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apache / arrow-rs / refs/tags/24.0.0
commit6477db16ca051b656bc0fe1f11bca85a23dbcd14[log] [tgz]
authorIan Alexander Joiner <iajoiner809@gmail.com>Fri Sep 30 15:05:56 2022 -0400
committerGitHub <noreply@github.com>Fri Sep 30 15:05:56 2022 -0400
tree4b4b8ccd212d19a7b37bec6acaf374a6a9a81cf4
parente2bf158946e5d81912bc9166d87b86f0ad442afb [diff]
Prepare for `24.0.0` (#2808)

* Create changelog

* Update version

* Update instructions to reflect label_issues.py needs admin

* Update release instructions with notes about the github token

* Update changelog

* update log

Co-authored-by: Ian Joiner <ian.joiner@spaceandtime.io>
Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
18 files changed
tree: 4b4b8ccd212d19a7b37bec6acaf374a6a9a81cf4
  1. .github/
  2. arrow/
  3. arrow-array/
  4. arrow-buffer/
  5. arrow-data/
  6. arrow-flight/
  7. arrow-pyarrow-integration-testing/
  8. arrow-schema/
  9. conbench/
  10. dev/
  11. format/
  12. integration-testing/
  13. object_store/
  14. parquet/
  15. parquet_derive/
  16. parquet_derive_test/
  17. parquet-testing
  18. testing
  19. .asf.yaml
  20. .gitattributes
  21. .github_changelog_generator
  22. .gitignore
  23. .gitmodules
  24. .pre-commit-config.yaml
  25. Cargo.toml
  26. CHANGELOG-old.md
  27. CHANGELOG.md
  28. CODE_OF_CONDUCT.md
  29. CONTRIBUTING.md
  30. header
  31. LICENSE.txt
  32. NOTICE.txt
  33. pre-commit.sh
  34. README.md
  35. rustfmt.toml
README.md

Native Rust implementation of Apache Arrow and Parquet

Coverage Status

Welcome to the implementation of Arrow, the popular in-memory columnar format, in Rust.

This repo contains the following main components:

CrateDescriptionDocumentation
arrowCore functionality (memory layout, arrays, low level computations)(README)
parquetSupport for Parquet columnar file format(README)
arrow-flightSupport for Arrow-Flight IPC protocol(README)
object-storeSupport for object store interactions (aws, azure, gcp, local, in-memory)(README)

There are two related crates in a different repository

CrateDescriptionDocumentation
DataFusionIn-memory query engine with SQL support(README)
BallistaDistributed query execution(README)

Collectively, these crates support a vast array of functionality for analytic computations in Rust.

For example, you can write an SQL query or a DataFrame (using the datafusion crate), run it against a parquet file (using the parquet crate), evaluate it in-memory using Arrow's columnar format (using the arrow crate), and send to another process (using the arrow-flight crate).

Generally speaking, the arrow crate offers functionality for using Arrow arrays, and datafusion offers most operations typically found in SQL, including joins and window functions.

You can find more details about each crate in their respective READMEs.

Arrow Rust Community

The dev@arrow.apache.org mailing list serves as the core communication channel for the Arrow community. Instructions for signing up and links to the archives can be found at the Arrow Community page. All major announcements and communications happen there.

The Rust Arrow community also uses the official ASF Slack for informal discussions and coordination. This is a great place to meet other contributors and get guidance on where to contribute. Join us in the #arrow-rust channel and feel free to ask for an invite via:

  1. the dev@arrow.apache.org mailing list
  2. the GitHub Discussions
  3. the Discord channel

Unlike other parts of the Arrow ecosystem, the Rust implementation uses GitHub issues as the system of record for new features and bug fixes and this plays a critical role in the release process.

For design discussions we generally collaborate on Google documents and file a GitHub issue linking to the document.

There is more information in the contributing guide.