【一】筛选过滤条件

【1】查询语句

-- 查询当前表中的指定字段的数据

select id,name from emp where id > 3;

【2】创建数据表

create database emp_data;

use emp_data;

create table emp(

	id int not null unique auto_increment,

    name varchar(20) not null,

    sex enum("male","female") not null default "male",

    age int(3) unsigned not null default 28,

    hire_data date not null,

    post varchar(50),

    post_comment varchar(100),

    salary double(15,2),

    office int,

    depart_id int

);

insert into emp(name, sex, age, hire_data, post, salary, office, depart_id) values

("dream", "male", 78, '20220306', "陌夜痴梦久生情", 730.33, 401, 1), # 以下是教学部

("mengmeng", "female", 25, '20220102', "teacher", 12000.50, 401, 1),

("xiaomeng", "male", 35, '20190607', "teacher", 15000.99, 401, 1),

("xiaona", "female", 29, '20180906', "teacher", 11000.80, 401, 1),

("xiaoqi", "female", 27, '20220806', "teacher", 13000.70, 401, 1),

("suimeng", "male", 33, '20230306', "teacher", 14000.62, 401, 1), # 以下是销售部

("娜娜", "female", 69, '20100307', "sale", 300.13, 402, 2),

("芳芳", "male", 45, '20140518', "sale", 400.45, 402, 2),

("小明", "male", 34, '20160103', "sale", 350.80, 402, 2),

("亚洲", "female", 42, '20170227', "sale", 320.99, 402, 2),

("华华", "female", 55, '20180319', "sale", 380.75, 402, 2),

("田七", "male", 44, '20230808', "sale", 420.33, 402, 2), # 以下是运行部

("大古", "female", 66, '20180509', "operation", 630.33, 403, 3),

("张三", "male", 51, '20191001', "operation", 410.25, 403, 3),

("李四", "male", 47, '20200512', "operation", 330.62, 403, 3),

("王五", "female", 39, '20210203', "operation", 370.98, 403, 3),

("赵六", "female", 36, '20220724', "operation", 390.15, 403, 3);

select * from emp;

select * from emp\G;

【3】筛选条件之where

  • 查询3<=id<=6的数据
mysql> select id,name,age from emp where id >=3 and id <=6;

+----+----------+-----+

| id | name     | age |

+----+----------+-----+

|  3 | xiaomeng |  35 |

|  4 | xiaona   |  29 |

|  5 | xiaoqi   |  27 |

|  6 | suimeng  |  33 |

+----+----------+-----+

4 rows in set (0.00 sec)

mysql> select id,name,age from emp where id between 3 and 6;

+----+----------+-----+

| id | name     | age |

+----+----------+-----+

|  3 | xiaomeng |  35 |

|  4 | xiaona   |  29 |

|  5 | xiaoqi   |  27 |

|  6 | suimeng  |  33 |

+----+----------+-----+

4 rows in set (0.00 sec)
  • 查询 薪资是 12000.50 或者 13000.70 或者730.33 的数据
mysql> select * from emp where salary in (12000.50,13000.70,730.33);

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

3 rows in set (0.00 sec)
  • 查询 员工姓名中包含字母o的姓名和薪资
mysql> select * from emp where name like "%o%";

+----+----------+--------+-----+------------+---------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post    | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+---------+--------------+----------+--------+-----------+

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher | NULL         | 15000.99 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher | NULL         | 11000.80 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher | NULL         | 13000.70 |    401 |         1 |

+----+----------+--------+-----+------------+---------+--------------+----------+--------+-----------+

3 rows in set (0.00 sec)
  • 查询员工姓名是由六个字符组成的姓名和薪资
mysql> select name,salary from emp where name like "______";

+--------+----------+

| name   | salary   |

+--------+----------+

| xiaona | 11000.80 |

| xiaoqi | 13000.70 |

+--------+----------+

2 rows in set (0.00 sec)

mysql> select name,salary from emp where char_length(name) = 6;

