MySQL数据库查询进阶之多表查询详解


Posted in MySQL onApril 08, 2022

一、多表查询

多表查询,也称为关联查询,指两个或更多个表一起完成查询操作。

前提条件:这些一起查询的表之间是有关系的(一对一、一对多),它们之间一定是有关联字段,这个关联字段可能建立了外键,也可能没有建立外键。比如:员工表和部门表,这两个表依靠“部门编号”进行关联。

1.引出

假如我们现在要查询员工的姓名还有部门名称

这两个字段在不同表中,如果没有关联条件的话,查询出来的结果会怎么样呢,让我们来看看。

SELECT last_name, department_name
FROM employees, departments;
+-----------+----------------------+
| last_name | department_name      |
+-----------+----------------------+
| King      | Administration       |
| King      | Marketing            |
| King      | Purchasing           |
| King      | Human Resources      |
| King      | Shipping             |
| King      | IT                   |
| King      | Public Relations     |
| King      | Sales                |
| King      | Executive            |
| King      | Finance              |
| King      | Accounting           |
| King      | Treasury             |
...
| Gietz     | IT Support           |
| Gietz     | NOC                  |
| Gietz     | IT Helpdesk          |
| Gietz     | Government Sales     |
| Gietz     | Retail Sales         |
| Gietz     | Recruiting           |
| Gietz     | Payroll              |
+-----------+----------------------+
2889 rows in set (0.01 sec)
SELECT COUNT(employee_id) FROM employees;
#输出107行

SELECT COUNT(department_id)FROM departments;
#输出27行

SELECT 107*27 FROM dual;
107*27=2889

很明显上面的操作是错误的

MySQL数据库查询进阶之多表查询详解

上面的操作,会导致员工表的一条记录会和部门表的每一条记录相匹配,就好像一个员工在所有部门都工作过一样,从现实角度来说,很明显,是不会出现这种情况的,
这种现象就是笛卡尔积。

2.笛卡尔积

笛卡儿积就是关系代数里的一个概念,表示两个表中的每一行数据任意组合的结果。比如:有两个表,左表有m条数据记录,x个字段,右表有n条数据记录,y个字段,则执行交叉连接后将返回m*n条数据记录,x+y个字段。笛卡儿积示意图如图所示。

MySQL数据库查询进阶之多表查询详解

SQL92中,笛卡尔积也称为交叉连接,英文是 CROSS JOIN。在 SQL99 中也是使用 CROSS JOIN表示交叉连接。它的作用就是可以把任意表进行连接,即使这两张表不相关。在MySQL中如下情况会出现笛卡尔积:
查询员工姓名和所在部门名称

SELECT last_name,department_name FROM employees,departments;
SELECT last_name,department_name FROM employees CROSS JOIN departments;
SELECT last_name,department_name FROM employees INNER JOIN departments;
SELECT last_name,department_name FROM employees JOIN departments;

3. 笛卡尔积的解决方法

笛卡尔积的错误会在下面条件下产生

  • 笛卡尔积的错误会在下面条件下产生

    • 省略多个表的连接条件(或关联条件)
    • 连接条件(或关联条件)无效
    • 所有表中的所有行互相连接
  • 为了避免笛卡尔积, 可以在 WHERE 加入有效的连接条件。

SELECT	table1.column, table2.column
FROM	table1, table2
WHERE	table1.column1 = table2.column2;  #连接条件
#案例:查询员工的姓名及其部门名称
SELECT last_name, department_name
FROM employees, departments
WHERE employees.department_id = departments.department_id;

注意:如果不同的表中有相同的字段,我们要声明我们查的是哪一张表的字段,表名.字段名这个和Java中,类名.属性是类似的,挺好理解的。

SELECT employees.last_name, departments.department_name,employees.department_id
FROM employees, departments
WHERE employees.department_id = departments.department_id;

二、多表查询分类

1.等值连接和非等值连接

等值连接其实很好理解,就是谁等于谁的意思,使用=。
非等值连接的话,比如查询某个字段>某个值的记录等等
MySQL数据库查询进阶之多表查询详解

SELECT employees.employee_id, employees.last_name, 
      employees.department_id, departments.department_id,
    departments.location_id
FROM   employees, departments
WHERE  employees.department_id = departments.department_id;

拓展:

使用别名可以简化查询。— 有的字段名太长了列名前使用表名前缀可以提高查询效率。
SELECT e.employee_id, e.last_name, e.department_id,
d.department_id, d.location_id
FROM   employees e , departments d
WHERE  e.department_id = d.department_id;

