GROUP BY GROUPING SETS
适用于 ✅ 开源版 ✅ 专业版 ✅ 企业版
在报表中，一次性对数据的多个维度运行多个聚合可能很有用。 GROUPING SETS 是一种实现此目的的方法。
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();
以上是编写以下 UNION ALL 查询的一种更简洁（并且可能性能更高）的形式
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
一个示例结果集可能如下所示
+-----------+--------------+----------+ | 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) +-----------+--------------+----------+
select(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count()).from(BOOK).groupBy(groupingSets(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID))
翻译成以下特定方言的表达式
Aurora Postgres, ClickHouse, DB2, Databricks, DuckDB, Hana, Oracle, Postgres, Redshift, 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, SQLDataWarehouse, SQLite, YugabyteDB
/* UNSUPPORTED */
使用 jOOQ 3.21 生成。早期 jOOQ 版本的支持可能有所不同。 在我们的网站上翻译您自己的 SQL
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