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在 PostgreSQL 中,GROUP BY 语句和 SELECT 语句一起使用,用来对相同的数据进行分组。
GROUP BY 在一个 SELECT 语句中,放在 WHRER 子句的后面,ORDER BY 子句的前面。
下面给出了 GROUP BY 子句的基本语法:
SELECT column-list FROM table_name WHERE [ conditions ] GROUP BY column1, column2....columnN ORDER BY column1, column2....columnN
GROUP BY 子句必须放在 WHERE 子句中的条件之后,必须放在 ORDER BY 子句之前。
在 GROUP BY 子句中,你可以对一列或者多列进行分组,但是被分组的列必须存在于列清单中。
创建 COMPANY 表(下载 COMPANY SQL 文件 ),数据内容如下:
nhooodb# 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)
下面示例将根据 NAME 字段值进行分组,找出每个人的工资总额:
nhooodb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME;
得到以下结果:
name | sum -------+------- Teddy | 20000 Paul | 20000 Mark | 65000 David | 85000 Allen | 15000 Kim | 45000 James | 10000 (7 rows)
现在我们添加使用下面语句在 CAMPANY 表中添加三条记录:
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 COMPANY 表中存在重复的名称,数据如下:
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)
现在再根据 NAME 字段值进行分组,找出每个客户的工资总额:
nhooodb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME;
这时的得到的结果如下:
name | sum -------+------- Allen | 15000 David | 85000 James | 20000 Kim | 45000 Mark | 65000 Paul | 40000 Teddy | 20000 (7 rows)
下面示例将 ORDER BY 子句与 GROUP BY 子句一起使用:
nhooodb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME DESC;
得到以下结果:
name | sum -------+------- Teddy | 20000 Paul | 40000 Mark | 65000 Kim | 45000 James | 20000 David | 85000 Allen | 15000 (7 rows)