需要注意的是,如果我们使用了表的别名,在查询字段中、过滤条件中就只能使用别名进行代替,不能使用原有的表名,否则就会报错。

2.自连接和非自连接

自连接,它的字面意思就是自己和自己连接
比如说现在有一张表,我们想要查找员工信息和对应的上级信息
我们知道,只有一张表是没办法把它们关联起来的,要想把它们他们关联起来,肯定是要有关联条件的,那么就应该要有两张表,这个时候,我们就可以抽取出一张表,和本来的表本质上是一样的,然后我们对表起别名,table1和table2本质上是同一张表,只是用取别名的方式虚拟成两张表以代表不同的意义。然后两个表再进行内连接,外连接等查询。MySQL数据库查询进阶之多表查询详解

比如说:现在我们想要查找员工和对应老板的名字,我们就可以使用自连接

SELECT CONCAT(worker.last_name ,' works for ' 
   , manager.last_name)
FROM   employees worker, employees manager
WHERE  worker.manager_id = manager.employee_id ;

练习:查询出last_name为 ‘Chen’ 的员工的 manager 的信息。MySQL数据库查询进阶之多表查询详解

3.内连接和外连接

内连接: 合并具有同一列的两个以上的表的行, 结果集中不包含一个表与另一个表不匹配的行

MySQL数据库查询进阶之多表查询详解

外连接: 两个表在连接过程中除了返回满足连接条件的行以外还返回左(或右)表中不满足条件的行 ,这种连接称为左(或右) 外连接。没有匹配的行时, 结果表中相应的列为空(NULL)。

如果是左外连接,则连接条件中左边的表也称为主表,右边的表称为从表。

如果是右外连接,则连接条件中右边的表也称为主表,左边的表称为从表。

外连接查询的数据比较多

SQL92:使用(+)创建连接

在 SQL92 中采用(+)代表从表所在的位置。即左或右外连接中,(+) 表示哪个是从表。

Oracle 对 SQL92 支持较好,而 MySQL 则不支持 SQL92 的外连接。

#左外连接
SELECT last_name,department_name
 FROM employees ,departments 
 WHERE  employees.department_id = departments.department_id(+);


#右外连接 
SELECT last_name,department_name 
FROM employees ,departments 
WHERE employees.department_id(+) = departments.department_id;  ```

SQL99语法实现多表查询

1.基本语法
使用JOIN…ON子句创建连接的语法结构:

SELECT table1.column, table2.column,table3.column FROM table1
    JOIN table2 ON table1 和 table2 的连接条件
        JOIN table3 ON table2 和 table3 的连接条件

语法说明:

可以使用 ON 子句指定额外的连接条件 。

这个连接条件是与其它条件分开的。ON 子句使语句具有更高的易读性。关键字 JOIN、INNER JOIN、CROSS JOIN 的含义是一样的,都表示内连接

2.内连接(INNER JOIN)
MySQL数据库查询进阶之多表查询详解
语法
select 字段
from 表1
join 表2 on 两个表的连接条件
where 其他子句

比如我们现在想要查询各个部门的员工的信息,他们的连接条件就是员工表中部门id和部门表中的部门id一样

SELECT e.employee_id, e.last_name, e.department_id, 
       d.department_id, d.location_id
FROM   employees e JOIN departments d
ON     (e.department_id = d.department_id);
这里截取部分结果
+-------------+-------------+---------------+---------------+-------------+
| employee_id | last_name   | department_id | department_id | location_id |
+-------------+-------------+---------------+---------------+-------------+
|         103 | Hunold      |            60 |            60 |        1400 |
|         104 | Ernst       |            60 |            60 |        1400 |
|         105 | Austin      |            60 |            60 |        1400 |
|         106 | Pataballa   |            60 |            60 |        1400 |
|         107 | Lorentz     |            60 |            60 |        1400 |
|         120 | Weiss       |            50 |            50 |        1500 |
|         121 | Fripp       |            50 |            50 |        1500 |
|         122 | Kaufling    |            50 |            50 |        1500 |
|         123 | Vollman     |            50 |            50 |        1500 |
|         124 | Mourgos     |            50 |            50 |        1500 |
|         125 | Nayer       |            50 |            50 |        1500 |
|         126 | Mikkilineni |            50 |            50 |        1500 |
|         127 | Landry      |            50 |            50 |        1500 |
|         128 | Markle      |            50 |            50 |        1500 |
|         129 | Bissot      |            50 |            50 |        1500 |

