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apache / arrow / e22197f39e41446789dcc52e931995fe20a784a4
commite22197f39e41446789dcc52e931995fe20a784a4[log] [tgz]
authorSarah Gilmore <74676073+sgilmore10@users.noreply.github.com>Tue Apr 30 09:41:44 2024 -0400
committerGitHub <noreply@github.com>Tue Apr 30 09:41:44 2024 -0400
treefffe56058bef845540ff5e49b835a6fe5e2f83ee
parentb609de374c7c00e1537eb8092e1ff2db718d2b61 [diff]
GH-41400: [MATLAB] Bump `libmexclass` version to commit `ca3cea6` (#41436)



### Rationale for this change

@ kevingurney and I recently resolved multiple issues related to `mathworks/libmexclass` not supporting ARM-based macOS builds (i.e. builds on `macos-14`):

- mathworks/libmexclass#76
- mathworks/libmexclass#77

We should bump the version of mathworks/libmexclass used by the MATLAB interface to the latest available commit ([ca3cea6](https://github.com/mathworks/libmexclass/commit/ca3cea6bf1ba5e9d86210bd207d643493e8d45f6) as of now) in order to enable building the MATLAB interface to Arrow on `macos-14` (which is ARM-based).

### What changes are included in this PR?

- Bumped version of `mathworks/libmexclass` used by the MATLAB interface to [ca3cea6](https://github.com/mathworks/libmexclass/commit/ca3cea6bf1ba5e9d86210bd207d643493e8d45f6)

### Are these changes tested?

- Yes. The existing test points verify verify upgrading `mathworks/libmexclass` does not break the MATLAB interface.

### Are there any user-facing changes?

- No. 

### Future Directions

- #41435
- #41385

* GitHub Issue: #41400

Authored-by: Sarah Gilmore <sgilmore@mathworks.com>
Signed-off-by: Sarah Gilmore <sgilmore@mathworks.com>
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README.md

Apache Arrow

Fuzzing Status License Twitter Follow

Powering In-Memory Analytics

Apache Arrow is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast.

Major components of the project include:

Arrow is an Apache Software Foundation project. Learn more at arrow.apache.org.

What's in the Arrow libraries?

The reference Arrow libraries contain many distinct software components:

  • Columnar vector and table-like containers (similar to data frames) supporting flat or nested types
  • Fast, language agnostic metadata messaging layer (using Google's Flatbuffers library)
  • Reference-counted off-heap buffer memory management, for zero-copy memory sharing and handling memory-mapped files
  • IO interfaces to local and remote filesystems
  • Self-describing binary wire formats (streaming and batch/file-like) for remote procedure calls (RPC) and interprocess communication (IPC)
  • Integration tests for verifying binary compatibility between the implementations (e.g. sending data from Java to C++)
  • Conversions to and from other in-memory data structures
  • Readers and writers for various widely-used file formats (such as Parquet, CSV)

Implementation status

The official Arrow libraries in this repository are in different stages of implementing the Arrow format and related features. See our current feature matrix on git main.

How to Contribute

Please read our latest project contribution guide.

Getting involved

Even if you do not plan to contribute to Apache Arrow itself or Arrow integrations in other projects, we'd be happy to have you involved: