PostgreSQL UNION子句/运算符用于组合两个或多个SELECT语句的结果,而不返回任何重复的行。
要使用UNION,每个SELECT必须具有相同的列数,相同数量的列表达式,相同的数据类型,并且具有相同的顺序,但不一定要相同。
语法:
UNION的基本语法如下:
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
UNION
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
这里根据您的要求给出的条件表达式。
示例:
考虑以下两个表,COMPANY
表如下:
yiibai_db=# 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)
另一张表是DEPARTMENT
如下:
yiibai_db=# SELECT * from DEPARTMENT;
id | dept | emp_id
----+-------------+--------
1 | IT Billing | 1
2 | Engineering | 2
3 | Finance | 7
4 | Engineering | 3
5 | Finance | 4
6 | Engineering | 5
7 | Finance | 6
(7 rows)
现在使用SELECT
语句和UNION
子句连接这两个表,如下所示:
yiibai_db=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID
UNION
SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;
这将产生以下结果:
emp_id | name | dept
--------+-------+--------------
5 | David | Engineering
6 | Kim | Finance
2 | Allen | Engineering
3 | Teddy | Engineering
4 | Mark | Finance
1 | Paul | IT Billing
7 | James | Finance
(7 rows)
UNION ALL子句
UNION ALL
运算符用于组合两个SELECT
语句(包括重复行)的结果。 适用于UNION的相同规则也适用于UNION ALL
运算符。
语法:
UNION ALL的基本语法如下:
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
UNION ALL
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
这里根据您的要求给出的条件表达式。
示例:
现在,我们在SELECT语句中加入上面提到的两个表,如下所示:
yiibai_db=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID
UNION ALL
SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT
ON COMPANY.ID = DEPARTMENT.EMP_ID;
这将产生以下结果:
emp_id | name | dept
--------+-------+--------------
1 | Paul | IT Billing
2 | Allen | Engineering
7 | James | Finance
3 | Teddy | Engineering
4 | Mark | Finance
5 | David | Engineering
6 | Kim | Finance
1 | Paul | IT Billing
2 | Allen | Engineering
7 | James | Finance
3 | Teddy | Engineering
4 | Mark | Finance
5 | David | Engineering
6 | Kim | Finance
(14 rows)