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Posted to issues@spark.apache.org by "Nick Pentreath (JIRA)" <ji...@apache.org> on 2017/02/24 08:02:44 UTC

[jira] [Commented] (SPARK-3434) Distributed block matrix

    [ https://issues.apache.org/jira/browse/SPARK-3434?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15882179#comment-15882179 ] 

Nick Pentreath commented on SPARK-3434:
---------------------------------------

This JIRA only has SPARK-3976 open. There was an old PR for it by [~brkyvz] here: https://github.com/apache/spark/pull/4286 (which was abandoned).

Unless SPARK-3976 is a priority and someone wants to revive it, shall we close this JIRA since the rest of the tickets are resolved?

> Distributed block matrix
> ------------------------
>
>                 Key: SPARK-3434
>                 URL: https://issues.apache.org/jira/browse/SPARK-3434
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Xiangrui Meng
>            Assignee: Shivaram Venkataraman
>
> This JIRA is for discussing distributed matrices stored in block sub-matrices. The main challenge is the partitioning scheme to allow adding linear algebra operations in the future, e.g.:
> 1. matrix multiplication
> 2. matrix factorization (QR, LU, ...)
> Let's discuss the partitioning and storage and how they fit into the above use cases.
> Questions:
> 1. Should it be backed by a single RDD that contains all of the sub-matrices or many RDDs with each contains only one sub-matrix?



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