집 >데이터 베이스 >MySQL 튜토리얼 >MySQL 데이터베이스 쿼리에서 다중 테이블 쿼리를 구현하는 방법
MySQL 데이터베이스 쿼리에서 다중 테이블 쿼리를 구현하는 방법
- WBOY앞으로
- 2023-05-29 16:18:265778검색
1. 다중 테이블 쿼리
연관 쿼리라고도 하는 다중 테이블 쿼리는 두 개 이상의 테이블이 함께 쿼리 작업을 완료하는 것을 말합니다.
전제 조건: 함께 쿼리되는 테이블 간에는 관계가 있어야 합니다(일대일, 일대다). 이 관련 필드에는 외래 키가 설정되어 있을 수도 있고 없을 수도 있습니다. 예를 들어 직원 테이블과 부서 테이블은 "부서 번호"로 관련되어 있습니다.
1. 소개
이제 직원 이름과 부서 이름을 쿼리한다고 가정해 보겠습니다.
이 두 필드가 서로 다른 테이블에 있으면 쿼리 결과는 어떻게 될까요? 구경하다. .
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
분명히 위 작업은 잘못되었습니다
위 작업을 수행하면 직원이 모든 부서에서 근무한 것처럼 직원 테이블의 레코드가 부서 테이블의 모든 레코드와 일치하게 됩니다. 이런 상황은 발생하지 않을 것이 분명합니다. 이 현상은 데카르트 곱입니다.
SQL92에서는 데카르트 곱을 크로스 조인이라고도 하며 영어로는3. 데카르트 곱의 해결 방법입니다. SQL99에서는 CROSS JOIN을 사용하여 교차 연결을 나타냅니다. 그 기능은 두 테이블이 관련되지 않은 경우에도 모든 테이블을 조인하는 것입니다. MySQL에서는 다음과 같은 상황에서 데카르트 곱이 발생합니다.
CROSS JOIN직원 이름과 부서 이름을 쿼리합니다.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;
다음 조건에서 데카르트 곱 오류가 발생합니다. :
다음 조건에서 데카르트 곱 오류가 발생합니다:
- 여러 테이블에 대한 조인 조건(또는 연결 조건) 생략
- 잘못된 연결 조건(또는 연결 조건)
- 모든 테이블의 모든 행은 서로 연결되어 있습니다.
- 데카르트 곱을 피하기 위해
WHERE에 유효한 연결 조건을 추가할 수 있습니다.
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;참고: 서로 다른 테이블에 동일한 필드가 있는 경우 확인 중인 테이블의 필드를 선언해야 합니다. 필드 이름은 Java의 클래스 이름과 유사합니다. 이해하다.
SELECT employees.last_name, departments.department_name,employees.department_id FROM employees, departments WHERE employees.department_id = departments.department_id;2. 다중 테이블 쿼리 분류 1. 등가 조인과 비등가 조인
등가 조인은 실제로 이해하기 쉽습니다. 즉, 누가 누구와 같은지 =를 사용합니다.특정 필드 > 특정 값 등의 레코드 쿼리와 같은 비동등 연결의 경우
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;확장:2. Self-connection과 Non-Self-Connection별칭을 사용하면 쿼리를 단순화할 수 있습니다. — 일부 필드 이름이 너무 깁니다. 열 이름 앞에 테이블 이름 접두사를 사용하면 쿼리 효율성이 향상됩니다.
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;테이블의 별칭을 사용하는 경우 쿼리 필드 및 필터 조건에서만 별칭을 사용할 수 있으며 원래 테이블 이름을 사용할 수 없습니다. 그렇지 않으면 오류가 보고됩니다.
Self-connection, 말 그대로 자신과 연결된다는 뜻예를 들어 지금 테이블이 있는데, 직원 정보와 그에 해당하는 상위 정보를 찾고 싶다
우리는 하나의 테이블에 연결할 수 있는 방법이 없다는 것을 알고 있어야 합니다. 연결하려면 연결 조건이 있어야 합니다. 그러면 테이블이 두 개 있어야 하며 원본 테이블은 기본적으로 table1과 table2는 본질적으로 동일한 테이블이지만 서로 다른 의미를 나타내기 위해 별칭을 사용하여 두 개의 테이블로 가상화됩니다. 그런 다음 내부 조인, 외부 조인 등을 사용하여 두 테이블을 쿼리합니다.
