|49.0.0||Nov 13, 2023|
|48.0.1||Nov 13, 2023|
|48.0.0||Oct 23, 2023|
|47.0.0||Sep 22, 2023|
|27.0.0||Nov 14, 2022|
#90 in Parser implementations
138,166 downloads per month
Used in 8 crates (4 directly)
Native Rust implementation of Apache Arrow and Parquet
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.
There are two related crates in a different repository
|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
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
firstname.lastname@example.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:
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.
Transfer data between the Arrow memory format and CSV (comma-separated values).