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apache / arrow-rs / refs/tags/object_store_0.5.2
commit74b174ca7a6c11d2b410334f45aa399987b35fc0[log] [tgz]
authorAndrew Lamb <andrew@nerdnetworks.org>Fri Dec 02 15:19:19 2022 -0500
committerGitHub <noreply@github.com>Fri Dec 02 15:19:19 2022 -0500
tree0e14dedd0c0d7b3ef42041b1ab614a749604bfbb
parentecbb8c23765ff6530ca32b5b3139713d6aaebfed [diff]
Update object_store version to 0.5.2 and add CHANGELOG (#3253)

* Update object_store crate version to 0.5.2

* Initial changelog

* Updates

* More update

* Update Changlog, semi manually

* final updates
4 files changed
tree: 0e14dedd0c0d7b3ef42041b1ab614a749604bfbb
  1. .github/
  2. arrow/
  3. arrow-array/
  4. arrow-buffer/
  5. arrow-cast/
  6. arrow-csv/
  7. arrow-data/
  8. arrow-flight/
  9. arrow-integration-test/
  10. arrow-integration-testing/
  11. arrow-ipc/
  12. arrow-json/
  13. arrow-pyarrow-integration-testing/
  14. arrow-schema/
  15. arrow-select/
  16. conbench/
  17. dev/
  18. format/
  19. object_store/
  20. parquet/
  21. parquet_derive/
  22. parquet_derive_test/
  23. parquet-testing
  24. testing
  25. .asf.yaml
  26. .gitattributes
  27. .github_changelog_generator
  28. .gitignore
  29. .gitmodules
  30. .pre-commit-config.yaml
  31. Cargo.toml
  32. CHANGELOG-old.md
  33. CHANGELOG.md
  34. CODE_OF_CONDUCT.md
  35. CONTRIBUTING.md
  36. header
  37. LICENSE.txt
  38. NOTICE.txt
  39. pre-commit.sh
  40. README.md
  41. 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.