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Native Rust implementation of Apache Arrow and Parquet

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

This repo contains the following main components:

Crate Description Latest API Docs README
arrow Core functionality (memory layout, arrays, low level computations) docs.rs (README)
parquet Support for Parquet columnar file format docs.rs (README)
arrow-flight Support for Arrow-Flight IPC protocol docs.rs (README)
object-store Support for object store interactions (aws, azure, gcp, local, in-memory) docs.rs (README)

The current development version the API documentation in this repo can be found here.

Release Versioning and Schedule

The Arrow Rust project releases approximately monthly and follows Semantic Versioning.

Due to available maintainer and testing bandwidth, arrow crates (arrow, arrow-flight, etc.) are released on the same schedule with the same versions as the parquet and parquet-derive crates.

Starting June 2024, we plan to release new major versions with potentially breaking API changes at most once a quarter, and release incremental minor versions in the intervening months. See this ticket for more details.

For example:

Approximate Date Version Notes
Jun 2024 52.0.0 Major, potentially breaking API changes
Jul 2024 52.1.0 Minor, NO breaking API changes
Aug 2024 52.2.0 Minor, NO breaking API changes
Sep 2024 53.0.0 Major, potentially breaking API changes

Related Projects

There are two related crates in different repositories

Crate Description Documentation
DataFusion In-memory query engine with SQL support (README)
Ballista Distributed 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

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.

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