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SELECT DISTINCT ON

Applies to ✅ Open Source Edition   ✅ Express Edition   ✅ Professional Edition   ✅ Enterprise Edition

A useful, though perhaps a bit esoteric PostgreSQL specific extension to SELECT DISTINCT is the ON clause. Using this clause, PostgreSQL users can specify a distinctness criteria, but then produce other columns per distinct group from one of the group's tuples. This is normally not possible in SQL, but with ON, the first tuple in the group according to the ORDER BY clause can be accessed nonetheless. An example:

SELECT DISTINCT ON (BOOK.LANGUAGE_ID)
  BOOK.LANGUAGE_ID, BOOK.TITLE
FROM BOOK
ORDER BY BOOK.LANGUAGE_ID, BOOK.TITLE
Select<?> select1 = create.select(BOOK.LANGUAGE_ID, BOOK.TITLE)
      .distinctOn(BOOK.LANGUAGE_ID)
      .from(BOOK)
      .orderBy(BOOK.LANGUAGE_ID, BOOK.TITLE).fetch();

For syntactic reasons, the order of keywords had to be inversed as the PostgreSQL syntax cannot be easily reproduced in jOOQ's internal DSL. Quite likely, you might find jOOQ's syntax a bit more intuitive, though, as it more clearly separates the SELECT parts and the DISTINCT ON parts. Arguably, the DISTINCT ON clause should be positioned after ORDER BY, where it logically belongs.

Dialect support

This example using jOOQ:

select(BOOK.LANGUAGE_ID, BOOK.TITLE).distinctOn(BOOK.LANGUAGE_ID).from(BOOK).orderBy(BOOK.LANGUAGE_ID, BOOK.TITLE)

Translates to the following dialect specific expressions:

Aurora Postgres, ClickHouse, CockroachDB, DuckDB, H2, Postgres, YugabyteDB

SELECT DISTINCT ON (BOOK.LANGUAGE_ID) BOOK.LANGUAGE_ID, BOOK.TITLE
FROM BOOK
ORDER BY BOOK.LANGUAGE_ID, BOOK.TITLE

DB2, Exasol, Firebird, Hana, Informix, MariaDB, MemSQL, MySQL, Oracle, Redshift, SQLDataWarehouse, SQLServer, SQLite, Snowflake, Sybase, Teradata, Trino, Vertica

SELECT t.LANGUAGE_ID, t.TITLE
FROM (
  SELECT
    BOOK.LANGUAGE_ID,
    BOOK.TITLE,
    row_number() OVER (
      PARTITION BY BOOK.LANGUAGE_ID
      ORDER BY BOOK.LANGUAGE_ID, BOOK.TITLE
    ) rn
  FROM BOOK
) t
WHERE rn = 1
ORDER BY LANGUAGE_ID, TITLE

ASE, Access, Aurora MySQL, BigQuery, Derby, HSQLDB

/* UNSUPPORTED */
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