SQL classification and common syntax && data types (super detailed version)

1. SQL classification

SQL is the abbreviation of Structured Query Language. It is a standardized language for managing and operating relational database systems. SQL classification is as follows:

• DDL: Data Definition Language, used to define database objects (databases, tables, fields)
• DML: Data manipulation language, used to add, delete, and modify data in database tables
• DQL: Data query language, used to query records in tables in the database
• DCL: Data control language, used to create database users and control database control permissions

2. DDL-data definition language

2.1 DDL-database operations

Query all databases:
  SHOW DATABASES;
Query current database:
  SELECT DATABASE();
Create database:
  CREATE DATABASE [ IF NOT EXISTS ] 数据库名 [ DEFAULT CHARSET 字符集] [COLLATE 排序规则 ];
Delete database:
  DROP DATABASE [ IF EXISTS ] 数据库名;
Use database:
  USE 数据库名;

Precautions

• The UTF8 character set is 3 bytes long, and some symbols occupy 4 bytes, so it is recommended to use the utf8mb4 character set.

 

2.2 DDL-table operations 

 Query all tables in the current database:
  SHOW TABLES;
Query table structure:
  DESC 表名;
Query the table creation statement of the specified table:
  SHOW CREATE TABLE 表名;

 Create table:

        CREATE TABLE table name (
            field 1 data type constraint,
            field 2 data type constraint,
            field 3 data type constraint,
            ...
        );

Modify table name:
    ALTER TABLE 表名 RENAME TO 新表名

Drop table:
    DROP TABLE [IF EXISTS] 表名;
Drop the table and recreate it:
    TRUNCATE TABLE 表名;

 

2.3 DDL-field operations 

Add fields:
    ALTER TABLE 表名 ADD 字段名 类型(长度) [COMMENT 注释] [约束];
Example:ALTER TABLE emp ADD nickname varchar(20) COMMENT '昵称';

Modify field data type:
    ALTER TABLE 表名 MODIFY 字段名 新数据类型(长度);
Modify field name and field type:
    ALTER TABLE 表名 CHANGE 旧字段名 新字段名 类型(长度) [COMMENT 注释] [约束];
Example: Modify the nickname field of the emp table to username, and the type is varchar(30)
    ALTER TABLE emp CHANGE nickname username varchar(30) COMMENT '昵称';

Delete fields:
    ALTER TABLE 表名 DROP 字段名;

 3. Supplement: Data types

3.1 Integer type

type name	Ranges	size
TINYINT	-128〜127	1 byte
SMALLINT	-32768〜32767	2 bytes
MEDIUMINT	-8388608〜8388607	3 bytes
INT	-2147483648〜2147483647	4 bytes
BIGINT	-9223372036854775808〜9223372036854775807	8 bytes

Unsigned adds the unsigned keyword after the data type.

3.2 Floating point type

type name	illustrate	storage requirements
FLOAT	Single precision floating point number	4 bytes
DOUBLE	Double precision floating point number	8 bytes
DECIMAL (M, D)，DEC	Compressed "strict" fixed-point numbers	M+2 bytes

3.3 Date and time

type name	date format	date range	storage requirements
YEAR	YYYY	1901 ~ 2155	1 byte
TIME	HH:MM:SS	-838:59:59 ~ 838:59:59	3 bytes
DATE	YYYY-MM-DD	1000-01-01 ~ 9999-12-3	3 bytes
DATETIME	YYYY-MM-DD HH:MM:SS	1000-01-01 00:00:00 ~ 9999-12-31 23:59:59	8 bytes
TIMESTAMP	YYYY-MM-DD HH:MM:SS	1980-01-01 00:00:01 UTC ~ 2040-01-19 03:14:07 UTC	4 bytes

3.4 String

type name	illustrate	storage requirements
CHAR(M)	Fixed length non-binary string (good performance)	M bytes, 1<=M<=255
VARCHAR(M)	Variable-length non-binary strings (poor performance)	L+1 bytes, here, L<=M and 1<=M<=255
TINYTEXT	very small non-binary string	L+1 bytes, here, L<2^8
TEXT	small non-binary string	L+2 bytes, here, L<2^16
MEDIUMTEXT	Medium size non-binary string	L+3 bytes, here, L<2^24
LONGTEXT	Large non-binary string	L+4 bytes, here, L<2^32
ENUM	Enumeration type, can only have one enumeration string value	1 or 2 bytes, depending on the number of enumeration values ​​(maximum value is 65535)
SET	A setting, string object can have zero or more SET members	1, 2, 3, 4, or 8 bytes, depending on the number of set members (maximum 64 members)

