Extensible SQL Lexer and Parser for Rust

This crate contains a lexer and parser for SQL that conforms with the ANSI/ISO SQL standard and other dialects. This crate is used as a foundation for SQL query engines, vendor-specific parsers, and various SQL analysis.

Example

To parse a simple SELECT statement:

use sqlparser::dialect::GenericDialect;
use sqlparser::parser::Parser;

let sql = "SELECT a, b, 123, myfunc(b) \
           FROM table_1 \
           WHERE a > b AND b < 100 \
           ORDER BY a DESC, b";

let dialect = GenericDialect {}; // or AnsiDialect, or your own dialect ...

let ast = Parser::parse_sql(&dialect, sql).unwrap();

println!("AST: {:?}", ast);

This outputs

AST: [Query(Query { ctes: [], body: Select(Select { distinct: false, projection: [UnnamedExpr(Identifier("a")), UnnamedExpr(Identifier("b")), UnnamedExpr(Value(Long(123))), UnnamedExpr(Function(Function { name:ObjectName([Identifier(Ident { value: "myfunc", quote_style: None })]), args: [Identifier("b")], filter: None, over: None, distinct: false }))], from: [TableWithJoins { relation: Table { name: ObjectName([Identifier(Ident { value: "table_1", quote_style: None })]), alias: None, args: [], with_hints: [] }, joins: [] }], selection: Some(BinaryOp { left: BinaryOp { left: Identifier("a"), op: Gt, right: Identifier("b") }, op: And, right: BinaryOp { left: Identifier("b"), op: Lt, right: Value(Long(100)) } }), group_by: [], having: None }), order_by: [OrderByExpr { expr: Identifier("a"), asc: Some(false) }, OrderByExpr { expr: Identifier("b"), asc: None }], limit: None, offset: None, fetch: None })]

Features

The following optional crate features are available:

serde: Adds Serde support by implementing Serialize and Deserialize for all AST nodes.
visitor: Adds a Visitor capable of recursively walking the AST tree.
recursive-protection (enabled by default), uses recursive for stack overflow protection.

Syntax vs Semantics

This crate provides only a syntax parser, and tries to avoid applying any SQL semantics, and accepts queries that specific databases would reject, even when using that Database's specific Dialect. For example, CREATE TABLE(x int, x int) is accepted by this crate, even though most SQL engines will reject this statement due to the repeated column name x.

This crate avoids semantic analysis because it varies drastically between dialects and implementations. If you want to do semantic analysis, feel free to use this project as a base.

Preserves Syntax Round Trip

This crate allows users to recover the original SQL text (with comments removed, normalized whitespace and keyword capitalization), which is useful for tools that analyze and manipulate SQL.

This means that other than comments, whitespace and the capitalization of keywords, the following should hold true for all SQL:

// Parse SQL
let ast = Parser::parse_sql(&GenericDialect, sql).unwrap();

// The original SQL text can be generated from the AST
assert_eq!(ast[0].to_string(), sql);

There are still some cases in this crate where different SQL with seemingly similar semantics are represented with the same AST. We welcome PRs to fix such issues and distinguish different syntaxes in the AST.

Source Locations (Work in Progress)

This crate allows recovering source locations from AST nodes via the Spanned trait, which can be used for advanced diagnostics tooling. Note that this feature is a work in progress and many nodes report missing or inaccurate spans. Please see this ticket for information on how to contribute missing improvements.

// Parse SQL
let ast = Parser::parse_sql(&GenericDialect, "SELECT A FROM B").unwrap();

// The source span can be retrieved with start and end locations
assert_eq!(ast[0].span(), Span {
  start: Location::of(1, 1),
  end: Location::of(1, 16),
});

SQL compliance

SQL was first standardized in 1987, and revisions of the standard have been published regularly since. Most revisions have added significant new features to the language, and as a result no database claims to support the full breadth of features. This parser currently supports most of the SQL-92 syntax, plus some syntax from newer versions that have been explicitly requested, plus various other dialect-specific syntax. Whenever possible, the online SQL:2016 grammar is used to guide what syntax to accept.

