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Wordsmith project description (#12778)
* Update description * Fmt * Update README.md Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org> * refine --------- Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
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README.md

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DataFusion is an extensible query engine written in [Rust] that
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uses [Apache Arrow] as its in-memory format.
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The DataFusion libraries in this repository are used to build data-centric system software. DataFusion also provides the
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following subprojects, which are packaged versions of DataFusion intended for end users.
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This crate provides libraries and binaries for developers building fast and
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feature rich database and analytic systems, customized to particular workloads.
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See [use cases] for examples. The following related subprojects target end users:
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- [DataFusion Python](https://github.com/apache/datafusion-python/) offers a Python interface for SQL and DataFrame
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queries.
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- [DataFusion Comet](https://github.com/apache/datafusion-comet/) is an accelerator for Apache Spark based on
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DataFusion.
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The target audience for the DataFusion crates in this repository are
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developers building fast and feature rich database and analytic systems,
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customized to particular workloads. See [use cases] for examples.
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DataFusion offers [SQL] and [`Dataframe`] APIs,
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excellent [performance], built-in support for CSV, Parquet, JSON, and Avro,
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extensive customization, and a great community.
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"Out of the box,"
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DataFusion offers [SQL] and [`Dataframe`] APIs, excellent [performance],
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built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and
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a great community.
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DataFusion features a full query planner, a columnar, streaming, multi-threaded,
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vectorized execution engine, and partitioned data sources. You can

docs/source/index.rst

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DataFusion is an extensible query engine written in `Rust <http://rustlang.org>`_ that
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uses `Apache Arrow <https://arrow.apache.org>`_ as its in-memory format.
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This documentation is for the `core DataFusion project <https://github.com/apache/datafusion>`_, which contains
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libraries that are used to build data-centric system software. DataFusion also offers the following subprojects, which
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provide packaged versions of DataFusion intended for end users, and these have separate documentation.
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The documentation on this site is for the `core DataFusion project <https://github.com/apache/datafusion>`_, which contains
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libraries and binaries for developers building fast and feature rich database and analytic systems,
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customized to particular workloads. See `use cases <https://datafusion.apache.org/user-guide/introduction.html#use-cases>`_ for examples.
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The following related subprojects target end users and have separate documentation.
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- `DataFusion Python <https://datafusion.apache.org/python/>`_ offers a Python interface for SQL and DataFrame
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queries.
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- `DataFusion Comet <https://datafusion.apache.org/comet/>`_ is an accelerator for Apache Spark based on
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DataFusion.
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DataFusion's target users are
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developers building fast and feature rich database and analytic systems,
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customized to particular workloads. See `use cases <https://datafusion.apache.org/user-guide/introduction.html#use-cases>`_ for examples.
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"Out of the box," DataFusion offers `SQL <https://datafusion.apache.org/user-guide/sql/index.html>`_
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and `Dataframe <https://docs.rs/datafusion/latest/datafusion/dataframe/struct.DataFrame.html>`_ APIs,
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excellent `performance <https://benchmark.clickhouse.com/>`_, built-in support for CSV, Parquet, JSON, and Avro,

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