本文实例讲述了MySQL单表查询操作。分享给大家供大家参考，具体如下：
语法
一、单表查询的语法
SELECT 字段1,字段2... FROM 表名
WHERE 条件
GROUP BY field
HAVING 筛选
ORDER BY field
LIMIT 限制条数
二、关键字的执行优先级（重点）
重点中的重点：关键字的执行优先级
from
where
group by
having
select
distinct
order by
limit
1.找到表:from
2.拿着where指定的约束条件，去文件/表中取出一条条记录
3.将取出的一条条记录进行分组group by，如果没有group by，则整体作为一组
4.将分组的结果进行having过滤
5.执行select
6.去重
7.将结果按条件排序：order by
8.限制结果的显示条数
（1）where 约束
where运算符
where子句中可以使用
1.比较运算符：>、<、>=、<=、<>、!=
2.between 80 and 100 ：值在80到100之间
3.in(80,90,100)值是10或20或30
4.like 'xiaomagepattern': pattern可以是%或者_。%小时任意多字符，_表示一个字符
5.逻辑运算符：在多个条件直接可以使用逻辑运算符 and or not
（2）group by 分组查询
#1、首先明确一点：分组发生在where之后，即分组是基于where之后得到的记录而进行的
#2、分组指的是：将所有记录按照某个相同字段进行归类，比如针对员工信息表的职位分组，或者按照性别进行分组等
#3、为何要分组呢？
取每个部门的最高工资
取每个部门的员工数
取男人数和女人数小窍门：‘每'这个字后面的字段，就是我们分组的依据
#4、大前提：
可以按照任意字段分组，但是分组完毕后，比如group by post，只能查看post字段，如果想查看组内信息，需要借助于聚合函数
当执行以下sql语句的时候，没有报错，但本身是没有意义的
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mysql> select * from employee group by post;
+----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| 14 | 张野 | male | 28 | 2016-03-11 | operation | NULL | 10000.13 | 403 | 3 |
| 9 | 歪歪 | female | 48 | 2015-03-11 | sale | NULL | 3000.13 | 402 | 2 |
| 2 | alex | male | 78 | 2015-03-02 | teacher | | 1000000.31 | 401 | 1 |
| 1 | egon | male | 18 | 2017-03-01 | 老男孩驻沙河办事处外交大使 | NULL | 7300.33 | 401 | 1 |
+----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
4 rows in set (0.00 sec)
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设置sql_mode为ONLY_FULL_GROUP_BY，并且退出，再进入才会生效
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mysql> set global sql_mode='STRICT_TRANS_TABLES,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION,ONLY_FULL_GROUP_BY';
Query OK, 0 rows affected (0.00 sec)
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再次进入
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mysql> select @@sql_mode;
+-----------------------------------------------------------------------------------+
| @@sql_mode |
+-----------------------------------------------------------------------------------+
| ONLY_FULL_GROUP_BY,STRICT_TRANS_TABLES,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION |
+-----------------------------------------------------------------------------------
mysql> select * from emp group by post;//现在的情况下就会报错
ERROR 1054 (42S22): Unknown column 'post' in 'group statement'
mysql> select * from employee group by post;
ERROR 1055 (42000): 't1.employee.id' isn't in GROUP BY
mysql> select post from employee group by post;
+-----------------------------------------+
| post |
+-----------------------------------------+
| operation |
| sale |
| teacher |
| 老男孩驻沙河办事处外交大使 |
+-----------------------------------------+
4 rows in set (0.00 sec)
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或者如下使用
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mysql> select name,post from employee group by post,name;
+------------+-----------------------------------------+
| name | post |
+------------+-----------------------------------------+
| 张野 | operation |
| 程咬金 | operation |
| 程咬铁 | operation |
| 程咬铜 | operation |
| 程咬银 | operation |
| 丁丁 | sale |
| 丫丫 | sale |
| 星星 | sale |
| 格格 | sale |
| 歪歪 | sale |
| alex | teacher |
| jingliyang | teacher |
| jinxin | teacher |
| liwenzhou | teacher |
| wupeiqi | teacher |
| xiaomage | teacher |
| yuanhao | teacher |
| egon | 老男孩驻沙河办事处外交大使 |
+------------+-----------------------------------------+
18 rows in set (0.00 sec)
mysql> select post,count(id) from employee group by post;
+-----------------------------------------+-----------+
| post | count(id) |
+-----------------------------------------+-----------+
| operation | 5 |
| sale | 5 |
| teacher | 7 |
| 老男孩驻沙河办事处外交大使 | 1 |
+-----------------------------------------+-----------+
4 rows in set (0.00 sec)
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（3）聚合函数
max()求最大值
min()求最小值
avg()求平均值
sum() 求和
count() 求总个数
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#强调：聚合函数聚合的是组的内容，若是没有分组，则默认一组
# 每个部门有多少个员工
select post,count(id) from employee group by post;
# 每个部门的最高薪水
select post,max(salary) from employee group by post;
# 每个部门的最低薪水
select post,min(salary) from employee group by post;
# 每个部门的平均薪水
select post,avg(salary) from employee group by post;
# 每个部门的所有薪水
select post,sum(age) from employee group by post;
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（4）HAVING过滤
HAVING与WHERE不一样的地方在于
#！！！执行优先级从高到低：where > group by > having
#1. Where 发生在分组group by之前，因而Where中可以有任意字段，但是绝对不能使用聚合函数。#2. Having发生在分组group by之后，因而Having中可以使用分组的字段，无法直接取到其他字段,可以使用聚合函数
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mysql> select * from employee where salary>1000000;
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
| 2 | alex | male | 78 | 2015-03-02 | teacher | | 1000000.31 | 401 | 1 |
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
1 row in set (0.00 sec)
mysql> select * from employee having salary>1000000;
ERROR 1463 (42000): Non-grouping field 'salary' is used in HAVING clause