3.5 Binary types

type name	illustrate	storage requirements
BIT(M)	Bit field type	About (M+7)/8 bytes
BINARY(M)	Fixed length binary string	M bytes
VARBINARY (M)	variable length binary string	M+1 bytes
TINYBLOB (M)	Very small BLOB	L+1 bytes, here, L<2^8
BLOB (M)	small BLOB	L+2 bytes, here, L<2^16
MEDIUMBLOB (M)	medium sized BLOB	L+3 bytes, here, L<2^24
LONGBLOB (M)	Very large BLOB	L+4 bytes, here, L<2^32

4. DML - data manipulation language

4.1 Add data

Specified fields:
  INSERT INTO 表名 (字段名1, 字段名2, ...) VALUES (值1, 值2, ...);
All fields:
  INSERT INTO 表名 VALUES (值1, 值2, ...);

Add data in batches:
  INSERT INTO 表名 (字段名1, 字段名2, ...) VALUES (值1, 值2, ...), (值1, 值2, ...), (值1, 值2, ...);
  INSERT INTO 表名 VALUES (值1, 值2, ...), (值1, 值2, ...), (值1, 值2, ...);

Precautions

• String and date type data should be enclosed in quotes
• The size of the inserted data should be within the specified range of the field

4.2 Updating and deleting data

 

Modify data:
  UPDATE 表名 SET 字段名1 = 值1, 字段名2 = 值2, ... [ WHERE 条件 ];
Example:
  UPDATE emp SET name = 'Jack' WHERE id = 1;

delete data:
  DELETE FROM 表名 [ WHERE 条件 ];

5. DQL - Data Query Language 

 

5.1 Basic query 

Query multiple fields:
  SELECT 字段1, 字段2, 字段3, ... FROM 表名;
  SELECT * FROM 表名;

Set alias:
  SELECT 字段1 [ AS 别名1 ], 字段2 [ AS 别名2 ], 字段3 [ AS 别名3 ], ... FROM 表名;
  SELECT 字段1 [ 别名1 ], 字段2 [ 别名2 ], 字段3 [ 别名3 ], ... FROM 表名;

Remove duplicate records:
  SELECT DISTINCT 字段列表 FROM 表名;

5.2 Conditional query 

Condition query:
  SELECT 字段列表 FROM 表名 WHERE 条件列表;

example: 

1. -- 年龄等于30
2. select * from employee where age = 30;
3. -- 年龄小于30
4. select * from employee where age < 30;
5. -- 小于等于
6. select * from employee where age <= 30;
7. -- 没有身份证
8. select * from employee where idcard is null or idcard = '';
9. -- 有身份证
10. select * from employee where idcard is not null;
11. -- 不等于
12. select * from employee where age != 30;
13. -- 年龄在20到30之间
14. select * from employee where age between 20 and 30;
15. select * from employee where age >= 20 and age <= 30;
16. -- 下面语句不报错，但查不到任何信息
17. select * from employee where age between 30 and 20;
18. -- 性别为女且年龄小于30
19. select * from employee where age < 30 and gender = '女';
20. -- 年龄等于25或30或35
21. select * from employee where age = 25 or age = 30 or age = 35;
22. select * from employee where age in (25, 30, 35);
23. -- 姓名为两个字
24. select * from employee where name like '__'; (此处为两个 _ )
25. -- 身份证最后为X
26. select * from employee where idcard like '%X';

5.3 Aggregation functions

 Grammar:
  SELECT 聚合函数(字段列表) FROM 表名;
Example:
  SELECT count(id) from employee where workaddress = "广东省";

5.4 Group query 

grammar:
  SELECT 字段列表 FROM 表名 [ WHERE 条件 ] GROUP BY 分组字段名 [ HAVING 分组后的过滤条件 ]; 