+--------+----------+

| name   | salary   |

+--------+----------+

| xiaona | 11000.80 |

| xiaoqi | 13000.70 |

+--------+----------+

2 rows in set (0.00 sec)
  • 查询岗位描述为空的员工姓名和岗位名
mysql> select * from emp where post_comment is null;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

|  8 | 芳芳     | male   |  45 | 2014-05-18 | sale                  | NULL         |   400.45 |    402 |         2 |

|  9 | 小明     | male   |  34 | 2016-01-03 | sale                  | NULL         |   350.80 |    402 |         2 |

| 10 | 亚洲     | female |  42 | 2017-02-27 | sale                  | NULL         |   320.99 |    402 |         2 |

| 11 | 华华     | female |  55 | 2018-03-19 | sale                  | NULL         |   380.75 |    402 |         2 |

| 12 | 田七     | male   |  44 | 2023-08-08 | sale                  | NULL         |   420.33 |    402 |         2 |

| 13 | 大古     | female |  66 | 2018-05-09 | operation             | NULL         |   630.33 |    403 |         3 |

| 14 | 张三     | male   |  51 | 2019-10-01 | operation             | NULL         |   410.25 |    403 |         3 |

| 15 | 李四     | male   |  47 | 2020-05-12 | operation             | NULL         |   330.62 |    403 |         3 |

| 16 | 王五     | female |  39 | 2021-02-03 | operation             | NULL         |   370.98 |    403 |         3 |

| 17 | 赵六     | female |  36 | 2022-07-24 | operation             | NULL         |   390.15 |    403 |         3 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

17 rows in set (0.00 sec)

【二】筛选条件之group by(分组)

mysql> select * from emp group by post;

ERROR 1055 (42000): Expression #1 of SELECT list is not in GROUP BY clause and contains nonaggregated column 'emp_data.emp.id' which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by

  • 模糊查询所有严格模式

  • 关闭这个严格模式

  • 删除了 ONLY_FULL_GROUP_BY

  • 拿到每一个部门的第一行数据

    最小的操作单位应该是组，而不是组内的单个数据

    这条命令在没有设置严格模式的时候是可以执行的，返回的数据是每组的第一条数据

    但是分组不应该以单条数据为参考，而是要以组为操作单位

    如果设置了严格模式，上述命令会直接报错

    也就是上面的那个错误

mysql> show variables like "%mode";

+--------------------------+-------------------------------------------------------------------------------------------------------------------------------------------+

| Variable_name            | Value

                                               |

+--------------------------+-------------------------------------------------------------------------------------------------------------------------------------------+

| block_encryption_mode    | aes-128-ecb

                                               |

| gtid_mode                | OFF

                                               |

| innodb_autoinc_lock_mode | 1

                                               |

| innodb_strict_mode       | ON

                                               |

| offline_mode             | OFF

                                               |

| pseudo_slave_mode        | OFF

                                               |

| rbr_exec_mode            | STRICT

                                               |

| slave_exec_mode          | STRICT

                                               |

| sql_mode                 | ONLY_FULL_GROUP_BY,STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION |

+--------------------------+-------------------------------------------------------------------------------------------------------------------------------------------+

9 rows in set, 1 warning (0.00 sec)


sql_mode='ONLY_FULL_GROUP_BY,STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION';

set session sql_mode='STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION';


mysql> select * from emp group by post;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| 13 | 大古     | female |  66 | 2018-05-09 | operation             | NULL         |   630.33 |    403 |         3 |

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

4 rows in set (0.00 sec)

【1】获取每个部门的最高薪资(max)

  • 聚合函数：max - 取最大值
  • 可以利用as关键字给字段起别名，或者默认不写
  • 但是不推荐，如果忽略语义不明确，容易错乱
select post,max(salary) from emp group by post;

-- as别名

select post,min(salary) as "最低薪资" from emp group by post;

【2】获取每个部门的最低薪资(min)

  • 聚合函数：min- 取最大值
mysql> select post,min(salary) from emp group by post;

+-----------------------+-------------+

| post                  | min(salary) |

+-----------------------+-------------+

| operation             |      330.62 |

| sale                  |      300.13 |

| teacher               |    11000.80 |

| 陌夜痴梦久生情        |      730.33 |

+-----------------------+-------------+

4 rows in set (0.00 sec)

mysql>

mysql> select post,min(salary) as "最低薪资" from emp group by post;

