Welcome to the Rust implementation of Apache Arrow, the popular in-memory columnar format.
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) |
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) |
parquet |
Support for Parquet columnar file format | docs.rs | (README) |
parquet_derive |
A crate for deriving RecordWriter/RecordReader for arbitrary, simple structs | docs.rs | (README) |
The current development version the API documentation in this repo can be found here.
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.
This crate releases every month. We 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.
To keep our maintenance burden down, we do regularly scheduled releases (major
and minor) from the master
branch. How we handle PRs with breaking API changes
is described in the contributing guide.
Planned Release Schedule
Approximate Date | Version | Notes |
---|---|---|
Sep 2024 | 53.0.0 |
Major, potentially breaking API changes |
Oct 2024 | 53.1.0 |
Minor, NO breaking API changes |
Nov 2024 | 53.2.0 |
Minor, NO breaking API changes |
Dec 2024 | 54.0.0 |
Major, potentially breaking API changes |
The object_store
crate is released independently of the arrow
and
parquet
crates and follows Semantic Versioning. We aim to release new
versions approximately every 2 months.
There are several related crates in different repositories
Crate | Description | Documentation |
---|---|---|
datafusion |
In-memory query engine with SQL support | (README) |
ballista |
Distributed query execution | (README) |
object_store_opendal |
Use opendal as object_store backend |
(README) |
Collectively, these crates support a wider array of functionality for analytic computations in Rust.
For example, you can write SQL queries or a DataFrame
(using the
datafusion
crate) to read 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 join
s and window functions.
You can find more details about each crate in their respective READMEs.
The [email protected]
mailing list serves as the core communication channel for the Arrow community. Instructions for signing up and links to the archives can be found on 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
[email protected]
mailing list - the GitHub Discussions
- 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.