表的删改
3. Update
语法:
UPDATE table_name SET column = expr [, column = expr ...]
[WHERE ...] [ORDER BY ...] [LIMIT ...]
AI 代码解读
对查询到的结果进行列值更新
案例:
3.1 将孙悟空同学的数学成绩变更为 80 分
-- 更新值为具体值
-- 查看原数据
SELECT name, math FROM exam_result WHERE name = '孙悟空';
+-------+----+
| name |math|
+-------+----+
| 孙悟空 | 78 |
+-------+----+
1 row in set (0.00 sec)
-- 数据更新
UPDATE exam_result SET math = 80 WHERE name = '孙悟空';
Query OK, 1 row affected (0.04 sec)
Rows matched: 1 Changed: 1 Warnings: 0
-- 查看更新后数据
SELECT name, math FROM exam_result WHERE name = '孙悟空';
+-------+----+
| name |math|
+-------+----+
| 孙悟空 | 80 |
+-------+----+
1 row in set (0.00 sec)
AI 代码解读
3.2 将曹孟德同学的数学成绩变更为 60 分,语文成绩变更为 70 分
-- 一次更新多个列
-- 查看原数据
SELECT name, math, chinese FROM exam_result WHERE name = '曹孟德';
+-------+----+-------+
| name |math|chinese|
+-------+----+-------+
| 曹孟德 | 84 | 82 |
+-------+----+-------+
1 row in set (0.00 sec)
-- 数据更新
UPDATE exam_result SET math = 60, chinese = 70 WHERE name = '曹孟德';
Query OK, 1 row affected (0.14 sec)
Rows matched: 1 Changed: 1 Warnings: 0
-- 查看更新后数据
SELECT name, math, chinese FROM exam_result WHERE name = '曹孟德';
+-------+----+-------+
| name |math|chinese|
+-------+----+-------+
| 曹孟德 | 60 | 70 |
+-------+----+-------+
1 row in set (0.00 sec)
AI 代码解读
3.3 将总成绩倒数前三的 3 位同学的数学成绩加上 30 分
-- 更新值为原值基础上变更
-- 查看原数据
-- 别名可以在ORDER BY中使用
SELECT name, math, chinese + math + english 总分 FROM exam_result ORDER BY 总分 LIMIT 3;
+-------+----+-----+
| name |math| 总分 |
+-------+----+-----+
| 宋公明 | 65 | 170 |
| 刘玄德 | 85 | 185 |
| 曹孟德 | 60 | 197 |
+-------+----+-----+
3 rows in set (0.00 sec)
-- 数据更新,不支持 math += 30 这种语法
UPDATE exam_result SET math = math + 30 ORDER BY chinese + math + english LIMIT 3;
-- 查看更新后数据
-- 思考:这里还可以按总分升序排序取前 3 个么?
SELECT name, math, chinese + math + english 总分 FROM exam_result WHERE name IN ('宋公明', '刘玄德', '曹孟德');
+-------+----+-----+
| name |math| 总分 |
+-------+----+-----+
| 曹孟德 | 90 | 227 |
| 刘玄德 |115 | 215 |
| 宋公明 | 95 | 200 |
+-------+----+-----+
3 rows in set (0.00 sec)
-- 按总成绩排序后查询结果
SELECT name, math, chinese + math + english 总分 FROM exam_result ORDER BY 总分 LIMIT 3;
+-------+----+-----+
| name |math| 总分 |
+-------+----+-----+
| 宋公明 | 95 | 200 |
| 刘玄德 |115 | 215 |
| 唐三藏 | 98 | 221 |
+-------+----+-----+
3 rows in set (0.00 sec)
AI 代码解读
3.4 将所有同学的语文成绩更新为原来的 2 倍
==注意:更新全表的语句慎用!==
-- 没有 WHERE 子句,则更新全表
-- 查看原数据
SELECT * FROM exam_result;
+---+-------+-------+----+-------+
| id| name |chinese|math|english|
+---+-------+-------+----+-------+
| 1 | 唐三藏 | 67 | 98 | 56 |
| 2 | 孙悟空 | 87 | 80 | 77 |
| 3 | 猪悟能 | 88 | 98 | 90 |
| 4 | 曹孟德 | 70 | 90 | 67 |
| 5 | 刘玄德 | 55 | 115| 45 |
| 6 | 孙权 | 70 | 73 | 78 |
| 7 | 宋公明 | 75 | 95 | 30 |
+---+-------+-------+----+-------+
7 rows in set (0.00 sec)
-- 数据更新
UPDATE exam_result SET chinese = chinese * 2;
Query OK, 7 rows affected (0.00 sec)
Rows matched: 7 Changed: 7 Warnings: 0
-- 查看更新后数据
SELECT * FROM exam_result;
+---+-------+-------+----+--------+
| id| name |chinese|math|english |
+---+-------+-------+----+--------+
| 1 | 唐三藏 | 134 | 98 | 56 |
| 2 | 孙悟空 | 174 | 80 | 77 |
| 3 | 猪悟能 | 176 | 98 | 90 |
| 4 | 曹孟德 | 140 | 90 | 67 |
| 5 | 刘玄德 | 110 |115 | 45 |
| 6 | 孙权 | 140 | 73 | 78 |
| 7 | 宋公明 | 150 | 95 | 30 |
+---+-------+-------+----+--------+
7 rows in set (0.00 sec)
AI 代码解读
4. Delete
4.1 删除数据
语法:
DELETE FROM table_name [WHERE ...] [ORDER BY ...] [LIMIT ...]