+-----------------------+--------------+

| post                  | 最低薪资     |

+-----------------------+--------------+

| operation             |       330.62 |

| sale                  |       300.13 |

| teacher               |     11000.80 |

| 陌夜痴梦久生情        |       730.33 |

+-----------------------+--------------+

4 rows in set (0.00 sec)

【3】获取每个部门的平均薪资(avg)

  • 聚合函数：avg- 取最大值
mysql> select post,avg(salary) from emp group by post;

+-----------------------+--------------+

| post                  | avg(salary)  |

+-----------------------+--------------+

| operation             |   426.466000 |

| sale                  |   362.241667 |

| teacher               | 13000.722000 |

| 陌夜痴梦久生情        |   730.330000 |

+-----------------------+--------------+

4 rows in set (0.00 sec)

mysql> select post,avg(salary) as "平均薪资" from emp group by post;

+-----------------------+--------------+

| post                  | 平均薪资     |

+-----------------------+--------------+

| operation             |   426.466000 |

| sale                  |   362.241667 |

| teacher               | 13000.722000 |

| 陌夜痴梦久生情        |   730.330000 |

+-----------------------+--------------+

4 rows in set (0.00 sec)

【4】获取每个部门的薪资总和(sum)

  • 聚合函数：sum- 取最大值
mysql> select post,sum(salary) from emp group by post;

+-----------------------+-------------+

| post                  | sum(salary) |

+-----------------------+-------------+

| operation             |     2132.33 |

| sale                  |     2173.45 |

| teacher               |    65003.61 |

| 陌夜痴梦久生情        |      730.33 |

+-----------------------+-------------+

4 rows in set (0.00 sec)

mysql>

mysql> select post,sum(salary) as "薪资综合" from emp group by post;

+-----------------------+--------------+

| post                  | 薪资综合     |

+-----------------------+--------------+

| operation             |      2132.33 |

| sale                  |      2173.45 |

| teacher               |     65003.61 |

| 陌夜痴梦久生情        |       730.33 |

+-----------------------+--------------+

4 rows in set (0.00 sec)

【5】获取每个部门的人数(count)

  • 聚合函数：count- 取最大值
mysql> select post,count(salary) from emp group by post;

+-----------------------+---------------+

| post                  | count(salary) |

+-----------------------+---------------+

| operation             |             5 |

| sale                  |             6 |

| teacher               |             5 |

| 陌夜痴梦久生情        |             1 |

+-----------------------+---------------+

4 rows in set (0.00 sec)

mysql>

mysql> select post,count(id) as "部门总人数" from emp group by post;

+-----------------------+-----------------+

| post                  | 部门总人数      |

+-----------------------+-----------------+

| operation             |               5 |

| sale                  |               6 |

| teacher               |               5 |

| 陌夜痴梦久生情        |               1 |

+-----------------------+-----------------+

4 rows in set (0.00 sec)

【6】查询分组之后的部门名称和每个部门下所有的员工姓名(group_concat)

  • 聚合函数：group_concat- 获得分组之后的具体的值
  • 不单单支持获取分组之后的其他字段值，还支持拼接操作
mysql> select post,group_concat(name) from emp group by post;

+-----------------------+-------------------------------------------+

| post                  | group_concat(name)                        |

+-----------------------+-------------------------------------------+

| operation             | 大古,张三,李四,王五,赵六                  |

| sale                  | 娜娜,芳芳,小明,亚洲,华华,田七             |

| teacher               | mengmeng,xiaomeng,xiaona,xiaoqi,suimeng   |

| 陌夜痴梦久生情        | dream                                     |

+-----------------------+-------------------------------------------+

4 rows in set (0.00 sec)

mysql>

mysql> select post,name from emp group by post;

+-----------------------+----------+

| post                  | name     |

+-----------------------+----------+

| operation             | 大古     |

| sale                  | 娜娜     |

| teacher               | mengmeng |

| 陌夜痴梦久生情        | dream    |

+-----------------------+----------+

4 rows in set (0.00 sec)
  • 拼接数据
mysql> select post,group_concat(name,'_drm') from emp group by post;

+-----------------------+-------------------------------------------------------------------+

| post                  | group_concat(name,'_drm')                                         |