使用内连接的一个问题就是他们把所有的信息都显示出来,它只能够显示匹配的数据,而外连接可以把不匹配的数据也显示出来

先来看看表的数据,方便后续操作

mysql> select * from emp;
+-------+--------+-----------+------+------------+---------+---------+--------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO |
+-------+--------+-----------+------+------------+---------+---------+--------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |
+-------+--------+-----------+------+------------+---------+---------+--------+
14 rows in set (0.00 sec)
mysql> select * from dept;
+--------+------------+----------+
| DEPTNO | DNAME      | LOC      |
+--------+------------+----------+
|     10 | ACCOUNTING | NEW YORK |
|     20 | RESEARCH   | DALLAS   |
|     30 | SALES      | CHICAGO  |
|     40 | OPERATIONS | BOSTON   |
+--------+------------+----------+
4 rows in set (0.00 sec)
mysql> select * from emp e
    -> join dept d
    -> on e.deptno=e.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     10 | ACCOUNTING | NEW YORK |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     10 | ACCOUNTING | NEW YORK |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     10 | ACCOUNTING | NEW YORK |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     10 | ACCOUNTING | NEW YORK |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     10 | ACCOUNTING | NEW YORK |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     10 | ACCOUNTING | NEW YORK |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     10 | ACCOUNTING | NEW YORK |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     10 | ACCOUNTING | NEW YORK |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     10 | ACCOUNTING | NEW YORK |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     10 | ACCOUNTING | NEW YORK |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     10 | ACCOUNTING | NEW YORK |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     20 | RESEARCH   | DALLAS   |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     20 | RESEARCH   | DALLAS   |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     20 | RESEARCH   | DALLAS   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     20 | RESEARCH   | DALLAS   |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     20 | RESEARCH   | DALLAS   |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     20 | RESEARCH   | DALLAS   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     20 | RESEARCH   | DALLAS   |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     20 | RESEARCH   | DALLAS   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     20 | RESEARCH   | DALLAS   |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     30 | SALES      | CHICAGO  |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     30 | SALES      | CHICAGO  |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     30 | SALES      | CHICAGO  |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     30 | SALES      | CHICAGO  |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     30 | SALES      | CHICAGO  |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     30 | SALES      | CHICAGO  |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     40 | OPERATIONS | BOSTON   |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     40 | OPERATIONS | BOSTON   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     40 | OPERATIONS | BOSTON   |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     40 | OPERATIONS | BOSTON   |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     40 | OPERATIONS | BOSTON   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     40 | OPERATIONS | BOSTON   |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     40 | OPERATIONS | BOSTON   |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     40 | OPERATIONS | BOSTON   |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     40 | OPERATIONS | BOSTON   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     40 | OPERATIONS | BOSTON   |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     40 | OPERATIONS | BOSTON   |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     40 | OPERATIONS | BOSTON   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     40 | OPERATIONS | BOSTON   |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
56 rows in set (0.01 sec)

– 问题:
– 1.40号部分没有员工,没有显示在查询结果中
– 2.员工scott没有部门,没有显示在查询结果中
所以想显示所有数据,要使用外连接

外连接(OUTER JOIN)
1.左外连接

左外连接: left outer join – 左面的那个表的信息,即使不匹配也可以查看出效果
SELECT 字段列表
FROM A表 LEFT JOIN B表
ON 关联条件
WHERE 等其他子句;

2.右外连接
SELECT 字段列表
FROM A表 RIGHT JOIN B表
ON 关联条件
WHERE 等其他子句;

mysql> select *
    -> from emp e
    -> right outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  NULL | NULL   | NULL      | NULL | NULL       |    NULL |    NULL |   NULL |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
15 rows in set (0.00 sec)

3.满外连接(FULL OUTER JOIN)

满外连接的结果 = 左右表匹配的数据 + 左表没有匹配到的数据 + 右表没有匹配到的数据。
SQL99是支持满外连接的。使用FULL JOIN 或 FULL OUTER JOIN来实现。
需要注意的是,MySQL不支持FULL JOIN,但是可以用 LEFT JOIN UNION RIGHT join代替。
在讲满外连接之前,我们先来介绍一下union关键字的使用,相信看了以后大家就清楚了

4.UNION

合并查询结果

利用UNION关键字,可以给出多条SELECT语句,并将它们的结果组合成单个结果集。合并时,两个表对应的列数和数据类型必须相同,并且相互对应。各个SELECT语句之间使用UNION或UNION ALL关键字分隔。

语法格式:

SELECT column,… FROM table1
UNION [ALL]
SELECT column,… FROM table2

UNION操作符

MySQL数据库查询进阶之多表查询详解

UNION 操作符返回两个查询的结果集的并集,去除重复记录。

`UNION ALL操作符

MySQL数据库查询进阶之多表查询详解

UNION ALL操作符返回两个查询的结果集的并集。对于两个结果集的重复部分,不去重。

注意:执行UNION ALL语句时所需要的资源比UNION语句少。如果明确知道合并数据后的结果数据不存在重复数据,或者不需要去除重复的数据,则尽量使用UNION ALL语句,以提高数据查询的效率。
为什么union all的效率比较高呢?首先我们如果使用union的话,它会先把数据查询出来,紧接着还要进去去重操作,它多了一步去重操作,当然花费的时间就比较多了,影响效率。

mysql> select *
    -> from emp e
    -> left outer join dept d
    -> on e.deptno = d.deptno
    -> union -- 并集 去重 效率低
    -> select *
    -> from emp e
    -> right outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  NULL | NULL   | NULL      | NULL | NULL       |    NULL |    NULL |   NULL |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
15 rows in set (0.01 sec)

