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* feat: optimize the strategy of finding the right range * test: apply commentOtherLine util to all suggestion tests * test: decomment suggestion test cases * test: add suggestion test cases in multiple statements * chore: improve comments * test: update log info in test |
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dt-sql-parser
English | 简体中文
dt-sql-parser is a SQL Parser project built with ANTLR4, and it's mainly for the BigData field. The ANTLR4 generated the basic Parser, Visitor, and Listener, so it's easy to complete the syntax validation, tokenizer, traverse the AST, and so on features.
Additionally, it provides auxiliary functions such as SQL splitting and code completion.
Supported SQL:
- MySQL
- Flink SQL
- Spark SQL
- Hive SQL
- PostgreSQL
- Trino SQL
- Impala SQL
Supported auxiliary methods
SQL Type | SQL Spliting | Code Completion |
---|---|---|
MySQL | ✅ | ✅ |
Flink SQL | ✅ | ✅ |
Spark SQL | ✅ | ✅ |
Hive SQL | ✅ | ✅ |
PostgreSQL | ✅ | ✅ |
Trino SQL | ✅ | ✅ |
Impala SQL | ✅ | ✅ |
Tips: This project is the default for Javascript language, also you can try to compile it to other languages if you need.
Integrating SQL Parser with Monaco Editor
We have provided monaco-sql-languages, it is easily to integrate with monaco-editor
.
Tips: If you want to run
dt-sql-parser
in browser, don't forget to install theassert
andutil
polyfills, and define the global variableprocess.env
. None of this is needed in the node environment, because node has them built-in.
Installation
# use npm
npm i dt-sql-parser --save
# use yarn
yarn add dt-sql-parser
Usage
We recommend learning the Fundamentals usage before continuing. The dt-sql-parser library provides SQL Parser classes for different types of SQL.
import { MySQL, FlinkSQL, SparkSQL, HiveSQL, PostgresSQL, TrinoSQL, ImpalaSQL } from 'dt-sql-parser';
Before using syntax validation, code completion, and other features, it is necessary to instantiate the Parser of the relevant SQL type.
For instance, one can consider using MySQL
as an example:
const parser = new MySQL();
The following usage examples will utilize the MySQL
, and the Parser for other SQL types will be used in a similar manner as MySQL
.
Syntax Validation
import { MySQL } from 'dt-sql-parser';
const parser = new MySQL();
const correctSql = 'select id,name from user1;';
const errors = parser.validate(correctSql);
console.log(errors);
output:
/*
[]
*/
Validate failed:
const incorrectSql = 'selec id,name from user1;'
const errors = parser.validate(incorrectSql);
console.log(errors);
output:
/*
[
{
endCol: 5,
endLine: 1,
startCol: 0,
startLine: 1,
message: "mismatched input 'SELEC' expecting {<EOF>, 'ALTER', 'ANALYZE', 'CALL', 'CHANGE', 'CHECK', 'CREATE', 'DELETE', 'DESC', 'DESCRIBE', 'DROP', 'EXPLAIN', 'GET', 'GRANT', 'INSERT', 'KILL', 'LOAD', 'LOCK', 'OPTIMIZE', 'PURGE', 'RELEASE', 'RENAME', 'REPLACE', 'RESIGNAL', 'REVOKE', 'SELECT', 'SET', 'SHOW', 'SIGNAL', 'UNLOCK', 'UPDATE', 'USE', 'BEGIN', 'BINLOG', 'CACHE', 'CHECKSUM', 'COMMIT', 'DEALLOCATE', 'DO', 'FLUSH', 'HANDLER', 'HELP', 'INSTALL', 'PREPARE', 'REPAIR', 'RESET', 'ROLLBACK', 'SAVEPOINT', 'START', 'STOP', 'TRUNCATE', 'UNINSTALL', 'XA', 'EXECUTE', 'SHUTDOWN', '--', '(', ';'}"
}
]
*/
We instanced a Parser object, and use the validate method to check the SQL syntax, if failed returns an array object includes error message.
Tokenizer
Get all tokens by the Parser:
import { MySQL } from 'dt-sql-parser';
const parser = new MySQL()
const sql = 'select id,name,sex from user1;'
const tokens = parser.getAllTokens(sql)
console.log(tokens)
output:
/*
[
{
channel: 0
column: 0
line: 1
source: [SqlLexer, InputStream]
start: 0
stop: 5
tokenIndex: -1
type: 137
_text: null
},
...