Unfortunately, stating anything more specific about compliance is difficult. There is no publicly available test suite that can assess compliance automatically, and doing so manually would strain the project's limited resources. Still, we are interested in eventually supporting the full SQL dialect, and we are slowly building out our own test suite.

If you are assessing whether this project will be suitable for your needs, you'll likely need to experimentally verify whether it supports the subset of SQL that you need. Please file issues about any unsupported queries that you discover. Doing so helps us prioritize support for the portions of the standard that are actually used. Note that if you urgently need support for a feature, you will likely need to write the implementation yourself. See the Contributing section for details.

Command line

This crate contains a CLI program that can parse a file and dump the results as JSON:

$ cargo run --features json_example --example cli FILENAME.sql [--dialectname]

Users

This parser is currently being used by the DataFusion query engine, LocustDB, Ballista, GlueSQL, Opteryx, Polars, PRQL, Qrlew, JumpWire, and ParadeDB.

If your project is using sqlparser-rs feel free to make a PR to add it to this list.

Design

The core expression parser uses the Pratt Parser design, which is a top-down operator-precedence (TDOP) parser, while the surrounding SQL statement parser is a traditional, hand-written recursive descent parser. Eli Bendersky has a good tutorial on TDOP parsers, if you are interested in learning more about the technique.

We are a fan of this design pattern over parser generators for the following reasons:

Code is simple to write and can be concise and elegant
Performance is generally better than code generated by parser generators
Debugging is much easier with hand-written code
It is far easier to extend and make dialect-specific extensions compared to using a parser generator

Supporting custom SQL dialects

This is a work in progress, but we have some notes on writing a custom SQL parser.

Contributing

Contributions are highly encouraged! However, the bandwidth we have to maintain this crate is limited. Please read the following sections carefully.

New Syntax

The most commonly accepted PRs add support for or fix a bug in a feature in the SQL standard, or a popular RDBMS, such as Microsoft SQL Server or PostgreSQL, will likely be accepted after a brief review. Any SQL feature that is dialect specific should be parsed by both the relevant Dialect as well as GenericDialect.

Major API Changes

The current maintainers do not plan for any substantial changes to this crate's API. PRs proposing major refactors are not likely to be accepted.

Testing

While we hope to review PRs in a reasonably timely fashion, it may take a week or more. In order to speed the process, please make sure the PR passes all CI checks, and includes tests demonstrating your code works as intended (and to avoid regressions). Remember to also test error paths.

PRs without tests will not be reviewed or merged. Since the CI ensures that cargo test, cargo fmt, and cargo clippy, pass you should likely to run all three commands locally before submitting your PR.

Filing Issues

If you are unable to submit a patch, feel free to file an issue instead. Please try to include:

some representative examples of the syntax you wish to support or fix;
the relevant bits of the SQL grammar, if the syntax is part of SQL:2016; and
links to documentation for the feature for a few of the most popular databases that support it.

Unfortunately, if you need support for a feature, you will likely need to implement it yourself, or file a well enough described ticket that another member of the community can do so. Our goal as maintainers is to facilitate the integration of various features from various contributors, but not to provide the implementations ourselves, as we simply don't have the resources.

Benchmarking

There are several micro benchmarks in the sqlparser_bench directory. You can run them with:

git checkout main
cd sqlparser_bench
cargo bench -- --save-baseline main
git checkout <your branch>
cargo bench -- --baseline main

By adding the --save-baseline main and --baseline main you can track the progress of your improvements as you continue working on the feature branch.

Licensing

All code in this repository is licensed under the Apache Software License 2.0.

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be licensed as above, without any additional terms or conditions.

License

coderdan/datafusion-sqlparser-rs

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