+-----------------------+-------------------------------------------------------------------+

| operation             | 大古_drm,张三_drm,李四_drm,王五_drm,赵六_drm                      |

| sale                  | 娜娜_drm,芳芳_drm,小明_drm,亚洲_drm,华华_drm,田七_drm             |

| teacher               | mengmeng_drm,xiaomeng_drm,xiaona_drm,xiaoqi_drm,suimeng_drm       |

| 陌夜痴梦久生情        | dream_drm                                                         |

+-----------------------+-------------------------------------------------------------------+

4 rows in set (0.00 sec)

【7】分组注意事项

  • where和group by可以同时使用，但是要注意顺序
-- 同时出现要有先后顺序

-- where 先对整体过滤 group by 再对局部过滤

select * from * where * group by *;

【8】统计各部门年龄在 30 岁以上的员工的平均薪资

mysql> select name,age,post,salary from emp where age>30;

+----------+-----+-----------------------+----------+

| name     | age | post                  | salary   |

+----------+-----+-----------------------+----------+

| dream    |  78 | 陌夜痴梦久生情        |   730.33 |

| xiaomeng |  35 | teacher               | 15000.99 |

| suimeng  |  33 | teacher               | 14000.62 |

| 娜娜     |  69 | sale                  |   300.13 |

| 芳芳     |  45 | sale                  |   400.45 |

| 小明     |  34 | sale                  |   350.80 |

| 亚洲     |  42 | sale                  |   320.99 |

| 华华     |  55 | sale                  |   380.75 |

| 田七     |  44 | sale                  |   420.33 |

| 大古     |  66 | operation             |   630.33 |

| 张三     |  51 | operation             |   410.25 |

| 李四     |  47 | operation             |   330.62 |

| 王五     |  39 | operation             |   370.98 |

| 赵六     |  36 | operation             |   390.15 |

+----------+-----+-----------------------+----------+

14 rows in set (0.00 sec)

mysql> select group_concat(name,":",age),post,salary from emp where age>30 group by post;

+-------------------------------------------------------------+-----------------------+----------+

| group_concat(name,":",age)                                  | post                  | salary   |

+-------------------------------------------------------------+-----------------------+----------+

| 大古:66,张三:51,李四:47,王五:39,赵六:36                     | operation             |   630.33 |

| 娜娜:69,芳芳:45,小明:34,亚洲:42,华华:55,田七:44             | sale                  |   300.13 |

| xiaomeng:35,suimeng:33                                      | teacher               | 15000.99 |

| dream:78                                                    | 陌夜痴梦久生情        |   730.33 |

+-------------------------------------------------------------+-----------------------+----------+

4 rows in set (0.00 sec)

mysql> select post,avg(salary) from emp where age>30 group by post;

+-----------------------+--------------+

| post                  | avg(salary)  |

+-----------------------+--------------+

| operation             |   426.466000 |

| sale                  |   362.241667 |

| teacher               | 14500.805000 |

| 陌夜痴梦久生情        |   730.330000 |

+-----------------------+--------------+

4 rows in set (0.00 sec)

【三】筛选条件之having(分组之后筛选)

  • having的语法和where是一致的
  • 只不过having是在分组之后进行的过滤操作
  • 即having是可以直接使用聚合函数的

【1】统计各部门年龄 30 岁以上的员工的工资，并且保留平均薪资大于1w的部门

  • 查询数据
mysql> select post,avg(salary) from emp

    ->  where age > 30

    ->  group by post

    ->  having avg(salary) > 10000;

+---------+--------------+

| post    | avg(salary)  |

+---------+--------------+

| teacher | 14500.805000 |

+---------+--------------+

1 row in set (0.00 sec)

【四】筛选条件之distinct(去重)

  • 必须是完全一样的数据才可以去重
  • 一定要注意主键的问题
  • 在主键存在的情况下是一定不可能去重的

【1】对emp表中的age和id去重

select distinct id,age from emp;

mysql> select distinct id,age from emp;

+----+-----+

| id | age |

+----+-----+

|  1 |  78 |

|  2 |  25 |

|  3 |  35 |

|  4 |  29 |

|  5 |  27 |

|  6 |  33 |

|  7 |  69 |

|  8 |  45 |

|  9 |  34 |

| 10 |  42 |

| 11 |  55 |

| 12 |  44 |

| 13 |  66 |

| 14 |  51 |

| 15 |  47 |

| 16 |  39 |

| 17 |  36 |

+----+-----+

17 rows in set (0.00 sec)

