python-day43--多表查询

一、多表连接查询:       #重点：外链接语法

准备表

#建表
create table department(
id int,
name varchar(20)
);

create table employee(
id int primary key auto_increment,
name varchar(20),
sex enum('male','female') not null default 'male',
age int,
dep_id int
);

#插入数据
insert into department values
(200,'技术'),
(201,'人力资源'),
(202,'销售'),
(203,'运营');

insert into employee(name,sex,age,dep_id) values
('egon','male',18,200),
('alex','female',48,201),
('wupeiqi','male',38,201),
('yuanhao','female',28,202),
('liwenzhou','male',18,200),
('jingliyang','female',18,204)
;

#查看表结构和数据
mysql> desc department;
+-------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+-------------+------+-----+---------+-------+
| id | int(11) | YES | | NULL | |
| name | varchar(20) | YES | | NULL | |
+-------+-------------+------+-----+---------+-------+

mysql> desc employee;
+--------+-----------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------+-----------------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(20) | YES | | NULL | |
| sex | enum('male','female') | NO | | male | |
| age | int(11) | YES | | NULL | |
| dep_id | int(11) | YES | | NULL | |
+--------+-----------------------+------+-----+---------+----------------+

mysql> select * from department;
+------+--------------+
| id | name |
+------+--------------+
| 200 | 技术 |
| 201 | 人力资源 |
| 202 | 销售 |
| 203 | 运营 |
+------+--------------+

mysql> select * from employee;
+----+------------+--------+------+--------+
| id | name | sex | age | dep_id |
+----+------------+--------+------+--------+
| 1 | egon | male | 18 | 200 |
| 2 | alex | female | 48 | 201 |
| 3 | wupeiqi | male | 38 | 201 |
| 4 | yuanhao | female | 28 | 202 |
| 5 | liwenzhou | male | 18 | 200 |
| 6 | jingliyang | female | 18 | 204 |
+----+------------+--------+------+--------+

1 .交叉连接：不适用任何匹配条件(没意义)。生成笛卡尔积

select * from department,employee;    #笛卡尔积

mysql> select * from employee,department;
+----+------------+--------+------+--------+------+--------------+
| id | name       | sex    | age  | dep_id | id   | name         |
+----+------------+--------+------+--------+------+--------------+
|  1 | egon       | male   |   18 |    200 |  200 | 技术         |
|  1 | egon       | male   |   18 |    200 |  201 | 人力资源     |
|  1 | egon       | male   |   18 |    200 |  202 | 销售         |
|  1 | egon       | male   |   18 |    200 |  203 | 运营         |
|  2 | alex       | female |   48 |    201 |  200 | 技术         |
|  2 | alex       | female |   48 |    201 |  201 | 人力资源     |
|  2 | alex       | female |   48 |    201 |  202 | 销售         |
|  2 | alex       | female |   48 |    201 |  203 | 运营         |
|  3 | wupeiqi    | male   |   38 |    201 |  200 | 技术         |
|  3 | wupeiqi    | male   |   38 |    201 |  201 | 人力资源     |
|  3 | wupeiqi    | male   |   38 |    201 |  202 | 销售         |
|  3 | wupeiqi    | male   |   38 |    201 |  203 | 运营         |
|  4 | yuanhao    | female |   28 |    202 |  200 | 技术         |
|  4 | yuanhao    | female |   28 |    202 |  201 | 人力资源     |
|  4 | yuanhao    | female |   28 |    202 |  202 | 销售         |
|  4 | yuanhao    | female |   28 |    202 |  203 | 运营         |
|  5 | liwenzhou  | male   |   18 |    200 |  200 | 技术         |
|  5 | liwenzhou  | male   |   18 |    200 |  201 | 人力资源     |
|  5 | liwenzhou  | male   |   18 |    200 |  202 | 销售         |
|  5 | liwenzhou  | male   |   18 |    200 |  203 | 运营         |
|  6 | jingliyang | female |   18 |    204 |  200 | 技术         |
|  6 | jingliyang | female |   18 |    204 |  201 | 人力资源     |
|  6 | jingliyang | female |   18 |    204 |  202 | 销售         |
|  6 | jingliyang | female |   18 |    204 |  203 | 运营         |
+----+------------+--------+------+--------+------+--------------+