# 必须使用group by才能使用group_concat()函数，将所有的name值连接
mysql> select post,group_concat(name) from emp group by post having salary > 10000; ##错误，分组后无法直接取到salary字段
ERROR 1054 (42S22): Unknown column 'post' in 'field list'
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练习
1. 查询各岗位内包含的员工个数小于2的岗位名、岗位内包含员工名字、个数
2. 查询各岗位平均薪资大于10000的岗位名、平均工资
3. 查询各岗位平均薪资大于10000且小于20000的岗位名、平均工资
答案
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mysql> select post,group_concat(name),count(id) from employee group by post;
+-----------------------------------------+-----------------------------------------------------------+-----------+
| post | group_concat(name) | count(id) |
+-----------------------------------------+-----------------------------------------------------------+-----------+
| operation | 程咬铁,程咬铜,程咬银,程咬金,张野 | 5 |
| sale | 格格,星星,丁丁,丫丫,歪歪 | 5 |
| teacher | xiaomage,jinxin,jingliyang,liwenzhou,yuanhao,wupeiqi,alex | 7 |
| 老男孩驻沙河办事处外交大使 | egon | 1 |
+-----------------------------------------+-----------------------------------------------------------+-----------+
4 rows in set (0.00 sec)
mysql> select post,group_concat(name),count(id) from employee group by post having count(id)<2;
+-----------------------------------------+--------------------+-----------+
| post | group_concat(name) | count(id) |
+-----------------------------------------+--------------------+-----------+
| 老男孩驻沙河办事处外交大使 | egon | 1 |
+-----------------------------------------+--------------------+-----------+
1 row in set (0.00 sec)
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#题2：
mysql> select post,avg(salary) from employee group by post having avg(salary) > 10000;
+-----------+---------------+
| post | avg(salary) |
+-----------+---------------+
| operation | 16800.026000 |
| teacher | 151842.901429 |
+-----------+---------------+
2 rows in set (0.00 sec)
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#题3：
mysql> select post,avg(salary) from employee group by post having avg(salary) > 10000 and avg(salary) <20000;
+-----------+--------------+
| post | avg(salary) |
+-----------+--------------+
| operation | 16800.026000 |
+-----------+--------------+
1 row in set (0.00 sec)
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（5）order by 查询排序
按单列排序
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SELECT * FROM employee ORDER BY age;
SELECT * FROM employee ORDER BY age ASC;
SELECT * FROM employee ORDER BY age DESC;
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按多列排序:先按照age升序排序，如果年纪相同，则按照id降序
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SELECT * from employee
ORDER BY age ASC,
id DESC;
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（5）limit 限制查询的记录数:
示例：
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SELECT * FROM employee ORDER BY salary DESC
LIMIT 3; #默认初始位置为0
SELECT * FROM employee ORDER BY salary DESC
LIMIT 0,5; #从第0开始，即先查询出第一条，然后包含这一条在内往后查5条
SELECT * FROM employee ORDER BY salary DESC
LIMIT 5,5; #从第5开始，即先查询出第6条，然后包含这一条在内往后查5条
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练习：每次显示5条
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# 第1页数据
mysql> select * from employee limit 0,5;
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| 1 | egon | male | 18 | 2017-03-01 | 老男孩驻沙河办事处外交大使 | NULL | 7300.33 | 401 | 1 |
| 2 | alex | male | 78 | 2015-03-02 | teacher | | 1000000.31 | 401 | 1 |
| 3 | wupeiqi | male | 81 | 2013-03-05 | teacher | NULL | 8300.00 | 401 | 1 |
| 4 | yuanhao | male | 73 | 2014-07-01 | teacher | NULL | 3500.00 | 401 | 1 |
| 5 | liwenzhou | male | 28 | 2012-11-01 | teacher | NULL | 2100.00 | 401 | 1 |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
5 rows in set (0.00 sec)
# 第2页数据
mysql> select * from employee limit 5,5;
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
| 6 | jingliyang | female | 18 | 2011-02-11 | teacher | NULL | 9000.00 | 401 | 1 |
| 7 | jinxin | male | 18 | 1900-03-01 | teacher | NULL | 30000.00 | 401 | 1 |
| 8 | xiaomage | male | 48 | 2010-11-11 | teacher | NULL | 10000.00 | 401 | 1 |
| 9 | 歪歪 | female | 48 | 2015-03-11 | sale | NULL | 3000.13 | 402 | 2 |
| 10 | 丫丫 | female | 38 | 2010-11-01 | sale | NULL | 2000.35 | 402 | 2 |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
5 rows in set (0.00 sec)
# 第3页数据
mysql> select * from employee limit 10,5;
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| 11 | 丁丁 | female | 18 | 2011-03-12 | sale | NULL | 1000.37 | 402 | 2 |
| 12 | 星星 | female | 18 | 2016-05-13 | sale | NULL | 3000.29 | 402 | 2 |
| 13 | 格格 | female | 28 | 2017-01-27 | sale | NULL | 4000.33 | 402 | 2 |
| 14 | 张野 | male | 28 | 2016-03-11 | operation | NULL | 10000.13 | 403 | 3 |
| 15 | 程咬金 | male | 18 | 1997-03-12 | operation | NULL | 20000.00 | 403 | 3 |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
5 rows in set (0.00 sec)
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希望本文所述对大家MySQL数据库计有所帮助。
原文链接：https://www.cnblogs.com/mmyy-blog/p/9626857.html