【2】只对emp表中的age去重

mysql> select distinct age from emp;

+-----+

| age |

+-----+

|  78 |

|  25 |

|  35 |

|  29 |

|  27 |

|  33 |

|  69 |

|  45 |

|  34 |

|  42 |

|  55 |

|  44 |

|  66 |

|  51 |

|  47 |

|  39 |

|  36 |

+-----+

17 rows in set (0.00 sec)

【五】筛选条件之order by(排序)

  • order by : 默认是升序
  • asc 默认可以省略不写 ---> 修改降序
  • desc : 降序

【1】将emp表中的数据按照薪资排序(升序)

mysql> select * from emp order by salary;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

| 10 | 亚洲     | female |  42 | 2017-02-27 | sale                  | NULL         |   320.99 |    402 |         2 |

| 15 | 李四     | male   |  47 | 2020-05-12 | operation             | NULL         |   330.62 |    403 |         3 |

|  9 | 小明     | male   |  34 | 2016-01-03 | sale                  | NULL         |   350.80 |    402 |         2 |

| 16 | 王五     | female |  39 | 2021-02-03 | operation             | NULL         |   370.98 |    403 |         3 |

| 11 | 华华     | female |  55 | 2018-03-19 | sale                  | NULL         |   380.75 |    402 |         2 |

| 17 | 赵六     | female |  36 | 2022-07-24 | operation             | NULL         |   390.15 |    403 |         3 |

|  8 | 芳芳     | male   |  45 | 2014-05-18 | sale                  | NULL         |   400.45 |    402 |         2 |

| 14 | 张三     | male   |  51 | 2019-10-01 | operation             | NULL         |   410.25 |    403 |         3 |

| 12 | 田七     | male   |  44 | 2023-08-08 | sale                  | NULL         |   420.33 |    402 |         2 |

| 13 | 大古     | female |  66 | 2018-05-09 | operation             | NULL         |   630.33 |    403 |         3 |

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

17 rows in set (0.00 sec)

【2】将emp表中的数据按照薪资排序(降序)

mysql> select * from emp order by salary desc;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

| 13 | 大古     | female |  66 | 2018-05-09 | operation             | NULL         |   630.33 |    403 |         3 |

| 12 | 田七     | male   |  44 | 2023-08-08 | sale                  | NULL         |   420.33 |    402 |         2 |

| 14 | 张三     | male   |  51 | 2019-10-01 | operation             | NULL         |   410.25 |    403 |         3 |

|  8 | 芳芳     | male   |  45 | 2014-05-18 | sale                  | NULL         |   400.45 |    402 |         2 |

| 17 | 赵六     | female |  36 | 2022-07-24 | operation             | NULL         |   390.15 |    403 |         3 |

| 11 | 华华     | female |  55 | 2018-03-19 | sale                  | NULL         |   380.75 |    402 |         2 |

| 16 | 王五     | female |  39 | 2021-02-03 | operation             | NULL         |   370.98 |    403 |         3 |

|  9 | 小明     | male   |  34 | 2016-01-03 | sale                  | NULL         |   350.80 |    402 |         2 |

| 15 | 李四     | male   |  47 | 2020-05-12 | operation             | NULL         |   330.62 |    403 |         3 |

| 10 | 亚洲     | female |  42 | 2017-02-27 | sale                  | NULL         |   320.99 |    402 |         2 |

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

17 rows in set (0.00 sec)

【3】将emp表中的数据按照薪资(升序)和年龄(降序)排序

  • order by 后面可以跟多个参数
  • 先按照age降序排
  • 如果碰到 age 相同 ，再按照salary 升序排
mysql> select * from emp order by age desc,salary asc;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

| 13 | 大古     | female |  66 | 2018-05-09 | operation             | NULL         |   630.33 |    403 |         3 |

| 11 | 华华     | female |  55 | 2018-03-19 | sale                  | NULL         |   380.75 |    402 |         2 |

| 14 | 张三     | male   |  51 | 2019-10-01 | operation             | NULL         |   410.25 |    403 |         3 |

