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INNER JOIN
Applies to ✅ Open Source Edition ✅ Express Edition ✅ Professional Edition ✅ Enterprise Edition
An INNER JOIN or just JOIN works like a CROSS JOIN, but adds a predicate of some sort filtering out unwanted combinations. This is the most popular way to join tables, as we hardly ever want to combine arbitrary rows from both tables, but the ones that have some relationship with each other, e.g. a FOREIGN KEY reference match.
SELECT * FROM AUTHOR JOIN BOOK ON BOOK.AUTHOR_ID = AUTHOR.ID
create.select()
.from(AUTHOR)
.join(BOOK).on(BOOK.AUTHOR_ID.eq(AUTHOR.ID))
.fetch();
The above query will return all authors and their books. True to the nature of an INNER JOIN, authors without books are excluded as well as books without authors (if the FOREIGN KEY is optional).
The result might look like this:
+------------+-----------+--------------+ | FIRST_NAME | LAST_NAME | TITLE | +------------+-----------+--------------+ | George | Orwell | 1984 | | George | Orwell | Animal Farm | | Paulo | Coelho | O Alquimista | | Paulo | Coelho | Brida | +------------+-----------+--------------+
In the example, we're using the ON clause to form the JOIN predicate, but other options will be discussed in later sections as well.
The INNER keyword is optional both in SQL and in jOOQ, and does not affect the query semantics at all.
Dialect support
This example using jOOQ:
select(BOOK.ID, AUTHOR.ID).from(BOOK.join(AUTHOR).on(BOOK.AUTHOR_ID.eq(AUTHOR.ID)))
Translates to the following dialect specific expressions:
Access
SELECT BOOK.ID, AUTHOR.ID
FROM BOOK
INNER JOIN AUTHOR
ON BOOK.AUTHOR_ID = AUTHOR.ID
ASE, Aurora MySQL, Aurora Postgres, BigQuery, ClickHouse, CockroachDB, DB2, Derby, DuckDB, Exasol, Firebird, H2, HSQLDB, Hana, Informix, MariaDB, MemSQL, MySQL, Oracle, Postgres, Redshift, SQLDataWarehouse, SQLServer, SQLite, Snowflake, Sybase, Teradata, Trino, Vertica, YugabyteDB
SELECT BOOK.ID, AUTHOR.ID
FROM BOOK
JOIN AUTHOR
ON BOOK.AUTHOR_ID = AUTHOR.ID
Generated with jOOQ 3.20. Translate your own SQL on our website
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