AI 代码解读
案例:
4.1.1 删除孙悟空同学的考试成绩
-- 查看原数据
SELECT * FROM exam_result WHERE name = '孙悟空';
+---+-------+-------+----+-------+
| id| name |chinese|math|english|
+---+-------+-------+----+-------+
| 2 | 孙悟空 | 174 | 80 | 77 |
+---+-------+-------+----+-------+
1 row in set (0.00 sec)
-- 删除数据
DELETE FROM exam_result WHERE name = '孙悟空';
Query OK, 1 row affected (0.17 sec)
-- 查看删除结果
SELECT * FROM exam_result WHERE name = '孙悟空';
Empty set (0.00 sec)
AI 代码解读
4.1.2 删除整张表数据
注意:删除整表操作要慎用!
-- 准备测试表
CREATE TABLE for_delete (
id INT PRIMARY KEY AUTO_INCREMENT,
name VARCHAR(20)
);
Query OK, 0 rows affected (0.16 sec)
-- 插入测试数据
INSERT INTO for_delete (name) VALUES ('A'), ('B'), ('C');
Query OK, 3 rows affected (1.05 sec)
Records: 3 Duplicates: 0 Warnings: 0
-- 查看测试数据
SELECT * FROM for_delete;
+---+----+
| id|name|
+---+----+
| 1 | A |
| 2 | B |
| 3 | C |
+---+----+
3 rows in set (0.00 sec)
AI 代码解读
-- 删除整表数据
DELETE FROM for_delete;
Query OK, 3 rows affected (0.00 sec)
-- 查看删除结果
SELECT * FROM for_delete;
Empty set (0.00 sec)
AI 代码解读
-- 再插入一条数据,自增 id 在原值上增长
INSERT INTO for_delete (name) VALUES ('D');
Query OK, 1 row affected (0.00 sec)
-- 查看数据
SELECT * FROM for_delete;
+----+------+
| id | name |
+----+------+
| 4 | D |
+----+------+
1 row in set (0.00 sec)
-- 查看表结构,会有 AUTO_INCREMENT=n 项
SHOW CREATE TABLE for_delete\G
*************************** 1. row ***************************
Table: for_delete
Create Table: CREATE TABLE `for_delete` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(20) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8
1 row in set (0.00 sec)
AI 代码解读
知识拓展:
4.2 截断表
语法:
TRUNCATE [TABLE] table_name
AI 代码解读
==注意:这个操作慎用==
- 只能对整表操作,不能像 DELETE 一样针对部分数据操作;
- 实际上 MySQL 不对数据操作,所以比 DELETE 更快,但是TRUNCATE在删除数据的时候,并不经过真正的事
物,所以无法回滚 - 会重置 AUTO_INCREMENT 项
-- 准备测试表
CREATE TABLE for_truncate (
id INT PRIMARY KEY AUTO_INCREMENT,
name VARCHAR(20)
);
Query OK, 0 rows affected (0.16 sec)
-- 插入测试数据
INSERT INTO for_truncate (name) VALUES ('A'), ('B'), ('C');
Query OK, 3 rows affected (1.05 sec)
Records: 3 Duplicates: 0 Warnings: 0
-- 查看测试数据
SELECT * FROM for_truncate;
+---+----+
| id|name|
+---+----+
| 1 | A |
| 2 | B |
| 3 | C |
+---+----+
3 rows in set (0.00 sec)
AI 代码解读
-- 截断整表数据,注意影响行数是 0,所以实际上没有对数据真正操作
TRUNCATE for_truncate;
Query OK, 0 rows affected (0.10 sec)
-- 查看删除结果
SELECT * FROM for_truncate;
Empty set (0.00 sec)
-- 再插入一条数据,自增 id 在重新增长
INSERT INTO for_truncate (name) VALUES ('D');
Query OK, 1 row affected (0.00 sec)
-- 查看数据
SELECT * FROM for_truncate;
+---+----+
| id|name|
+---+----+
| 1 | D |
+---+----+
1 row in set (0.00 sec)
-- 查看表结构,会有 AUTO_INCREMENT=2 项
SHOW CREATE TABLE for_truncate\G
*************************** 1. row ***************************
Table: for_truncate
Create Table: CREATE TABLE `for_truncate` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(20) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8
1 row in set (0.00 sec)
AI 代码解读
5. 插入查询结果
语法:
INSERT INTO table_name [(column [, column ...])] SELECT ...