예: 이제 직원의 이름과 해당 상사의 이름을 찾고 싶다면 self-connection3. 내부 조인 및 외부 조인내부 조인: 동일한 열이 있는 두 개 이상의 테이블에서 행을 병합합니다.SELECT CONCAT(worker.last_name ,' works for ' , manager.last_name) FROM employees worker, employees manager WHERE worker.manager_id = manager.employee_id ;을 사용하면 됩니다. 연습: 성이 ‘Chen’인 직원의 관리자 정보를 쿼리하세요.
결과 집합에는 한 테이블과 다른 테이블과 일치하지 않는 행이 포함되지 않습니다.
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)
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
以查询各个部门的员工信息为例，它们之间的连接条件是员工表中的部门id与部门表中的部门id相同
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
使用UNION关键字，可以将多个SELECT语句的结果组合成一个结果集。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。使用UNION或UNION ALL关键字来分隔各个SELECT语句。
语法格式：
SELECT column,… FROM table1
UNION [ALL]
SELECT column,… FROM table2
UNION操作符
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
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
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。
聚合函数类型
AVG()
SUM()
MAX()
MIN()
COUNT()
语法
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)
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
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> 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。
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。
在需要对数据进行分组统计时，HAVING语句能够完成WHERE语句无法完成的任务。由于查询语法结构中WHERE在GROUP BY之前，因此无法筛选分组结果。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：
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。HAVING is used for conditions that involve grouping and aggregation functions, while WHERE is used for regular conditions.。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
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：
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；
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；
바깥쪽 행을 추가하세요. 왼쪽 조인, 오른쪽 링크 또는 전체 조인을 사용하는 경우 외부 행이 포함됩니다. 즉, 가상 테이블 vt1-2에 외부 행을 추가하면 가상 테이블 vt1-3이 생성됩니다.
테이블을 2개 이상 운영하는 경우 모든 테이블이 처리될 때까지 위의 단계를 반복하게 됩니다. 이 프로세스를 통해 원본 데이터가 생성됩니다.
최종 가상 테이블 vt1인 쿼리 데이터 테이블의 원본 데이터를 얻으면 이를 기반으로 WHERE 단계로 진행할 수 있습니다. 이 단계에서는 vt1 테이블의 결과가 필터링되고 필터링되어 가상 테이블 vt2가 생성됩니다.
다음 단계는 세 번째와 네 번째 단계로 그룹화와 심사 단계입니다. 이 단계에서는 가상 테이블 vt2를 기반으로 실제로 그룹화 및 그룹 필터링이 수행되고, 중간 가상 테이블 vt3, vt4가 획득된다.
조건부 필터링 부분을 완료한 후에는 테이블에서 추출된 필드를 필터링할 수 있습니다. 즉, SELECT 및 DISTINCT 단계로 들어갈 수 있습니다.
먼저 SELECT 단계에서 원하는 필드를 추출한 다음 DISTINCT 단계에서 중복 행을 필터링하여 각각 중간 가상 테이블 vt5-1과 vt5-2를 얻습니다.
원하는 필드 데이터를 추출한 후 ORDER BY 단계인 지정된 필드에 따라 정렬하고 가상 테이블 vt6을 얻을 수 있습니다.
마지막으로 vt6를 기준으로 지정된 행의 레코드를 꺼내는 것이 LIMIT 단계이고 최종 결과는 가상 테이블 vt7에 해당합니다.
물론 SELECT 문을 작성할 때 모든 키워드가 존재할 수는 없으며 해당 단계는 생략됩니다.
동시에 SQL은 영어와 유사한 구조화된 쿼리 언어이기 때문에 SELECT 문을 작성할 때 해당 키워드 순서에도 주의해야 합니다. 소위 기본 작동 원리는 우리가 방금 말한 실행 순서입니다. 이야기했다.
위 내용은 MySQL 데이터베이스 쿼리에서 다중 테이블 쿼리를 구현하는 방법의 상세 내용입니다. 자세한 내용은 PHP 중국어 웹사이트의 기타 관련 기사를 참조하세요!
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