[jira] [Resolved] (ARROW-854) [Format] Support sparse tensor

["Wes McKinney (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-854?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wes McKinney resolved ARROW-854.
--------------------------------
    Resolution: Fixed

Issue resolved by pull request 2546
[https://github.com/apache/arrow/pull/2546]

> [Format] Support sparse tensor
> ------------------------------
>
>                 Key: ARROW-854
>                 URL: https://issues.apache.org/jira/browse/ARROW-854
>             Project: Apache Arrow
>          Issue Type: New Feature
>          Components: Format
>            Reporter: Kouhei Sutou
>            Assignee: Kenta Murata
>            Priority: Minor
>              Labels: pull-request-available
>             Fix For: 0.12.0
>
>          Time Spent: 9h 40m
>  Remaining Estimate: 0h
>
> From http://mail-archives.apache.org/mod_mbox/arrow-dev/201704.mbox/%3CCAJPUwMBV5pkiXqY1-hsfP%3D2qgjQg-hMKZMwmQa3jKdDfxSS26A%40mail.gmail.com%3E
> bq. since we have metadata for tensors/ndarrays and support in C++, having analogous metadata for sparse matrices seems reasonable. Someone else asked me about this in person recently (related to machine learning applications).
> bq. While many Arrow implementations will be focused on the in-memory columnar / record batch data model, having these traditional scientific computing memory layouts available for shared memory IPC will open up the Arrow C/C++ libraries to more use cases. We wouldn't necessarily expect other Arrow implementations (like Java) to implement these, though, unless they needed them.



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