PostgreSQL GROUP BY 子句与SELECT语句协作使用,将表中具有相同数据的行组合在一起.这样做是为了消除输出中的冗余和/或计算适用于这些组的聚合.
GROUP BY子句跟随SELECT语句中的WHERE子句并位于ORDER BY子句之前.
下面给出GROUP BY子句的基本语法. GROUP BY子句必须遵循WHERE子句中的条件,并且必须在ORDER BY子句之前(如果使用).
SELECT column-list FROM table_name WHERE [conditions] GROUP BY column1,column2 .... columnN ORDER BY column1,column2 .... columnN
您可以在GROUP BY子句中使用多个列.确保您用于分组的列,该列应该在列列表中可用.
考虑表 COMPANY ,记录如下 :
# select * from COMPANY; id | name | age | address | salary ----+-------+-----+-----------+-------- 1 | Paul | 32 | California| 20000 2 | Allen | 25 | Texas | 15000 3 | Teddy | 23 | Norway | 20000 4 | Mark | 25 | Rich-Mond | 65000 5 | David | 27 | Texas | 85000 6 | Kim | 22 | South-Hall| 45000 7 | James | 24 | Houston | 10000 (7 rows)
如果您想知道每个客户的工资总额,那么GROUP BY查询将如下所示;
testdb =#SELECT NAME,SUM(SALARY)FROM COMPANY GROUP BY NAME;
这会产生以下结果 :
name | sum -------+------- Teddy | 20000 Paul | 20000 Mark | 65000 David | 85000 Allen | 15000 Kim | 45000 James | 10000 (7 rows)
现在,让我们在COMPANY表中使用以下INSERT语句创建另外三条记录 :
INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00); INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00); INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);
现在,我们的表格中包含以下重复名称的记录;
id | name | age | address | salary ----+-------+-----+--------------+-------- 1 | Paul | 32 | California | 20000 2 | Allen | 25 | Texas | 15000 3 | Teddy | 23 | Norway | 20000 4 | Mark | 25 | Rich-Mond | 65000 5 | David | 27 | Texas | 85000 6 | Kim | 22 | South-Hall | 45000 7 | James | 24 | Houston | 10000 8 | Paul | 24 | Houston | 20000 9 | James | 44 | Norway | 5000 10 | James | 45 | Texas | 5000 (10 rows)
再次,让我们使用相同的语句对所有使用NAME列的记录进行分组,如下所示;
testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME;
这会产生以下结果 :
name | sum -------+------- Allen | 15000 David | 85000 James | 20000 Kim | 45000 Mark | 65000 Paul | 40000 Teddy | 20000 (7 rows)
让我们使用ORDER BY子句和GROUP BY子句,如下所示 :
testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME DESC;
这会产生以下结果 :
name | sum -------+------- Teddy | 20000 Paul | 40000 Mark | 65000 Kim | 45000 James | 20000 David | 85000 Allen | 15000 (7 rows)