| 15 | 李四     | male   |  47 | 2020-05-12 | operation             | NULL         |   330.62 |    403 |         3 |

|  8 | 芳芳     | male   |  45 | 2014-05-18 | sale                  | NULL         |   400.45 |    402 |         2 |

| 12 | 田七     | male   |  44 | 2023-08-08 | sale                  | NULL         |   420.33 |    402 |         2 |

| 10 | 亚洲     | female |  42 | 2017-02-27 | sale                  | NULL         |   320.99 |    402 |         2 |

| 16 | 王五     | female |  39 | 2021-02-03 | operation             | NULL         |   370.98 |    403 |         3 |

| 17 | 赵六     | female |  36 | 2022-07-24 | operation             | NULL         |   390.15 |    403 |         3 |

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

|  9 | 小明     | male   |  34 | 2016-01-03 | sale                  | NULL         |   350.80 |    402 |         2 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

17 rows in set (0.00 sec)

【4】混合排序

  • 统计各部门年龄在 30 岁以上的员工的工资，并且保留平均薪资大于1000的部门，对平均工资进行排序
mysql> select avg(salary) from emp

    ->  where age > 30

    ->  group by post

    ->  having avg(salary) > 400

    ->  order by avg(salary) desc

    ->  ;

+--------------+

| avg(salary)  |

+--------------+

| 14500.805000 |

|   730.330000 |

|   426.466000 |

+--------------+

3 rows in set (0.00 sec)

【六】筛选条件之limit（限制展示条数）

  • 针对数据太多的情况，我们大都是做分页处理
  • limit x,y : 第一个参数是起始位置，第二个是条数

【1】查询数据方式一：单数字限制

select * from emp limit 10;

mysql> select * from emp limit 10;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

|  7 | 娜娜     | female |  69 | 2010-03-07 | sale                  | NULL         |   300.13 |    402 |         2 |

|  8 | 芳芳     | male   |  45 | 2014-05-18 | sale                  | NULL         |   400.45 |    402 |         2 |

|  9 | 小明     | male   |  34 | 2016-01-03 | sale                  | NULL         |   350.80 |    402 |         2 |

| 10 | 亚洲     | female |  42 | 2017-02-27 | sale                  | NULL         |   320.99 |    402 |         2 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

10 rows in set (0.00 sec)

【2】查询数据：多限制

select * from emp limit 0,6;

mysql> select * from emp limit 0,6;

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

| id | name     | sex    | age | hire_data  | post                  | post_comment | salary   | office | depart_id |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

|  1 | dream    | male   |  78 | 2022-03-06 | 陌夜痴梦久生情        | NULL         |   730.33 |    401 |         1 |

|  2 | mengmeng | female |  25 | 2022-01-02 | teacher               | NULL         | 12000.50 |    401 |         1 |

|  3 | xiaomeng | male   |  35 | 2019-06-07 | teacher               | NULL         | 15000.99 |    401 |         1 |

|  4 | xiaona   | female |  29 | 2018-09-06 | teacher               | NULL         | 11000.80 |    401 |         1 |

|  5 | xiaoqi   | female |  27 | 2022-08-06 | teacher               | NULL         | 13000.70 |    401 |         1 |

|  6 | suimeng  | male   |  33 | 2023-03-06 | teacher               | NULL         | 14000.62 |    401 |         1 |

+----+----------+--------+-----+------------+-----------------------+--------------+----------+--------+-----------+

6 rows in set (0.00 sec)

