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GROUP BY GROUPING SETS
Applies to ✅ Open Source Edition ✅ Express Edition ✅ Professional Edition ✅ Enterprise Edition
In reports, it may be useful to run multiple aggregations across multiple dimensions of the data in one go. GROUPING SETS
is one way to do this.
SELECT AUTHOR_ID, PUBLISHED_IN, COUNT(*) FROM BOOK GROUP BY GROUPING SETS ((AUTHOR_ID), (PUBLISHED_IN))
create.select(BOOK.AUTHOR_ID, BOOK.PUBLISHED_IN, count()) .from(BOOK) .groupBy(groupingSets(BOOK.AUTHOR_ID, BOOK.PUBLISHED_IN)) .fetch();
The above is a more concise (and possibly more performant) form of writing the following UNION ALL query:
SELECT AUTHOR_ID, NULL AS PUBLISHED_IN, COUNT(*) FROM BOOK GROUP BY AUTHOR_ID UNION ALL SELECT NULL, PUBLISHED_IN, COUNT(*) FROM BOOK GROUP BY LANGUAGE_ID
An example result set might look like this:
+-----------+--------------+----------+ | AUTHOR_ID | PUBLISHED_IN | COUNT(*) | +-----------+--------------+----------+ | NULL | 1945 | 1 | <- GROUP BY (PUBLISHED_IN) | NULL | 1948 | 1 | <- GROUP BY (PUBLISHED_IN) | NULL | 1988 | 1 | <- GROUP BY (PUBLISHED_IN) | NULL | 1990 | 1 | <- GROUP BY (PUBLISHED_IN) | 1 | NULL | 2 | <- GROUP BY (AUTHOR_ID) | 2 | NULL | 2 | <- GROUP BY (AUTHOR_ID) +-----------+--------------+----------+
Note that the most common GROUPING SETS
specifications have a dedicated, special syntax:
Dialect support
This example using jOOQ:
select(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count()).from(BOOK).groupBy(groupingSets(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID))
Translates to the following dialect specific expressions:
Aurora Postgres, ClickHouse, DB2, DuckDB, Hana, Oracle, Postgres, SQLServer, Snowflake, Sybase, Teradata, Trino, Vertica
SELECT BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count(*) FROM BOOK GROUP BY GROUPING SETS ( (BOOK.AUTHOR_ID), (BOOK.LANGUAGE_ID) )
ASE, Access, Aurora MySQL, BigQuery, CockroachDB, Derby, Exasol, Firebird, H2, HSQLDB, Informix, MariaDB, MemSQL, MySQL, Redshift, SQLDataWarehouse, SQLite, YugabyteDB
/* UNSUPPORTED */
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