mysql> ^C
mysql> https://blog.csdn.net/weixin_42250835/article/details/123535439^Z^Z^C
mysql> select *
    -> from emp e
    -> left outer join dept d
    -> on e.deptno = d.deptno
    -> union -- 并集 去重 效率低
    -> select *
    -> from emp e
    -> right outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  NULL | NULL   | NULL      | NULL | NULL       |    NULL |    NULL |   NULL |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
15 rows in set (0.00 sec)

mysql> select *
    -> from emp e
    -> left outer join dept d
    -> on e.deptno = d.deptno
    -> union all-- 并集 不去重 效率高
    -> select *
    -> from emp e
    -> right outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  NULL | NULL   | NULL      | NULL | NULL       |    NULL |    NULL |   NULL |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
29 rows in set (0.00 sec)

为了让大家更清楚知道他们的区别,我们分别看一下有多少记录

-> on e.deptno = d.deptno' at line 2
mysql> select *
    -> from emp e
    -> left outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
14 rows in set (0.00 sec)

mysql> select *
    -> from emp e
    -> right outer join dept d
    -> on e.deptno = d.deptno;
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO | DEPTNO | DNAME      | LOC      |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |     10 | ACCOUNTING | NEW YORK |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |     20 | RESEARCH   | DALLAS   |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |     30 | SALES      | CHICAGO  |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |     30 | SALES      | CHICAGO  |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |     30 | SALES      | CHICAGO  |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |     30 | SALES      | CHICAGO  |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |     30 | SALES      | CHICAGO  |
|  NULL | NULL   | NULL      | NULL | NULL       |    NULL |    NULL |   NULL |     40 | OPERATIONS | BOSTON   |
+-------+--------+-----------+------+------------+---------+---------+--------+--------+------------+----------+
15 rows in set (0.00 sec)

14+15=29所=所以可以看出union all确实是不去重

总结
MySQL数据库查询进阶之多表查询详解

中图:内连接 A∩B
SELECT employee_id,last_name,department_name
FROM employees e JOIN departments d
ON e.`department_id` = d.`department_id`;
左上图:左外连接
SELECT employee_id,last_name,department_name
FROM employees e LEFT JOIN departments d
ON e.`department_id` = d.`department_id`;
右上图:右外连接
SELECT employee_id,last_name,department_name
FROM employees e RIGHT JOIN departments d
ON e.`department_id` = d.`department_id`;
左中图:A - A∩B
SELECT employee_id,last_name,department_name
FROM employees e LEFT JOIN departments d
ON e.`department_id` = d.`department_id`
WHERE d.`department_id` IS NULL
右中图:B-A∩B
SELECT employee_id,last_name,department_name
FROM employees e RIGHT JOIN departments d
ON e.`department_id` = d.`department_id`
WHERE e.`department_id` IS NULL
左下图:满外连接
  左中图 + 右上图  A∪B
SELECT employee_id,last_name,department_name
FROM employees e LEFT JOIN departments d
ON e.`department_id` = d.`department_id`
WHERE d.`department_id` IS NULL
UNION ALL  #没有去重操作,效率高
SELECT employee_id,last_name,department_name
FROM employees e RIGHT JOIN departments d
ON e.`department_id` = d.`department_id`;
右下图
 左中图 + 右中图  A ∪B- A∩B 或者 (A -  A∩B) ∪ (B - A∩B)
SELECT employee_id,last_name,department_name
FROM employees e LEFT JOIN departments d
ON e.`department_id` = d.`department_id`
WHERE d.`department_id` IS NULL
UNION ALL
SELECT employee_id,last_name,department_name
FROM employees e RIGHT JOIN departments d
ON e.`department_id` = d.`department_id`
WHERE e.`department_id` IS NULL

4.自然连接

SQL99 在 SQL92 的基础上提供了一些特殊语法,比如 NATURAL JOIN 用来表示自然连接。我们可以把自然连接理解为 SQL92 中的等值连接。它会帮你自动查询两张连接表中所有相同的字段,然后进行等值连接

SELECT employee_id,last_name,department_name
FROM employees e NATURAL JOIN departments d;

上面的写法的效果和下面是一样的

SELECT employee_id,last_name,department_name
FROM employees e JOIN departments d
USING (department_id);

5.using连接

当我们进行连接的时候,SQL99还支持使用 USING 指定数据表里的同名字段进行等值连接。但是只能配合JOIN一起使用。比如:

SELECT employee_id,last_name,department_name
FROM employees e JOIN departments d
USING (department_id);

你能看出与自然连接 NATURAL JOIN 不同的是,USING 指定了具体的相同的字段名称,你需要在 USING 的括号 () 中填入要指定的同名字段。同时使用 JOIN...USING 可以简化 JOIN ON 的等值连接。它与下面的 SQL 查询结果是相同的:

SELECT employee_id,last_name,department_name
FROM employees e ,departments d
WHERE e.department_id = d.department_id;

