datafusion 45.0.0

DataFusion is an in-memory query engine that uses Apache Arrow as the memory model
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# Apache DataFusion

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[license-url]: https://github.com/apache/datafusion/blob/main/LICENSE.txt
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[Website](https://datafusion.apache.org/) |
[API Docs](https://docs.rs/datafusion/latest/datafusion/) |
[Chat](https://discord.com/channels/885562378132000778/885562378132000781)

<a href="https://datafusion.apache.org/">
  <img src="https://github.com/apache/datafusion/raw/HEAD/docs/source/_static/images/2x_bgwhite_original.png" width="512" alt="logo"/>
</a>

DataFusion is an extensible query engine written in [Rust] that
uses [Apache Arrow] as its in-memory format.

This crate provides libraries and binaries for developers building fast and
feature rich database and analytic systems, customized to particular workloads.
See [use cases] for examples. The following related subprojects target end users:

- [DataFusion Python](https://github.com/apache/datafusion-python/) offers a Python interface for SQL and DataFrame
  queries.
- [DataFusion Ray](https://github.com/apache/datafusion-ray/) provides a distributed version of DataFusion that scales
  out on Ray clusters.
- [DataFusion Comet](https://github.com/apache/datafusion-comet/) is an accelerator for Apache Spark based on
  DataFusion.

"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.

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.

[rust]: http://rustlang.org
[apache arrow]: https://arrow.apache.org
[use cases]: https://datafusion.apache.org/user-guide/introduction.html#use-cases
[python bindings]: https://github.com/apache/datafusion-python
[performance]: https://benchmark.clickhouse.com/
[architecture]: https://datafusion.apache.org/contributor-guide/architecture.html

Here are links to some important information

- [Project Site](https://datafusion.apache.org/)
- [Installation](https://datafusion.apache.org/user-guide/cli/installation.html)
- [Rust Getting Started](https://datafusion.apache.org/user-guide/example-usage.html)
- [Rust DataFrame API](https://datafusion.apache.org/user-guide/dataframe.html)
- [Rust API docs](https://docs.rs/datafusion/latest/datafusion)
- [Rust Examples](https://github.com/apache/datafusion/tree/main/datafusion-examples)
- [Python DataFrame API](https://arrow.apache.org/datafusion-python/)
- [Architecture](https://docs.rs/datafusion/latest/datafusion/index.html#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](https://datafusion.apache.org/user-guide/introduction.html#known-users) to see a list known users.

## Contributing to DataFusion

Please see the [contributor guide] and [communication] pages for more information.

[contributor guide]: https://datafusion.apache.org/contributor-guide
[communication]: https://datafusion.apache.org/contributor-guide/communication.html

## Crate features

This crate has several [features] which can be specified in your `Cargo.toml`.

[features]: https://doc.rust-lang.org/cargo/reference/features.html

Default features:

- `nested_expressions`: functions for working with nested type function such as `array_to_string`
- `compression`: reading files compressed with `xz2`, `bzip2`, `flate2`, and `zstd`
- `crypto_expressions`: cryptographic functions such as `md5` and `sha256`
- `datetime_expressions`: date and time functions such as `to_timestamp`
- `encoding_expressions`: `encode` and `decode` functions
- `parquet`: support for reading the [Apache Parquet] format
- `regex_expressions`: regular expression functions, such as `regexp_match`
- `unicode_expressions`: Include unicode aware functions such as `character_length`
- `unparser`: enables support to reverse LogicalPlans back into SQL
- `recursive_protection`: uses [recursive](https://docs.rs/recursive/latest/recursive/) for stack overflow protection.

Optional features:

- `avro`: support for reading the [Apache Avro] format
- `backtrace`: include backtrace information in error messages
- `pyarrow`: conversions between PyArrow and DataFusion types
- `serde`: enable arrow-schema's `serde` feature

[apache avro]: https://avro.apache.org/
[apache parquet]: https://parquet.apache.org/

## Rust Version Compatibility Policy

The Rust toolchain releases are tracked at [Rust Versions](https://releases.rs) and follow
[semantic versioning](https://semver.org/). A Rust toolchain release can be identified
by a version string like `1.80.0`, or more generally `major.minor.patch`.

DataFusion's supports the last 4 stable Rust minor versions released and any such versions released within the last 4 months.

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`.

Note: If a Rust hotfix is released for the current MSRV, the MSRV will be updated to the specific minor version that includes all applicable hotfixes preceding other policies.

DataFusion enforces MSRV policy using a [MSRV CI Check](https://github.com/search?q=repo%3Aapache%2Fdatafusion+rust-version+language%3ATOML+path%3A%2F%5ECargo.toml%2F&type=code)

## DataFusion API Evolution and Deprecation Guidelines

Public methods in Apache DataFusion evolve over time: while we try to maintain a
stable API, we also improve the API over time. As a result, we typically
deprecate methods before removing them, according to the [deprecation guidelines].

[deprecation guidelines]: https://datafusion.apache.org/library-user-guide/api-health.html

## Dependencies and a `Cargo.lock`

`datafusion` is intended for use as a library and thus purposely does not have a
`Cargo.lock` file checked in. You can read more about the distinction in the
[Cargo book].

CI tests always run against the latest compatible versions of all dependencies
(the equivalent of doing `cargo update`), as suggested in the [Cargo CI guide]
and we rely on Dependabot for other upgrades. This strategy has two problems
that occasionally arise:

1. CI failures when downstream libraries upgrade in some non compatible way
2. Local development builds that fail when DataFusion inadvertently relies on
   a feature in a newer version of a dependency than declared in `Cargo.toml`
   (e.g. a new method is added to a trait that we use).

However, we think the current strategy is the best tradeoff between maintenance
overhead and user experience and ensures DataFusion always works with the latest
compatible versions of all dependencies. If you encounter either of these
problems, please open an issue or PR.

[cargo book]: https://doc.rust-lang.org/cargo/guide/cargo-toml-vs-cargo-lock.html
[cargo ci guide]: https://doc.rust-lang.org/cargo/guide/continuous-integration.html#verifying-latest-dependencies