
A huge thank you to our sponsor, Starlake.ai who simplifies data ingestion, transformation, and orchestration, enabling faster delivery of high-quality data. Starlake has been instrumental in providing Piped SQL and numerous test cases for BigQuery, Redshift, DataBricks, and DuckDB. Show your support for ongoing development by visiting Starlake.ai and giving us a star!
Summary
Please visit our WebSite for detailed information. JSqlParser is a RDBMS agnostic SQL statement parser. It translates SQL statements into a traversable hierarchy of Java classes (see Samples):
SELECT 1 FROM dual WHERE a = b
String sqlStr = "select 1 from dual where a=b";
PlainSelect select = (PlainSelect) CCJSqlParserUtil.parse(sqlStr);
SelectItem selectItem =
select.getSelectItems().get(0);
Assertions.assertEquals(
new LongValue(1)
, selectItem.getExpression());
Table table = (Table) select.getFromItem();
Assertions.assertEquals("dual", table.getName());
EqualsTo equalsTo = (EqualsTo) select.getWhere();
Column a = (Column) equalsTo.getLeftExpression();
Column b = (Column) equalsTo.getRightExpression();
Assertions.assertEquals("a", a.getColumnName());
Assertions.assertEquals("b", b.getColumnName());
Support for Piped SQL
Work is progressing for parsing Piped SQL
, a much saner and more logical way to write queries in its semantic order.
FROM Produce
|> WHERE
item != 'bananas'
AND category IN ('fruit', 'nut')
|> AGGREGATE COUNT(*) AS num_items, SUM(sales) AS total_sales
GROUP BY item
|> ORDER BY item DESC;
For details, please see https://storage.googleapis.com/gweb-research2023-media/pubtools/1004848.pdf, https://cloud.google.com/bigquery/docs/reference/standard-sql/pipe-syntax and https://duckdb.org/docs/sql/query_syntax/from.html#from-first-syntax
Java Version
JSQLParser-4.9 was the last JDK8 compatible version. JSQLParser-5.0 and later depend on JDK11 and introduce API breaking changes to the AST Visitors. Please see the Migration Guide for the details.
Building JSQLParser-5.1 and newer with Gradle will depend on a JDK17 toolchain due to the used plugins.
Performance
Unfortunately the released JSQLParser-5.2 shows a performance deterioration caused by commit 30cf5d7 related to FunctionAllColumns()
.
This has been resolved in JSQLParser 5.3-SNAPSHOT and JMH benchmarks have been added to avoid such regressions in the future. Further all LOOKAHEADS
have been revised one by one, and we have gained back a very good performance of the Parser.
Benchmark (version) Mode Cnt Score Error Units
JSQLParserBenchmark.parseSQLStatements latest avgt 30 78.287 ± 4.730 ms/op <-- `FunctionAllColumns()` disabled
JSQLParserBenchmark.parseSQLStatements 5.2 avgt 30 400.876 ± 8.291 ms/op
JSQLParserBenchmark.parseSQLStatements 5.1 avgt 30 85.731 ± 1.288 ms/op
JSqlParser aims to support the SQL standard as well as all major RDBMS. Any missing syntax or features can be added on demand.
Oracle MS SQL Server and Sybase Postgres MySQL and MariaDB DB2 H2 and HSQLDB and Derby SQLite | SELECT
INSERT , UPDATE , UPSERT , MERGE
DELETE , TRUNCATE TABLE
CREATE ... , ALTER .... , DROP ...
WITH ... |
Salesforce SOQL | INCLUDES , EXCLUDES |
Piped SQL (also known as FROM SQL) | |
JSqlParser can also be used to create SQL Statements from Java Code with a fluent API (see Samples).
Sister Projects
If you like JSqlParser then please check out its related projects:
Alternatives to JSqlParser?
General SQL Parser looks pretty good, with extended SQL syntax (like PL/SQL and T-SQL) and java + .NET APIs. The tool is commercial (license available online), with a free download option.
Alternatively the dual-licensed JOOQ provides a handwritten Parser supporting a lot of RDBMS, translation between dialects, SQL transformation, can be used as a JDBC proxy for translation and transformation purposes.
License
JSqlParser is dual licensed under LGPL V2.1 or Apache Software License, Version 2.0.