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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-1580) [MLlib] ALS: Estimate communication and computation costs given a partitioner
Date Sat, 02 Aug 2014 04:25:40 GMT

     [ https://issues.apache.org/jira/browse/SPARK-1580?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiangrui Meng updated SPARK-1580:
---------------------------------

    Assignee: Tor Myklebust

> [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
>            Assignee: 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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