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apache / arrow / refs/tags/apache-arrow-0.5.0
tag058712e65e3e7bc328b87dc81b5935046da559a4
taggerWes McKinney <wes.mckinney@twosigma.com>Thu Jul 20 13:02:51 2017 -0400
objecte9f76e125b836d0fdc0a533e2fee3fca8bf4c1a1 
[maven-release-plugin] copy for tag apache-arrow-0.5.0
commite9f76e125b836d0fdc0a533e2fee3fca8bf4c1a1[log] [tgz]
authorWes McKinney <wes.mckinney@twosigma.com>Thu Jul 20 13:02:41 2017 -0400
committerWes McKinney <wes.mckinney@twosigma.com>Thu Jul 20 13:02:41 2017 -0400
tree88abc95a8827aa2bd36467a07f67ae8cc449a815
parent62ef2cd8a39fc93e7fa4bb790d7cd92adb77571f [diff]
[maven-release-plugin] prepare release apache-arrow-0.5.0

Change-Id: Icb6a8ac2d92a38190fbc89d88a0a97120646f843
5 files changed
tree: 88abc95a8827aa2bd36467a07f67ae8cc449a815
  1. c_glib/
  2. ci/
  3. cpp/
  4. dev/
  5. format/
  6. integration/
  7. java/
  8. js/
  9. python/
  10. site/
  11. .gitignore
  12. .readthedocs.yml
  13. .travis.yml
  14. appveyor.yml
  15. CHANGELOG.md
  16. header
  17. LICENSE.txt
  18. NOTICE.txt
  19. README.md
README.md

Apache Arrow

Powering Columnar In-Memory Analytics

Arrow is a set of technologies that enable big-data systems to process and move data fast.

Initial implementations include:

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

What's in the Arrow libraries?

The reference Arrow implementations contain a number of 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
  • Low-overhead IO interfaces to files on disk, HDFS (C++ only)
  • 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 (e.g. Python's pandas library)

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:

How to Contribute

We prefer to receive contributions in the form of GitHub pull requests. Please send pull requests against the github.com/apache/arrow repository.

If you are looking for some ideas on what to contribute, check out the JIRA issues for the Apache Arrow project. Comment on the issue and/or contact dev@arrow.apache.org with your questions and ideas.

If you’d like to report a bug but don’t have time to fix it, you can still post it on JIRA, or email the mailing list dev@arrow.apache.org

To contribute a patch:

  1. Break your work into small, single-purpose patches if possible. It’s much harder to merge in a large change with a lot of disjoint features.
  2. Create a JIRA for your patch on the Arrow Project JIRA.
  3. Submit the patch as a GitHub pull request against the master branch. For a tutorial, see the GitHub guides on forking a repo and sending a pull request. Prefix your pull request name with the JIRA name (ex: https://github.com/apache/arrow/pull/240).
  4. Make sure that your code passes the unit tests. You can find instructions how to run the unit tests for each Arrow component in its respective README file.
  5. Add new unit tests for your code.

Thank you in advance for your contributions!