample
> ----------------------------------------------------------------
>
> Key: SPARK-4708
> URL: https://issues.apache.org/jira/browse/SPARK-4708
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: DB Tsai
>
> Note that the usage of `breezeSquaredDistance` in
> `org.apache.spark.mllib.util.MLUtils.fastSquaredDistance` is in the critical
> path, and breezeSquaredDistance is slow. We should replace it with our own
> implementation.
> Here is the benchmark against mnist8m dataset.
> Before
> DenseVector: 70.04secs
> SparseVector: 59.05secs
> With this PR
> DenseVector: 30.58secs
> SparseVector: 21.14secs
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