注意:using只能和join配合使用,而且要求两个关联字段在关联表中名称一致,而且只能表示关联字段值相等

三、子查询

1.不相关子查询

子查询就是查询语句的嵌套,有多个select语句

子查询的引入:

– 查询所有比“CLARK”工资高的员工的信息

– 步骤1:“CLARK”工资

mysql> select * from emp where ename='clark';  工资2450
+-------+-------+---------+------+------------+---------+------+--------+
| EMPNO | ENAME | JOB     | MGR  | HIREDATE   | SAL     | COMM | DEPTNO |
+-------+-------+---------+------+------------+---------+------+--------+
|  7782 | CLARK | MANAGER | 7839 | 1981-06-09 | 2450.00 | NULL |     10 |
+-------+-------+---------+------+------------+---------+------+--------+
1 row in set (0.00 sec)

– 步骤2:查询所有工资比2450高的员工的信息

mysql> select * from emp where sal > 2450;
+-------+-------+-----------+------+------------+---------+------+--------+
| EMPNO | ENAME | JOB       | MGR  | HIREDATE   | SAL     | COMM | DEPTNO |
+-------+-------+-----------+------+------------+---------+------+--------+
|  7566 | JONES | MANAGER   | 7839 | 1981-04-02 | 2975.00 | NULL |     20 |
|  7698 | BLAKE | MANAGER   | 7839 | 1981-05-01 | 2850.00 | NULL |     30 |
|  7788 | SCOTT | ANALYST   | 7566 | 1987-04-19 | 3000.00 | NULL |     20 |
|  7839 | KING  | PRESIDENT | NULL | 1981-11-17 | 5000.00 | NULL |     10 |
|  7902 | FORD  | ANALYST   | 7566 | 1981-12-03 | 3000.00 | NULL |     20 |
+-------+-------+-----------+------+------------+---------+------+--------+
5 rows in set (0.01 sec)

两次命令解决问题的话,效率低 ,第二个命令依托于第一个命令,第一个命令的结果给第二个命令使用,但是
因为第一个命令的结果可能不确定要改,所以第二个命令也会导致修改
将步骤1和步骤2合并 --》子查询:-- 一个命令解决问题 --》效率高

mysql> select *from emp where sal>(select sal from emp where ename='clark');
+-------+-------+-----------+------+------------+---------+------+--------+
| EMPNO | ENAME | JOB       | MGR  | HIREDATE   | SAL     | COMM | DEPTNO |
+-------+-------+-----------+------+------------+---------+------+--------+
|  7566 | JONES | MANAGER   | 7839 | 1981-04-02 | 2975.00 | NULL |     20 |
|  7698 | BLAKE | MANAGER   | 7839 | 1981-05-01 | 2850.00 | NULL |     30 |
|  7788 | SCOTT | ANALYST   | 7566 | 1987-04-19 | 3000.00 | NULL |     20 |
|  7839 | KING  | PRESIDENT | NULL | 1981-11-17 | 5000.00 | NULL |     10 |
|  7902 | FORD  | ANALYST   | 7566 | 1981-12-03 | 3000.00 | NULL |     20 |
+-------+-------+-----------+------+------------+---------+------+--------+
5 rows in set (0.00 sec)

【2】执行顺序:

先执行子查询,再执行外查询;

【3】不相关子查询:

子查询可以独立运行,称为不相关子查询。

【4】不相关子查询分类:

