GROUP BY ROLLUP
适用于 ✅ 开源版 ✅ 专业版 ✅ 企业版
在报告中，一次运行多个跨多个数据维度的聚合可能很有用。ROLLUP 是一种实现此目的的方法。
SELECT AUTHOR_ID, PUBLISHED_IN, COUNT(*) FROM BOOK GROUP BY ROLLUP (AUTHOR_ID, PUBLISHED_IN)
create.select(BOOK.AUTHOR_ID, BOOK.PUBLISHED_IN, count())
.from(BOOK)
.groupBy(rollup(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, PUBLISHED_IN, COUNT(*) FROM BOOK GROUP BY AUTHOR_ID, PUBLISHED_IN UNION ALL SELECT AUTHOR_ID, NULL, COUNT(*) FROM BOOK GROUP BY AUTHOR_ID UNION ALL SELECT NULL, NULL, COUNT(*) FROM BOOK GROUP BY ()
ROLLUP 函数只是更复杂的 GROUPING SETS 规范的语法糖。一般来说
-- This ROLLUP (A, B, C) -- Is just short for this GROUPING SETS ((A, B, C), (A, B), (A), ())
一个示例结果集可能如下所示
+-----------+--------------+----------+ | AUTHOR_ID | PUBLISHED_IN | COUNT(*) | +-----------+--------------+----------+ | 1 | 1945 | 1 | <- GROUP BY (AUTHOR_ID, PUBLISHED_IN) | 1 | 1948 | 1 | <- GROUP BY (AUTHOR_ID, PUBLISHED_IN) | 1 | NULL | 2 | <- GROUP BY (AUTHOR_ID) | 2 | 1988 | 1 | <- GROUP BY (AUTHOR_ID, PUBLISHED_IN) | 2 | 1990 | 1 | <- GROUP BY (AUTHOR_ID, PUBLISHED_IN) | 2 | NULL | 2 | <- GROUP BY (AUTHOR_ID) | NULL | NULL | 4 | <- GROUP BY () +-----------+--------------+----------+
方言支持
此示例使用 jOOQ
select(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count()).from(BOOK).groupBy(rollup(BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID))
翻译成以下特定方言的表达式
Aurora MySQL, MariaDB, MySQL
SELECT BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count(*) FROM BOOK GROUP BY BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID WITH ROLLUP
Aurora Postgres, ClickHouse, DB2, Databricks, DuckDB, Hana, MemSQL, Oracle, Postgres, Redshift, SQLDataWarehouse, SQLServer, Snowflake, Sybase, Teradata, Trino, Vertica
SELECT BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID, count(*) FROM BOOK GROUP BY ROLLUP (BOOK.AUTHOR_ID, BOOK.LANGUAGE_ID)
ASE, Access, BigQuery, CockroachDB, Derby, Exasol, Firebird, H2, HSQLDB, Informix, 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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