AI 代码解读
案例:删除表中的的重复复记录,重复的数据只能有一份
-- 创建原数据表
CREATE TABLE duplicate_table (id int, name varchar(20));
Query OK, 0 rows affected (0.01 sec)
-- 插入测试数据
INSERT INTO duplicate_table VALUES
(100, 'aaa'),
(100, 'aaa'),
(200, 'bbb'),
(200, 'bbb'),
(200, 'bbb'),
(300, 'ccc');
Query OK, 6 rows affected (0.00 sec)
Records: 6 Duplicates: 0 Warnings: 0
AI 代码解读
思路:
为啥最后通过rename方式进行呢? -- 就是等一切数据就绪再进行统一放入/更新/生效
不先进行rename再插入呢? -- MySQL当中rename的效率是非常高效的,插入是十分低效的而且也不安全(万一在插入的过程中断点丢失数据是非常危险的)
-- 查看最终结果
SELECT * FROM duplicate_table;
+----+-----+
| id | name|
+----+-----+
| 100| aaa |
| 200| bbb |
| 300| ccc |
+----+-----+
3 rows in set (0.00 sec)
AI 代码解读
6. 聚合函数
+-------------------------+------------------------------------+
| 函数 | 说明 |
+-------------------------+------------------------------------+
| COUNT([DISTINCT] expr) | 返回查询到的数据的 数量 |
| SUM([DISTINCT] expr) | 返回查询到的数据的 总和,不是数字没有意义 |
| AVG([DISTINCT] expr) | 返回查询到的数据的 平均值,不是数字没有意义|
| MAX([DISTINCT] expr) | 返回查询到的数据的 最大值,不是数字没有意义|
| MIN([DISTINCT] expr) | 返回查询到的数据的 最小值,不是数字没有意义|
+-------------------------+------------------------------------+
AI 代码解读
案例:
6.1 统计班级共有多少同学
-- 使用 * 做统计,不受 NULL 影响
SELECT COUNT(*) FROM students;
+----------+
| COUNT(*) |
+----------+
| 4 |
+----------+
1 row in set (0.00 sec)
-- 使用表达式做统计
SELECT COUNT(1) FROM students;
+----------+
| COUNT(1) |
+----------+
| 4 |
+----------+
1 row in set (0.00 sec)
AI 代码解读
6.2 统计班级收集的 qq 号有多少
-- NULL 不会计入结果
SELECT COUNT(qq) FROM students;
+-----------+
| COUNT(qq) |
+-----------+
| 1 |
+-----------+
1 row in set (0.00 sec)
AI 代码解读
6.3 统计本次考试的数学成绩分数个数
-- COUNT(math) 统计的是全部成绩
SELECT COUNT(math) FROM exam_result;
+-------------+
| COUNT(math) |
+-------------+
| 6 |
+-------------+
1 row in set (0.00 sec)
-- COUNT(DISTINCT math) 统计的是去重成绩数量
SELECT COUNT(DISTINCT math) FROM exam_result;
+----------------------+
| COUNT(DISTINCT math) |
+----------------------+
| 5 |
+----------------------+
1 row in set (0.00 sec)
AI 代码解读
6.4 统计数学成绩总分
SELECT SUM(math) FROM exam_result;
+-----------+
| SUM(math) |
+-----------+
| 569 |
+-----------+
1 row in set (0.00 sec)
-- 不及格 < 60 的总分,没有结果,返回 NULL
SELECT SUM(math) FROM exam_result WHERE math < 60;
+-----------+
| SUM(math) |
+-----------+
| NULL |
+-----------+
1 row in set (0.00 sec)
AI 代码解读
6.4 统计平均总分
SELECT AVG(chinese + math + english) 平均总分 FROM exam_result;
+---------+
| 平均总分 |
+---------+
| 297.5 |
+---------+
AI 代码解读
6.5 返回英语最高分
SELECT MAX(english) FROM exam_result;
+-------------+
| MAX(english)|
+-------------+
| 90 |
+-------------+
1 row in set (0.00 sec)
AI 代码解读
6.6 返回 > 70 分以上的数学最低分
SELECT MIN(math) FROM exam_result WHERE math > 70;
+-----------+
| MIN(math) |
+-----------+
| 73 |
+-----------+
1 row in set (0.00 sec)
AI 代码解读
7. group by子句的使用
在select中使用group by 子句可以对指定列进行分组查询
select column1, column2, .. from table group by column;
AI 代码解读
案例:
准备工作,创建一个雇员信息表(来自oracle 9i的经典测试表)
这里我将雇员信息表放在gitee上,点击这里即可!!!