2.内链接（只连接匹配的行）：按照on条件只两张表的相同的部分，连接成一张虚拟的表
select * from employee inner join department on department.id=employee.dep_id;
select * from department inner join employee on department.id=employee.dep_id;
select * from employee,department where department.id=employee.dep_id;
在内连接两张表的时候不推荐使用where，推荐 inner join，因为join on 在where之前执行

mysql> select * from employee inner join department on department.id=employee.dep_id;
+----+-----------+--------+------+--------+------+--------------+
| id | name      | sex    | age  | dep_id | id   | name         |
+----+-----------+--------+------+--------+------+--------------+
|  1 | egon      | male   |   18 |    200 |  200 | 技术         |
|  2 | alex      | female |   48 |    201 |  201 | 人力资源     |
|  3 | wupeiqi   | male   |   38 |    201 |  201 | 人力资源     |
|  4 | yuanhao   | female |   28 |    202 |  202 | 销售         |
|  5 | liwenzhou | male   |   18 |    200 |  200 | 技术         |
+----+-----------+--------+------+--------+------+--------------+
5 rows in set (0.01 sec)

3.左链接（外链接之左连接：优先显示左表全部记录）：在按照on的条件取到两张表共同部分的基础上，保留左表的记录
select * from employee left join department on department.id=employee.dep_id;

mysql> select * from employee left join department on department.id=employee.dep_id;
+----+------------+--------+------+--------+------+--------------+
| id | name       | sex    | age  | dep_id | id   | name         |
+----+------------+--------+------+--------+------+--------------+
|  1 | egon       | male   |   18 |    200 |  200 | 技术         |
|  5 | liwenzhou  | male   |   18 |    200 |  200 | 技术         |
|  2 | alex       | female |   48 |    201 |  201 | 人力资源     |
|  3 | wupeiqi    | male   |   38 |    201 |  201 | 人力资源     |
|  4 | yuanhao    | female |   28 |    202 |  202 | 销售         |
|  6 | jingliyang | female |   18 |    204 | NULL | NULL         |
+----+------------+--------+------+--------+------+--------------+
6 rows in set (0.00 sec)

4.右链接（外链接之右连接：优先显示右表全部记录）：在按照on的条件取到两张表共同部分的基础上，保留右表的记录
select * from employee right join department on department.id=employee.dep_id;

mysql> select * from employee right join department on department.id=employee.dep_id;
+------+-----------+--------+------+--------+------+--------------+
| id   | name      | sex    | age  | dep_id | id   | name         |
+------+-----------+--------+------+--------+------+--------------+
|    1 | egon      | male   |   18 |    200 |  200 | 技术         |
|    2 | alex      | female |   48 |    201 |  201 | 人力资源     |
|    3 | wupeiqi   | male   |   38 |    201 |  201 | 人力资源     |
|    4 | yuanhao   | female |   28 |    202 |  202 | 销售         |
|    5 | liwenzhou | male   |   18 |    200 |  200 | 技术         |
| NULL | NULL      | NULL   | NULL |   NULL |  203 | 运营         |
+------+-----------+--------+------+--------+------+--------------+
6 rows in set (0.00 sec)

5.full join：（注意在sql语句中没有full join）
全链接（全外连接：显示左右两个表全部记录）：union
select * from employee left join department on department.id=employee.dep_id
union
select * from employee right join department on department.id=employee.dep_id;

mysql> select * from employee left join department on department.id=employee.dep_id
    -> union
    -> select * from employee right join department on department.id=employee.dep_id;
+------+------------+--------+------+--------+------+--------------+
| id   | name       | sex    | age  | dep_id | id   | name         |
+------+------------+--------+------+--------+------+--------------+
|    1 | egon       | male   |   18 |    200 |  200 | 技术         |
|    5 | liwenzhou  | male   |   18 |    200 |  200 | 技术         |
|    2 | alex       | female |   48 |    201 |  201 | 人力资源     |
|    3 | wupeiqi    | male   |   38 |    201 |  201 | 人力资源     |
|    4 | yuanhao    | female |   28 |    202 |  202 | 销售         |
|    6 | jingliyang | female |   18 |    204 | NULL | NULL         |
| NULL | NULL       | NULL   | NULL |   NULL |  203 | 运营         |
+------+------------+--------+------+--------+------+--------------+
7 rows in set (0.00 sec)

#注意 union与union all的区别：union会去掉相同的纪录

6.子查询：
　　1：子查询是将一个查询语句嵌套在另一个查询语句中。
　　2：内层查询语句的查询结果，可以为外层查询语句提供查询条件。
　　3：子查询中可以包含：IN、NOT IN、ANY、ALL、EXISTS 和 NOT EXISTS等关键字
　　4：还可以包含比较运算符：= 、 !=、> 、<等

1 带IN关键字的子查询：
#查询employee表，但dep_id必须在department表中出现过
select * from employee
    where dep_id in
        (select id from department);

mysql> select * from employee where dep_id in (select id from department where name in ('技术','销售'));
+----+-----------+--------+------+--------+
| id | name      | sex    | age  | dep_id |
+----+-----------+--------+------+--------+
|  1 | egon      | male   |   18 |    200 |
|  4 | yuanhao   | female |   28 |    202 |
|  5 | liwenzhou | male   |   18 |    200 |
+----+-----------+--------+------+--------+
3 rows in set (0.02 sec)

