base on Apache DataFusion SQL Query Engine <!--- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> # Apache DataFusion [![Crates.io][crates-badge]][crates-url] [![Apache licensed][license-badge]][license-url] [![Build Status][actions-badge]][actions-url] [![Discord chat][discord-badge]][discord-url] [crates-badge]: https://img.shields.io/crates/v/datafusion.svg [crates-url]: https://crates.io/crates/datafusion [license-badge]: https://img.shields.io/badge/license-Apache%20v2-blue.svg [license-url]: https://github.com/apache/datafusion/blob/main/LICENSE.txt [actions-badge]: https://github.com/apache/datafusion/actions/workflows/rust.yml/badge.svg [actions-url]: https://github.com/apache/datafusion/actions?query=branch%3Amain [discord-badge]: https://img.shields.io/discord/885562378132000778.svg?logo=discord&style=flat-square [discord-url]: https://discord.com/invite/Qw5gKqHxUM [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 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 ", Assign "at most 3 tags" to the expected json: {"id":"577","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"