]
*/
Visitor
Traverse the tree node by the Visitor:
import { MySQL, MySqlParserVisitor } from 'dt-sql-parser';
const parser = new MySQL()
const sql = `select id,name from user1;`
// parseTree
const tree = parser.parse(sql)
class MyVisitor extends MySqlParserVisitor {
// overwrite visitTableName
visitTableName(ctx) {
let tableName = ctx.getText().toLowerCase()
console.log('TableName', tableName)
}
// overwrite visitSelectElements
visitSelectElements(ctx) {
let selectElements = ctx.getText().toLowerCase()
console.log('SelectElements', selectElements)
}
}
const visitor = new MyVisitor()
visitor.visit(tree)
output:
/*
SelectElements id,name
TableName user1
*/
Tips: The node's method name can be found in the Visitor file under the corresponding SQL directory
Listener
Access the specified node in the AST by the Listener
import { MySQL, MySqlParserListener } from 'dt-sql-parser';
const parser = new MySQL();
const sql = 'select id,name from user1;'
// parseTree
const tree = parser.parse(sql)
class MyListener extends MySqlParserListener {
enterTableName(ctx) {
let tableName = ctx.getText().toLowerCase()
console.log('TableName', tableName)
}
enterSelectElements(ctx) {
let selectElements = ctx.getText().toLowerCase()
console.log('SelectElements', selectElements)
}
}
const listenTableName = new MyListener();
parser.listen(listenTableName, tree);
output:
/*
SelectElements id,name
TableName user1
*/
Tips: The node's method name can be found in the Listener file under the corresponding SQL directory
Splitting SQL statements
Take FlinkSQL
as an example:
import { FlinkSQL } from 'dt-sql-parser';
const parser = new FlinkSQL();
const sql = 'SHOW TABLES;\nSELECT * FROM tb;';
const sqlSlices = parser.splitSQLByStatement(sql);
console.log(sqlSlices)
output:
/*
[
{
startIndex: 0,
endIndex: 11,
startLine: 1,
endLine: 1,
startColumn: 1,
endColumn: 12,
text: 'SHOW TABLES;'
},
{
startIndex: 13,
endIndex: 29,
startLine: 2,
endLine: 2,
startColumn: 1,
endColumn: 17,
text: 'SELECT * FROM tb;'
}
]
*/
Code Completion
Obtaining code completion information at a specified position in SQL.
We can refer to the example of using FlinkSQL
.
Invoke the getSuggestionAtCaretPosition
method, pass the SQL content and the row and column numbers indicating the position where code completion is desired.
-
keyword candidates list
import { FlinkSQL } from 'dt-sql-parser'; const parser = new FlinkSQL(); const sql = 'CREATE '; const pos = { lineNumber: 1, column: 16 }; // the end position const keywords = parser.getSuggestionAtCaretPosition(sql, pos)?.keywords; console.log(keywords);
output:
/* [ 'CATALOG', 'FUNCTION', 'TEMPORARY', 'VIEW', 'DATABASE', 'TABLE' ] */
-
Obtaining information related to grammar completion
const parser = new FlinkSQL(); const sql = 'SELECT * FROM tb'; const pos = { lineNumber: 1, column: 16 }; // after 'tb' const syntaxSuggestions = parser.getSuggestionAtCaretPosition(sql, pos)?.syntax; console.log(syntaxSuggestions);
output:
/* [ { syntaxContextType: 'table', wordRanges: [ { text: 'tb', startIndex: 14, stopIndex: 15, line: 1, startColumn: 15, stopColumn: 16 } ] }, { syntaxContextType: 'view', wordRanges: [ { text: 'tb', startIndex: 14, stopIndex: 15, line: 1, startColumn: 15, stopColumn: 16 } ] } ] */
The grammar-related code completion information returns an array, where each item represents what grammar can be filled in at that position. For example, the output in the above example represents that the position can be filled with either a table name or a view name. In this case, syntaxContextType
represents the type of grammar that can be completed, and wordRanges
represents the content that has already been filled.
Other API
createLexer
Create an instance of Antlr4 Lexer and return it;createParser
Create an instance of Antlr4 parser and return it;parse
Parses the input SQL and returns the parse tree;