- EMP员工表
- DEPT部门表
- SALGRADE工资等级表
下载到本地上之后导入到云服务的MySQL数据目录下:
-rw-r--r-- 1 root root 3878 Mar 25 2022 scott_data.sql
[root@iZ0jl69kyvg0h181cozuf5Z tt]# pwd
/var/lib/mysql/tt
这里tt是我自己建的数据库(自己选择路径)
AI 代码解读
将数据库还原出来:
mysql> source /var/lib/mysql/tt/scott_data.sql
Query OK, 0 rows affected, 1 warning (0.00 sec)
Query OK, 1 row affected (0.00 sec)
Database changed
Query OK, 0 rows affected, 1 warning (0.00 sec)
Query OK, 0 rows affected (0.01 sec)
Query OK, 0 rows affected, 1 warning (0.00 sec)
Query OK, 0 rows affected (0.01 sec)
Query OK, 0 rows affected, 1 warning (0.00 sec)
Query OK, 0 rows affected (0.01 sec)
Query OK, 1 row affected (0.01 sec)
AI 代码解读
对应的/var/lib/mysql下同样出现对应的数据库内容文件
[root@iZ0jl69kyvg0h181cozuf5Z mysql]# pwd
/var/lib/mysql
[root@iZ0jl69kyvg0h181cozuf5Z mysql]# ll
drwxr-x--- 2 mysql mysql 4096 Mar 21 09:30 scott
AI 代码解读
7.1 显示每个部门的平均工资和最高工资
7.2 显示每个部门的每种岗位的平均工资和最低工资
mysql> select deptno,job, min(sal) 最低,avg(sal) 平均 from emp group by deptno,job;
+--------+-----------+---------+-------------+
| deptno | job | 最低 | 平均 |
+--------+-----------+---------+-------------+
| 10 | CLERK | 1300.00 | 1300.000000 |
| 10 | MANAGER | 2450.00 | 2450.000000 |
| 10 | PRESIDENT | 5000.00 | 5000.000000 |
| 20 | ANALYST | 3000.00 | 3000.000000 |
| 20 | CLERK | 800.00 | 950.000000 |
| 20 | MANAGER | 2975.00 | 2975.000000 |
| 30 | CLERK | 950.00 | 950.000000 |
| 30 | MANAGER | 2850.00 | 2850.000000 |
| 30 | SALESMAN | 1250.00 | 1400.000000 |
+--------+-----------+---------+-------------+
9 rows in set (0.00 sec)
AI 代码解读
7.3 显示平均工资低于2000的部门和它的平均工资
统计各个部门的平均工资
select avg(sal) from EMP group by deptno
AI 代码解读
having和group by配合使用,对group by结果进行过滤
select deptno,avg(sal) 平均 from EMP group by deptno having myavg<2000;
+--------+-------------+
| deptno | 平均 |
+--------+-------------+
| 30 | 1566.666667 |
+--------+-------------+
1 row in set (0.00 sec)
AI 代码解读
--having经常和group by搭配使用,作用是对分组进行筛选,作用有些像where
7.4 SMITH员工不参与计算,显示平均工资低于2000的岗位和它的平均工资
mysql> select deptno,job,avg(sal) 平均 from emp where ename !='SMITH' group by deptno,job having avg(sal) < 2000;+--------+----------+-------------+
| deptno | job | 平均 |
+--------+----------+-------------+
| 10 | CLERK | 1300.000000 |
| 20 | CLERK | 1100.000000 |
| 30 | CLERK | 950.000000 |
| 30 | SALESMAN | 1400.000000 |
+--------+----------+-------------+
4 rows in set (0.00 sec)
AI 代码解读
切屏小技巧:
练习题
在进行练习之前,请务必熟悉两篇博客当中的内容并且动手实践!!!