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apache / arrow / refs/tags/apache-arrow-0.8.0
tagf65ec93da51ce495a955a1471bf47bcc1099b5bd
taggerWes McKinney <wes.mckinney@twosigma.com>Tue Dec 12 17:22:39 2017 -0500
object1d689e5a3e417d3a4b3de16fea7a6fe195c8f8df 
[maven-release-plugin] copy for tag apache-arrow-0.8.0
commit1d689e5a3e417d3a4b3de16fea7a6fe195c8f8df[log] [tgz]
authorWes McKinney <wes.mckinney@twosigma.com>Tue Dec 12 17:22:29 2017 -0500
committerWes McKinney <wes.mckinney@twosigma.com>Tue Dec 12 17:22:29 2017 -0500
treedd716e87e462158bbd6ff605213e3b986fd86b9b
parent3afb8f4e2df14fb9a512d2a82b6aeff27d013df6 [diff]
[maven-release-plugin] prepare release apache-arrow-0.8.0

Change-Id: Ia6278e52e2669880cbe32d79bd2fcda48951d3fa
5 files changed
tree: dd716e87e462158bbd6ff605213e3b986fd86b9b
  1. .github/
  2. c_glib/
  3. ci/
  4. cpp/
  5. dev/
  6. format/
  7. integration/
  8. java/
  9. js/
  10. python/
  11. site/
  12. .gitignore
  13. .readthedocs.yml
  14. .travis.yml
  15. appveyor.yml
  16. CHANGELOG.md
  17. header
  18. LICENSE.txt
  19. NOTICE.txt
  20. 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!