# arrow-rs **Repository Path**: endpoint_rust/arrow-rs ## Basic Information - **Project Name**: arrow-rs - **Description**: No description available - **Primary Language**: Rust - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-09-09 - **Last Updated**: 2024-12-12 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Native Rust implementation of Apache Arrow and Parquet [![Coverage Status](https://codecov.io/gh/apache/arrow-rs/rust/branch/master/graph/badge.svg)](https://codecov.io/gh/apache/arrow-rs?branch=master) Welcome to the implementation of Arrow, the popular in-memory columnar format, in [Rust](https://www.rust-lang.org/). This repo contains the following main components: | Crate | Description | Documentation | | ------------ | ------------------------------------------------------------------ | ---------------------------------- | | arrow | Core functionality (memory layout, arrays, low level computations) | [(README)](arrow/README.md) | | parquet | Support for Parquet columnar file format | [(README)](parquet/README.md) | | arrow-flight | Support for Arrow-Flight IPC protocol | [(README)](arrow-flight/README.md) | There are two related crates in a different repository | Crate | Description | Documentation | | ------------ | ------------------------------------------------------------------ | ------------------------------------------------------------------------------------- | | DataFusion | In-memory query engine with SQL support | [(README)](https://github.com/apache/arrow-datafusion/blob/master/README.md) | | Ballista | Distributed query execution | [(README)](https://github.com/apache/arrow-datafusion/blob/master/ballista/README.md) | 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 `join`s 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](https://arrow.apache.org/community/) page. All major announcements and communications happen there. The Rust Arrow community also uses the official [ASF Slack](https://s.apache.org/slack-invite) 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](https://github.com/apache/arrow-rs/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.