根据子查询的结果行数,可以分为单行子查询和多行子查询。

练习

单行子查询

mysql> -- 单行子查询
mysql> -- 查询工资高与拼接工资的员工名字和工资
mysql> select ename,sal from emp
    -> where sal>(select avg(sal) from emp);
+-------+---------+
| ename | sal     |
+-------+---------+
| JONES | 2975.00 |
| BLAKE | 2850.00 |
| CLARK | 2450.00 |
| SCOTT | 3000.00 |
| KING  | 5000.00 |
| FORD  | 3000.00 |
+-------+---------+
6 rows in set (0.00 sec)
-- 查询和CLARK同一部门且比他工资低的雇员名字和工资。
select ename,sal
from emp
where deptno = (select deptno from emp where ename = 'CLARK') 
      and 
      sal < (select sal from emp where ename = 'CLARK')
+--------+---------+
| ename  | sal     |
+--------+---------+
| MILLER | 1300.00 |
+--------+---------+
1 row in set (0.00 sec)
多行子查询:
  【1】查询【部门20中职务同部门10的雇员一样的】雇员信息。
-- 查询雇员信息
select * from emp;
+-------+--------+-----------+------+------------+---------+---------+--------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO |
+-------+--------+-----------+------+------------+---------+---------+--------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |
+-------+--------+-----------+------+------------+---------+---------+--------+
14 rows in set (0.00 sec)
-- 查询部门20中的雇员信息
select * from emp where deptno = 20;
+-------+-------+---------+------+------------+---------+------+--------+
| EMPNO | ENAME | JOB     | MGR  | HIREDATE   | SAL     | COMM | DEPTNO |
+-------+-------+---------+------+------------+---------+------+--------+
|  7369 | SMITH | CLERK   | 7902 | 1980-12-17 |  800.00 | NULL |     20 |
|  7566 | JONES | MANAGER | 7839 | 1981-04-02 | 2975.00 | NULL |     20 |
|  7788 | SCOTT | ANALYST | 7566 | 1987-04-19 | 3000.00 | NULL |     20 |
|  7876 | ADAMS | CLERK   | 7788 | 1987-05-23 | 1100.00 | NULL |     20 |
|  7902 | FORD  | ANALYST | 7566 | 1981-12-03 | 3000.00 | NULL |     20 |
+-------+-------+---------+------+------------+---------+------+--------+
5 rows in set (0.00 sec)
-- 部门10的雇员的职务:
select job from emp where deptno = 10; -- MANAGER,PRESIDENT,CLERK
+-----------+
| job       |
+-----------+
| MANAGER   |
| PRESIDENT |
| CLERK     |
+-----------+
3 rows in set (0.00 sec)
-- 查询部门20中职务同部门10的雇员一样的雇员信息。
select * from emp 
where deptno = 20 
and job in (select job from emp where deptno = 10)
-- > Subquery returns more than 1 row
select * from emp 
where deptno = 20 
and job = any(select job from emp where deptno = 10)
【2】查询工资比所有的“SALESMAN”都高的雇员的编号、名字和工资。
-- 查询雇员的编号、名字和工资
select empno,ename,sal from emp
+-------+--------+---------+
| empno | ename  | sal     |
+-------+--------+---------+
|  7369 | SMITH  |  800.00 |
|  7499 | ALLEN  | 1600.00 |
|  7521 | WARD   | 1250.00 |
|  7566 | JONES  | 2975.00 |
|  7654 | MARTIN | 1250.00 |
|  7698 | BLAKE  | 2850.00 |
|  7782 | CLARK  | 2450.00 |
|  7788 | SCOTT  | 3000.00 |
|  7839 | KING   | 5000.00 |
|  7844 | TURNER | 1500.00 |
|  7876 | ADAMS  | 1100.00 |
|  7900 | JAMES  |  950.00 |
|  7902 | FORD   | 3000.00 |
|  7934 | MILLER | 1300.00 |
+-------+--------+---------+
14 rows in set (0.00 sec)
-- “SALESMAN”的工资:
select sal from emp where job = 'SALESMAN';
+---------+
| sal     |
+---------+
| 1600.00 |
| 1250.00 |
| 1250.00 |
| 1500.00 |
+---------+
4 rows in set (0.00 sec)
-- 查询工资比所有的“SALESMAN”都高的雇员的编号、名字和工资。
-- 多行子查询:
select empno,ename,sal 
from emp 
where sal > all(select sal from emp where job = 'SALESMAN');
+-------+-------+---------+
| empno | ename | sal     |
+-------+-------+---------+
|  7566 | JONES | 2975.00 |
|  7698 | BLAKE | 2850.00 |
|  7782 | CLARK | 2450.00 |
|  7788 | SCOTT | 3000.00 |
|  7839 | KING  | 5000.00 |
|  7902 | FORD  | 3000.00 |
+-------+-------+---------+
6 rows in set (0.00 sec)

2.相关子查询

【1】不相关的子查询引入:

不相关的子查询:子查询可以独立运行,先运行子查询,再运行外查询。

相关子查询:子查询不可以独立运行,并且先运行外查询,再运行子查询

【2】不相关的子查询优缺点:

好处:简单 功能强大(一些使用不相关子查询不能实现或者实现繁琐的子查询,可以使用相关子查询实现)

缺点:稍难理解

【3】sql展示:

-- 【1】查询最高工资的员工  (不相关子查询)
select * from emp where sal = (select max(sal) from emp)
-- 【2】查询本部门最高工资的员工   (相关子查询)
-- 方法1:通过不相关子查询实现:
select * from emp where deptno = 10 and sal = (select max(sal) from emp where deptno = 10)
union
select * from emp where deptno = 20 and sal = (select max(sal) from emp where deptno = 20)
union
select * from emp where deptno = 30 and sal = (select max(sal) from emp where deptno = 30)
-- 缺点:语句比较多,具体到底有多少个部分未知
-- 方法2: 相关子查询
select * from emp e where sal = (select max(sal) from emp where deptno = e.deptno) order by deptno
-- 【3】查询工资高于其所在岗位的平均工资的那些员工  (相关子查询)
-- 不相关子查询:
select * from emp where job = 'CLERK' and sal >= (select avg(sal) from emp where job = 'CLERK')
union ......
-- 相关子查询:
select * from emp e where sal >= (select avg(sal) from emp e2 where e2.job = e.job)

