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docs: fix typos and improve wording in README (#20301)
## Which issue does this PR close? N/A <!-- We generally require a GitHub issue to be filed for all bug fixes and enhancements and this helps us generate change logs for our releases. You can link an issue to this PR using the GitHub syntax. For example `Closes #123` indicates that this PR will close issue #123. --> ## Rationale for this change This PR fixes minor typos and improves wording consistency in README.md to enhance clarity and maintain consistent formatting. <!-- Why are you proposing this change? If this is already explained clearly in the issue then this section is not needed. Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes. --> ## What changes are included in this PR? - Fix minor typos - Improve wording clarity - Ensure consistent capitalization in feature descriptions <!-- There is no need to duplicate the description in the issue here but it is sometimes worth providing a summary of the individual changes in this PR. --> ## Are these changes tested? Not needed. These are documentation changes only. <!-- We typically require tests for all PRs in order to: 1. Prevent the code from being accidentally broken by subsequent changes 2. Serve as another way to document the expected behavior of the code If tests are not included in your PR, please explain why (for example, are they covered by existing tests)? --> ## Are there any user-facing changes? No. This only updates the README. <!-- If there are user-facing changes then we may require documentation to be updated before approving the PR. --> <!-- If there are any breaking changes to public APIs, please add the `api change` label. -->
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README.md

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@@ -58,7 +58,7 @@ 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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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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feature-rich database and analytic systems, customized for 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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DataFusion.
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"Out of the box,"
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DataFusion offers [SQL](https://datafusion.apache.org/user-guide/sql/index.html) and [Dataframe](https://datafusion.apache.org/user-guide/dataframe.html) APIs, excellent [performance],
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DataFusion offers [SQL](https://datafusion.apache.org/user-guide/sql/index.html) and [DataFrame](https://datafusion.apache.org/user-guide/dataframe.html) 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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[performance]: https://benchmark.clickhouse.com/
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[architecture]: https://datafusion.apache.org/contributor-guide/architecture.html
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Here are links to some important information
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Here are links to important resources:
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- [Project Site](https://datafusion.apache.org/)
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- [Installation](https://datafusion.apache.org/user-guide/cli/installation.html)
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## What can you do with this crate?
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DataFusion is great for building projects such as domain specific query engines, new database platforms and data pipelines, query languages and more.
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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.
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DataFusion is great for building projects such as domain-specific query engines, new database platforms and data pipelines, query languages and more.
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It lets you start quickly from a fully working engine, and then customize those features specific to your needs. See the [list of known users](https://datafusion.apache.org/user-guide/introduction.html#known-users).
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## Contributing to DataFusion
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Default features:
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- `nested_expressions`: functions for working with nested type function such as `array_to_string`
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- `nested_expressions`: functions for working with nested types such as `array_to_string`
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- `compression`: reading files compressed with `xz2`, `bzip2`, `flate2`, and `zstd`
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- `crypto_expressions`: cryptographic functions such as `md5` and `sha256`
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- `datetime_expressions`: date and time functions such as `to_timestamp`
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- `encoding_expressions`: `encode` and `decode` functions
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- `parquet`: support for reading the [Apache Parquet] format
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- `sql`: Support for sql parsing / planning
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- `sql`: support for SQL parsing and planning
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- `regex_expressions`: regular expression functions, such as `regexp_match`
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- `unicode_expressions`: Include unicode aware functions such as `character_length`
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- `unicode_expressions`: include Unicode-aware functions such as `character_length`
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- `unparser`: enables support to reverse LogicalPlans back into SQL
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- `recursive_protection`: uses [recursive](https://docs.rs/recursive/latest/recursive/) for stack overflow protection.
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