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Posted to issues@spark.apache.org by "burness duan (JIRA)" <ji...@apache.org> on 2016/03/26 15:38:25 UTC
[jira] [Commented] (SPARK-3220) K-Means clusterer should perform
K-Means initialization in parallel
[ https://issues.apache.org/jira/browse/SPARK-3220?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15213059#comment-15213059 ]
burness duan commented on SPARK-3220:
-------------------------------------
I have use this Derrick's kmeans， It is efficient in our project for a 12 million points(300 dimensionality). I run the spark mllib kmeans in 6.9h （2000 clustering). While, It only took less than 2h when i use Derrick's one.
> K-Means clusterer should perform K-Means initialization in parallel
> -------------------------------------------------------------------
>
> Key: SPARK-3220
> URL: https://issues.apache.org/jira/browse/SPARK-3220
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Derrick Burns
> Labels: clustering
>
> The LocalKMeans method should be replaced with a parallel implementation. As it stands now, it becomes a bottleneck for large data sets.
> I have implemented this functionality in my version of the clusterer. However, I see that there are hundreds of outstanding pull requests. If someone on the team wants to sponsor the pull request, I will create one. Otherwise, I will just maintain my own private fork of the clusterer.
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