四、聚合函数

1.聚合函数介绍

聚合函数作用于一组数据,并对一组数据返回一个值。

MySQL数据库查询进阶之多表查询详解

聚合函数类型

  • AVG()
  • SUM()
  • MAX()
  • MIN()
  • COUNT()

语法

MySQL数据库查询进阶之多表查询详解

注意:聚合函数不允许嵌套使用

1.1 AVG和SUM函数

可以对数值型数据使用AVG 和 SUM 函数。

他们在计算有空值的时候,会把非空计算进去,然后自动忽略空值
AVG=SUM/COUNT

mysql> select * from emp;
+-------+--------+-----------+------+------------+---------+---------+--------+
| EMPNO | ENAME  | JOB       | MGR  | HIREDATE   | SAL     | COMM    | DEPTNO |
+-------+--------+-----------+------+------------+---------+---------+--------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 |  800.00 |    NULL |     20 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 | 1600.00 |  300.00 |     30 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 | 1250.00 |  500.00 |     30 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 | 2975.00 |    NULL |     20 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 | 1250.00 | 1400.00 |     30 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 | 2850.00 |    NULL |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 | 2450.00 |    NULL |     10 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1987-04-19 | 3000.00 |    NULL |     20 |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 | 5000.00 |    NULL |     10 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 | 1500.00 |    0.00 |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1987-05-23 | 1100.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 |  950.00 |    NULL |     30 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 | 3000.00 |    NULL |     20 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 | 1300.00 |    NULL |     10 |
+-------+--------+-----------+------+------------+---------+---------+--------+

14 rows in set (0.00 sec)

MySQL数据库查询进阶之多表查询详解

1.2 MIN和MAX函数

可以对任意数据类型的数据使用 MIN 和 MAX 函数。

1.3 COUNT函数

COUNT(*)返回表中记录总数,适用于任意数据类型

mysql> select count(*) from emp;
+----------+
| count(*) |
+----------+
|       14 |
+----------+
1 row in set (0.01 sec)

计算指定字段再查询结果中出现的个数

mysql> select count(comm) from emp;
+-------------+
| count(comm) |
+-------------+
|           4 |
+-------------+
1 row in set (0.00 sec)

COUNT(expr) 返回expr不为空的记录总数。

-问题:用count(*),count(1),count(列名)谁好呢?

其实,对于MyISAM引擎的表是没有区别的。这种引擎内部有一计数器在维护着行数。

Innodb引擎的表用count(*),count(1)直接读行数,复杂度是O(n),因为innodb真的要去数一遍。但好于具体的count(列名)。

问题:能不能使用count(列名)替换count(*)?

不要使用 count(列名)来替代 count(*)count(*)是 SQL92 定义的标准统计行数的语法,跟数据库无关,跟 NULL 和非 NULL 无关。

说明: count(*)会统计值为 NULL 的行,而 count(列名)不会统计此列为 NULL 值的行。
这样子讲的话,大家可能还比较懵,接下来,我来演示一下

MySQL数据库查询进阶之多表查询详解

MySQL数据库查询进阶之多表查询详解

MySQL数据库查询进阶之多表查询详解

2.group by

使用group by可以进行分组,我们以前使用avg可以求出所有员工的平均工资,但是如果我们想要求各个部门的员工的平均工资的话,就得对部门进行分组,以部门为单位来划分,然后求出他们各自的平均工资
注意:字段不可以和多行函数一起使用,因为记录个数不匹配,这样就会导致查询的数据没有全部展示,但是,如果这个字段属于分组是可以的
MySQL数据库查询进阶之多表查询详解

mysql> select deptno,avg(sal) from emp group by deptno;
+--------+-------------+
| deptno | avg(sal)    |
+--------+-------------+
|     20 | 2175.000000 |
|     30 | 1566.666667 |
|     10 | 2916.666667 |
+--------+-------------+
3 rows in set (0.00 sec)
统计各个岗位的平均工资
mysql> select job,avg(sal) from emp group by job;
+-----------+-------------+
| job       | avg(sal)    |
+-----------+-------------+
| CLERK     | 1037.500000 |
| SALESMAN  | 1400.000000 |
| MANAGER   | 2758.333333 |
| ANALYST   | 3000.000000 |
| PRESIDENT | 5000.000000 |
+-----------+-------------+
5 rows in set (0.00 sec)

3.使用having进行分组后的筛选

使用having的条件:

1 行已经被分组。

2. 使用了聚合函数。

3. 满足HAVING 子句中条件的分组将被显示。

4. HAVING 不能单独使用,必须要跟 GROUP BY 一起使用。

MySQL数据库查询进阶之多表查询详解

统计各个部门的平均工资 ,只显示平均工资2000以上的 - 分组以后进行二次筛选 having

mysql> select deptno,avg(sal) from emp
    -> group by deptno
    -> having avg(sal) >2000;
+--------+-------------+
| deptno | avg(sal)    |
+--------+-------------+
|     20 | 2175.000000 |
|     10 | 2916.666667 |
+--------+-------------+
2 rows in set (0.01 sec)

