[jira] [Commented] (SPARK-4708) Make k-mean runs two/three times faster with dense/sparse sample

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-4708?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14232428#comment-14232428 ] 

Apache Spark commented on SPARK-4708:
-------------------------------------

User 'dbtsai' has created a pull request for this issue:
https://github.com/apache/spark/pull/3565

> 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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