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apache / arrow-rs / refs/tags/19.0.0
commitc3e019f3011a902a344758969b1cfc3604f3c2d7[log] [tgz]
authorAndrew Lamb <andrew@nerdnetworks.org>Fri Jul 22 12:40:34 2022 -0400
committerGitHub <noreply@github.com>Fri Jul 22 12:40:34 2022 -0400
tree8002c8859925ead97ecdf2b214d07688c52c3730
parent567c45747c2fad12c6746ec8cc35ef44aa0f617f [diff]
Update version to `19.0.0` and add CHANGELOG (#2120)

* Update version to 19.0.0

* Prepare for new changelog

* Initial changelog

* update changelog

* updates

* final fixes
14 files changed
tree: 8002c8859925ead97ecdf2b214d07688c52c3730
  1. .github/
  2. arrow/
  3. arrow-flight/
  4. arrow-pyarrow-integration-testing/
  5. conbench/
  6. dev/
  7. format/
  8. integration-testing/
  9. parquet/
  10. parquet_derive/
  11. parquet_derive_test/
  12. parquet-testing
  13. testing
  14. .asf.yaml
  15. .gitattributes
  16. .github_changelog_generator
  17. .gitignore
  18. .gitmodules
  19. .pre-commit-config.yaml
  20. Cargo.toml
  21. CHANGELOG-old.md
  22. CHANGELOG.md
  23. CODE_OF_CONDUCT.md
  24. CONTRIBUTING.md
  25. header
  26. LICENSE.txt
  27. NOTICE.txt
  28. pre-commit.sh
  29. README.md
  30. 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)

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.

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.