五、where和having的对比

区别1:WHERE 可以直接使用表中的字段作为筛选条件,但不能使用分组中的计算函数作为筛选条件;HAVING 必须要与 GROUP BY 配合使用,可以把分组计算的函数和分组字段作为筛选条件。

这决定了,在需要对数据进行分组统计的时候,HAVING 可以完成 WHERE 不能完成的任务。这是因为,在查询语法结构中,WHERE 在 GROUP BY 之前,所以无法对分组结果进行筛选。HAVING 在 GROUP BY 之后,可以使用分组字段和分组中的计算函数,对分组的结果集进行筛选,这个功能是 WHERE 无法完成的。另外,WHERE排除的记录不再包括在分组中。

区别2:如果需要通过连接从关联表中获取需要的数据,WHERE 是先筛选后连接,而 HAVING 是先连接后筛选。 这一点,就决定了在关联查询中,WHERE 比 HAVING 更高效。因为 WHERE 可以先筛选,用一个筛选后的较小数据集和关联表进行连接,这样占用的资源比较少,执行效率也比较高。HAVING 则需要先把结果集准备好,也就是用未被筛选的数据集进行关联,然后对这个大的数据集进行筛选,这样占用的资源就比较多,执行效率也较低。

小结如下:

MySQL数据库查询进阶之多表查询详解

开发中的选择:

WHERE 和 HAVING 也不是互相排斥的,我们可以在一个查询里面同时使用 WHERE 和 HAVING。包含分组统计函数的条件用 HAVING,普通条件用 WHERE。这样,我们就既利用了 WHERE 条件的高效快速,又发挥了 HAVING 可以使用包含分组统计函数的查询条件的优点。当数据量特别大的时候,运行效率会有很大的差别。

六、select的执行过程

1.关键字顺序

SELECT … FROM … WHERE … GROUP BY … HAVING … ORDER BY … LIMIT…

2.SELECT 语句的执行顺序

FROM -> WHERE -> GROUP BY -> HAVING -> SELECT 的字段 -> DISTINCT -> ORDER BY -> LIMIT

MySQL数据库查询进阶之多表查询详解

比如你写了一个 SQL 语句,那么它的关键字顺序和执行顺序是下面这样的:

SELECT DISTINCT player_id, player_name, count(*) as num  顺序 5
FROM player JOIN team ON player.team_id = team.team_id   顺序 1
WHERE height > 1.80  顺序 2
GROUP BY player.team_id   顺序 3
HAVING num > 2  顺序 4
ORDER BY num DESC   顺序 6
LIMIT 2   顺序 7

3.SQL的执行原理(先了解)

SELECT 是先执行 FROM 这一步的。在这个阶段,如果是多张表联查,还会经历下面的几个步骤:

  1. 首先先通过 CROSS JOIN 求笛卡尔积,相当于得到虚拟表 vt(virtual table)1-1;
  2. 通过 ON 进行筛选,在虚拟表 vt1-1 的基础上进行筛选,得到虚拟表 vt1-2;
  3. 添加外部行。如果我们使用的是左连接、右链接或者全连接,就会涉及到外部行,也就是在虚拟表 vt1-2 的基础上增加外部行,得到虚拟表 vt1-3。

当然如果我们操作的是两张以上的表,还会重复上面的步骤,直到所有表都被处理完为止。这个过程得到是我们的原始数据。

当我们拿到了查询数据表的原始数据,也就是最终的虚拟表 vt1,就可以在此基础上再进行 WHERE 阶段。在这个阶段中,会根据 vt1 表的结果进行筛选过滤,得到虚拟表 vt2。

然后进入第三步和第四步,也就是 GROUP 和 HAVING 阶段。在这个阶段中,实际上是在虚拟表 vt2 的基础上进行分组和分组过滤,得到中间的虚拟表 vt3 和 vt4。

当我们完成了条件筛选部分之后,就可以筛选表中提取的字段,也就是进入到 SELECT 和 DISTINCT 阶段。

首先在 SELECT 阶段会提取想要的字段,然后在 DISTINCT 阶段过滤掉重复的行,分别得到中间的虚拟表 vt5-1 和 vt5-2。

当我们提取了想要的字段数据之后,就可以按照指定的字段进行排序,也就是 ORDER BY 阶段,得到虚拟表 vt6。

最后在 vt6 的基础上,取出指定行的记录,也就是 LIMIT 阶段,得到最终的结果,对应的是虚拟表 vt7。

当然我们在写 SELECT 语句的时候,不一定存在所有的关键字,相应的阶段就会省略。

同时因为 SQL 是一门类似英语的结构化查询语言,所以我们在写 SELECT 语句的时候,还要注意相应的关键字顺序,所谓底层运行的原理,就是我们刚才讲到的执行顺序。

总结

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