从 0 后面 取六条

第一个参数是起始位置，第二个是条数

【七】筛选条件之正则

【1】语法

属性名 REGEXP '匹配方式'
  • 其中，“属性名”表示需要查询的字段名称；
  • “匹配方式”表示以哪种方式来匹配查询。

【2】匹配方式

  • “匹配方式”中有很多的模式匹配字符，它们分别表示不同的意思。
  • 下表列出了 REGEXP 操作符中常用的匹配方式。
选项 说明 例子 匹配值示例
^ 匹配文本的开始字符 ‘^b’ 匹配以字母 b 开头的字符串 book、big、banana、bike
$ 匹配文本的结束字符 ‘st$’ 匹配以 st 结尾的字符串 test、resist、persist
. 匹配任何单个字符 ‘b.t’ 匹配任何 b 和 t 之间有一个字符 bit、bat、but、bite
* 匹配前面的字符 0 次或多次 ‘f*n’ 匹配字符 n 前面有任意个字符 f fn、fan、faan、abcn
+ 匹配前面的字符 1 次或多次 ‘ba+’ 匹配以 b 开头，后面至少紧跟一个 a ba、bay、bare、battle
? 匹配前面的字符 0 次或1次 ‘sa?’ 匹配0个或1个a字符 sa、s
字符串 匹配包含指定字符的文本 ‘fa’ 匹配包含‘fa’的文本 fan、afa、faad
[字符集合] 匹配字符集合中的任何一个字符 ‘[xz]’ 匹配 x 或者 z dizzy、zebra、x-ray、extra
[^] 匹配不在括号中的任何字符 ‘[^abc]’ 匹配任何不包含 a、b 或 c 的字符串 desk、fox、f8ke
字符串 匹配前面的字符串至少 n 次 ‘b{2}’ 匹配 2 个或更多的 b bbb、bbbb、bbbbbbb
字符串 匹配前面的字符串至少 n 次， 至多 m 次 ‘b{2,4}’ 匹配最少 2 个，最多 4 个 b bbb、bbbb

【3】演示

  • 创建表
DROP TABLE IF EXISTS `person`;


mysql> CREATE TABLE `person`  (

    ->   `name` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,

    ->   `age` int(40) NULL DEFAULT NULL,

    ->   `heigh` int(40) NULL DEFAULT NULL,

    ->   `sex` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL

    -> ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;

Query OK, 0 rows affected (0.04 sec)

  • 插入数据

INSERT INTO `person` VALUES ('Thomas ', 25, 168, '男');

INSERT INTO `person` VALUES ('Tom ', 20, 172, '男');

INSERT INTO `person` VALUES ('Dany', 29, 175, '男');

INSERT INTO `person` VALUES ('Jane', 27, 171, '男');

INSERT INTO `person` VALUES ('Susan', 24, 173, '女');

INSERT INTO `person` VALUES ('Green', 25, 168, '女');

INSERT INTO `person` VALUES ('Henry', 21, 160, '女');

INSERT INTO `person` VALUES ('Lily', 18, 190, '男');

INSERT INTO `person` VALUES ('LiMing', 19, 187, '男');


# 查询 name 字段以j开头的记录

select * from person where name REGEXP '^j';

select * from person where name REGEXP 'y$';

select * from person where name REGEXP 'Th*';

# SQL语句中的正则表达式并不完善，所以功能不全

select * from person where name REGEXP '....';

MySQL之过滤条件的更多相关文章

  1. MySQL全面瓦解7：查询的过滤条件

    概述 在实际的业务场景应用中,我们经常要根据业务条件获取并筛选出我们的目标数据.这个过程我们称之为数据查询的过滤.而过滤过程使用的各种条件(比如日期时间.用户.状态)是我们获取精准数据的必要步骤, 这 ...

  2. MySQL · 性能优化 · 条件下推到物化表

    MySQL · 性能优化 · 条件下推到物化表 http://mysql.taobao.org/monthly/2016/07/08/ 背景 MySQL引入了Materialization(物化)这一 ...

  3. 在sphinx中应用复杂过滤条件

    一.问题的引入   在sphinx应用中,需要对数据进行复杂的条件过滤,刷选出我们需要的数据.这个过程,等同于mysql查询中的where条件.   但sphinx本身的filter并不能支持复杂的逻 ...

  4. SQL语句中过滤条件放在on和where子句中的区别和联系

    摘要: 介绍在多表关联SQL语句中,过滤条件放在on和where子句中的区别--inner join中没区别,外连接就不一样. 综述   蚂蚁金服的一道SQL面试题如下:SQL语句中,过滤条件放在on ...

  5. .NET深入实战系列--EF到底怎么写过滤条件

    本文唯一访问地址:http://www.cnblogs.com/yubaolee/p/DynamicLinq.html 对于系统开发来说,按不同字段进行过滤查询是一种常见的需求.在EF中通常的做法是: ...

