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From "Reza Zadeh (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-3434) Distributed block matrix
Date Fri, 17 Oct 2014 21:21:34 GMT

    [ https://issues.apache.org/jira/browse/SPARK-3434?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14175557#comment-14175557
] 

Reza Zadeh commented on SPARK-3434:
-----------------------------------

Thanks Shivaram! As discussed over the phone, we will use your design and build upon it, so
that you can focus on the linear algebraic operations such as TSQR.

> 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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