2 stable releases
42.0.0 | Sep 17, 2024 |
---|---|
41.0.0 | Aug 11, 2024 |
#6 in #query-engine
259,202 downloads per month
Used in 51 crates
(via datafusion)
3.5MB
69K
SLoC
Apache DataFusion
DataFusion is an extensible query engine written in Rust that uses Apache Arrow as its in-memory format. DataFusion's target users are developers building fast and feature rich database and analytic systems, customized to particular workloads. See use cases for examples.
"Out of the box," DataFusion offers [SQL] and Dataframe
APIs,
excellent performance, built-in support for CSV, Parquet, JSON, and Avro,
extensive customization, and a great community.
Python Bindings are also available.
DataFusion features a full query planner, a columnar, streaming, multi-threaded, vectorized execution engine, and partitioned data sources. You can customize DataFusion at almost all points including additional data sources, query languages, functions, custom operators and more. See the Architecture section for more details.
Here are links to some important information
- Project Site
- Installation
- Rust Getting Started
- Rust DataFrame API
- Rust API docs
- Rust Examples
- Python DataFrame API
- Architecture
What can you do with this crate?
DataFusion is great for building projects such as domain specific query engines, new database platforms and data pipelines, query languages and more. It lets you start quickly from a fully working engine, and then customize those features specific to your use. Click Here to see a list known users.
Contributing to DataFusion
Please see the contributor guide and communication pages for more information.
Crate features
This crate has several features which can be specified in your Cargo.toml
.
Default features:
nested_expressions
: functions for working with nested type function such asarray_to_string
compression
: reading files compressed withxz2
,bzip2
,flate2
, andzstd
crypto_expressions
: cryptographic functions such asmd5
andsha256
datetime_expressions
: date and time functions such asto_timestamp
encoding_expressions
:encode
anddecode
functionsparquet
: support for reading the Apache Parquet formatregex_expressions
: regular expression functions, such asregexp_match
unicode_expressions
: Include unicode aware functions such ascharacter_length
unparser
: enables support to reverse LogicalPlans back into SQL
Optional features:
avro
: support for reading the Apache Avro formatbacktrace
: include backtrace information in error messagespyarrow
: conversions between PyArrow and DataFusion typesserde
: enable arrow-schema'sserde
feature
Rust Version Compatibility Policy
DataFusion's Minimum Required Stable Rust Version (MSRV) policy is to support stable 4 latest Rust versions OR the stable minor Rust version as of 4 months, whichever is lower.
For example, given the releases 1.78.0
, 1.79.0
, 1.80.0
, 1.80.1
and 1.81.0
DataFusion will support 1.78.0, which is 3 minor versions prior to the most minor recent 1.81
.
If a hotfix is released for the minimum supported Rust version (MSRV), the MSRV will be the minor version with all hotfixes, even if it surpasses the four-month window.
We enforce this policy using a MSRV CI Check
Dependencies
~27–42MB
~688K SLoC