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https://issues.apache.org/jira/browse/SPARK-1580?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14083305#comment-14083305
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Apache Spark commented on SPARK-1580:
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User 'mengxr' has created a pull request for this issue:
https://github.com/apache/spark/pull/1731
> [MLlib] ALS: Estimate communication and computation costs given a partitioner
> -----------------------------------------------------------------------------
>
> Key: SPARK-1580
> URL: https://issues.apache.org/jira/browse/SPARK-1580
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Tor Myklebust
> Priority: Minor
>
> It would be nice to be able to estimate the amount of work needed to solve an
> ALS problem. The chief components of this "work" are computation time---time
> spent forming and solving the least squares problems---and communication
> cost---the number of bytes sent across the network. Communication cost
> depends heavily on how the users and products are partitioned.
> We currently do not try to cluster users or products so that fewer feature
> vectors need to be communicated. This is intended as a first step toward
> that end---we ought to be able to tell whether one partitioning is better
> than another.
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