The difference between where and having:

• The execution timing is different: where is filtering before grouping, and if the where condition is not met, the grouping will not be performed; having is filtering the results after grouping.
• The judgment conditions are different: where cannot judge the aggregate function, but having can.

example: 

1. -- 根据性别分组，统计男性和女性数量（只显示分组数量，不显示哪个是男哪个是女）
2. select count(*) from employee group by gender;
3. -- 根据性别分组，统计男性和女性数量
4. select gender, count(*) from employee group by gender;
5. -- 根据性别分组，统计男性和女性的平均年龄
6. select gender, avg(age) from employee group by gender;
7. -- 年龄小于45，并根据工作地址分组
8. select workaddress, count(*) from employee where age < 45 group by workaddress;
9. -- 年龄小于45，并根据工作地址分组，获取员工数量大于等于3的工作地址
10. select workaddress, count(*) address_count from employee where age < 45 group by workaddress having address_count >= 3;

Precautions

• Execution order: where > aggregate function > having
• After grouping, the fields queried are generally aggregate functions and grouping fields. It is meaningless to query other fields.

5.5 Sorting query

grammar:
  SELECT 字段列表 FROM 表名 ORDER BY 字段1 排序方式1, 字段2 排序方式2;

sort by:

• ASC: Ascending (default)
• DESC: descending order

example:

1. -- 根据年龄升序排序
2. SELECT * FROM employee ORDER BY age ASC;
3. SELECT * FROM employee ORDER BY age;
4. -- 两字段排序，根据年龄升序排序，入职时间降序排序
5. SELECT * FROM employee ORDER BY age ASC, entrydate DESC;

Precautions:

If it is a multi-field sort, only when the first field has the same value, the second field will be sorted.

5.6  分页查询

语法：
  SELECT 字段列表 FROM 表名 LIMIT 起始索引, 查询记录数;

例子：

1. -- 查询第一页数据，展示10条
2. SELECT * FROM employee LIMIT 0, 10;
3. -- 查询第二页
4. SELECT * FROM employee LIMIT 10, 10;

注意事项

• 起始索引从0开始，起始索引 = （查询页码 - 1） * 每页显示记录数
• 分页查询是数据库的方言，不同数据库有不同实现，MySQL是LIMIT
• 如果查询的是第一页数据，起始索引可以省略，直接简写 LIMIT 10

 六、DQL-执行顺序

DQL执行顺序

FROM -> WHERE -> GROUP BY -> SELECT -> ORDER BY -> LIMIT

七、DCL-数据控制语言 （开发人员操作较少）

7.1  管理用户

查询用户：

1. USE mysql;
2. SELECT * FROM user;

创建用户:
  CREATE USER '用户名'@'主机名' IDENTIFIED BY '密码';

修改用户密码：
  ALTER USER '用户名'@'主机名' IDENTIFIED WITH mysql_native_password BY '新密码';

删除用户：
  DROP USER '用户名'@'主机名';

 例子：

1. -- 创建用户test，只能在当前主机localhost访问
2. create user 'test'@'localhost' identified by '123456';
3. -- 创建用户test，能在任意主机访问
4. create user 'test'@'%' identified by '123456';
5. create user 'test' identified by '123456';
6. -- 修改密码
7. alter user 'test'@'localhost' identified with mysql_native_password by '1234';
8. -- 删除用户
9. drop user 'test'@'localhost';

注意事项

• 主机名可以使用 % 通配

7.2  权限控制

常用权限：

权限	说明
ALL, ALL PRIVILEGES	所有权限
SELECT	查询数据
INSERT	插入数据
UPDATE	修改数据
DELETE	删除数据
ALTER	修改表
DROP	删除数据库/表/视图
CREATE	创建数据库/表

查询权限：
  SHOW GRANTS FOR '用户名'@'主机名';

授予权限：
  GRANT 权限列表 ON 数据库名.表名 TO '用户名'@'主机名';

撤销权限：
  REVOKE 权限列表 ON 数据库名.表名 FROM '用户名'@'主机名';

注意事项

• 多个权限用逗号分隔
• 授权时，数据库名和表名可以用 * 进行通配，代表所有