  6. SQL优化 查询语句中，用 inner join 作为过滤条件和用where作为过滤条件的区别

    前段时间遇到一个存储过程,参数之一是一个字符串,在存储过程中,把字符串拆分成一个临时表之后存为一个key值的临时表,作为其中一个查询条件, 逻辑实现上有两种处理方式 insert into #t se ...

  7. 自定义 Azure Table storage 查询过滤条件

    本文是在Azure Table storage 基本用法一文的基础上,介绍如何自定义 Azure Table storage 的查询过滤条件.如果您还不太清楚 Azure Table storage ...

  8. mysql数据过滤

    WHERE子句 在我们使用数据库时,通常只会根据特定条件提取表数据的子集.只检索所需数据需要指定搜索条件(search criteria),搜索条件也称为过滤条件(filtercondition). ...

  9. WireShark系列： 使用WireShark过滤条件抓取特定数据流(zz)

    应用抓包过滤,选择Capture | Options,扩展窗口查看到Capture Filter栏.双击选定的接口,如下图所示,弹出Edit Interface Settints窗口. 下图显示了Ed ...

  10. .NET深入实战系列--EF到底怎么写过滤条件（转）

    原文来自:http://www.cnblogs.com/yubaolee/p/DynamicLinq.html 对于系统开发来说,按不同字段进行过滤查询是一种常见的需求.在EF中通常的做法是: /// ...

随机推荐

  1. 小白学k8s(5)k8s中的service

    k8s中的service service存在的意义 Pod与Service的关系 Port port targetPort nodePort IP Node IP Pod IP Cluster IP ...

  2. Midjourney|文心一格prompt教程[Text Prompt（下篇）]：游戏、实物、人物、风景、动漫、邮票、海报等生成，终极模板教学

    Midjourney|文心一格prompt教程[Text Prompt(下篇)]:游戏.实物.人物.风景.动漫.邮票.海报等生成,终极模板教学 场景6:游戏 Prompt 真的越长越好吗? 按照 Mi ...

  3. 9.4 Windows驱动开发：内核PE结构VA与FOA转换

    本章将继续探索内核中解析PE文件的相关内容,PE文件中FOA与VA,RVA之间的转换也是很重要的,所谓的FOA是文件中的地址,VA则是内存装入后的虚拟地址,RVA是内存基址与当前地址的相对偏移,本章还 ...

  4. 4.2 Inline Hook 挂钩技术

    InlineHook 是一种计算机安全编程技术,其原理是在计算机程序执行期间进行拦截.修改.增强现有函数功能.它使用钩子函数(也可以称为回调函数)来截获程序执行的各种事件,并在事件发生前或后进行自定义 ...

  5. C/C++ Qt QThread 线程组件应用

    QThread库是QT中提供的跨平台多线程实现方案,使用时需要继承QThread这个基类,并重写实现内部的Run方法,由于该库是基本库,默认依赖于QtCore.dll这个基础模块,在使用时无需引入其他 ...

  6. 进程锁（互斥锁）（Python）

    3:# 抢票示例 import json import time from multiprocessing import Process,Lock def search(i): with open(' ...

  7. AI PC两年要大卖1亿台！就靠它了

    Intel在中国北京召开了主题为"AI无处不在,创芯无所不及"的2023Intel新品发布会暨AI技术创新派对,正式发布了代号为"Meteor Lake"的面向 ...

  8. Vite4+Typescript+Vue3+Pinia 从零搭建(1) - 项目初始化

    项目代码同步至码云 weiz-vue3-template 前提准备 1. node版本 Node.js版本 >= 12,如果有老项目需要旧版本的,推荐用 nvm 管理node版本. PS C:\ ...

  9. CF145E Lucky Queries 题解

    题目链接:CF 或者 洛谷 前置知识点:序列操作 本文关键词 约定俗称:因为频繁敲最长不下降子序列 \(LNCS\) 和最长不上升子序列 \(LNIS\) 太麻烦了,下文将 \(000011111\) ...

  10. 教你用JavaScript获取大转盘

    案例介绍 欢迎来到我的小院,我是霍大侠,恭喜你今天又要进步一点点了!我们来用JavaScript编程实战案例,做一个大转盘.当你难以抉择的时候不妨用这个案例来帮你做选择.通过编程实战我们可以学到按钮的 ...