2 带比较运算符的子查询：
#比较运算符：=、!=、>、>=、<、<=、<>

#查询平均年龄在25岁以上的部门名
select name from department where id in (
select dep_id from employee group by dep_id having avg(age) > 25
);

+--------------+
| name         |
+--------------+
| 人力资源     |
| 销售         |
+--------------+
2 rows in set (0.00 sec)

#查看技术部员工姓名
select name from employee where dep_id = (select id from department where name='技术');

+-----------+
| name      |
+-----------+
| egon      |
| liwenzhou |
+-----------+
2 rows in set (0.00 sec)

#查看小于2人的部门名
select name from department where id in (
select dep_id from employee group by dep_id having count(id) < 2
)
union
select name from department where id not in (select distinct dep_id from employee);

+--------+
| name   |
+--------+
| 销售   |
| 运营   |
+--------+
2 rows in set (0.01 sec)

#提取空部门                              #没有人的部门
select * from department where id not in (select distinct dep_id from employee);

+------+--------+
| id   | name   |
+------+--------+
|  203 | 运营   |
+------+--------+
1 row in set (0.00 sec)

或者：
select name from department where id in
(
select dep_id from employee group by dep_id having count(id) < 2
union
select id from department where id not in (select distinct dep_id from employee)
);

+--------+
| name   |
+--------+
| 销售   |
| 运营   |
+--------+
2 rows in set (0.00 sec)

3 带EXISTS关键字的子查询：
exists关字键字表示存在。在使用EXISTS关键字时，内层查询语句不返回查询的记录。
而是返回一个真假值。True或False
当返回True时，外层查询语句将进行查询；当返回值为False时，外层查询语句不进行查询

mysql> select * from employee where exists (select id from department where name='hahahahah');
Empty set (0.00 sec)

mysql> select * from employee where exists (select id from department where name='技术');
+----+------------+--------+------+--------+
| id | name       | sex    | age  | dep_id |
+----+------------+--------+------+--------+
|  1 | egon       | male   |   18 |    200 |
|  2 | alex       | female |   48 |    201 |
|  3 | wupeiqi    | male   |   38 |    201 |
|  4 | yuanhao    | female |   28 |    202 |
|  5 | liwenzhou  | male   |   18 |    200 |
|  6 | jingliyang | female |   18 |    204 |
+----+------------+--------+------+--------+
6 rows in set (0.00 sec)

7.！！！重中之重：务必搞清楚sql逻辑查询语句的执行顺序

SELECT语句关键字的定义顺序

SELECT DISTINCT <select_list>
FROM <left_table>
<join_type> JOIN <right_table>
ON <join_condition>
WHERE <where_condition>
GROUP BY <group_by_list>
HAVING <having_condition>
ORDER BY <order_by_condition>
LIMIT <limit_number>

SELECT语句关键字的执行顺序

(7)     SELECT
(8)     DISTINCT <select_list>
(1)     FROM <left_table>
(3)     <join_type> JOIN <right_table>
(2)     ON <join_condition>
(4)     WHERE <where_condition>
(5)     GROUP BY <group_by_list>
(6)     HAVING <having_condition>
(9)     ORDER BY <order_by_condition>
(10)    LIMIT <limit_number>

三 准备表和数据
1. 新建一个测试数据库TestDB；
create database TestDB;
2.创建测试表table1和table2；

CREATE TABLE table1
 (
     customer_id VARCHAR(10) NOT NULL,
     city VARCHAR(10) NOT NULL,
     PRIMARY KEY(customer_id)
 )ENGINE=INNODB DEFAULT CHARSET=UTF8;

 CREATE TABLE table2
 (
     order_id INT NOT NULL auto_increment,
     customer_id VARCHAR(10),
     PRIMARY KEY(order_id)
 )ENGINE=INNODB DEFAULT CHARSET=UTF8;

3.插入测试数据；

 INSERT INTO table1(customer_id,city) VALUES('','hangzhou');
 INSERT INTO table1(customer_id,city) VALUES('9you','shanghai');
 INSERT INTO table1(customer_id,city) VALUES('tx','hangzhou');
 INSERT INTO table1(customer_id,city) VALUES('baidu','hangzhou');

 INSERT INTO table2(customer_id) VALUES('');
 INSERT INTO table2(customer_id) VALUES('');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('tx');
 INSERT INTO table2(customer_id) VALUES(NULL);

准备工作做完以后，table1和table2看起来应该像下面这样：

mysql> select * from table1;
 +-------------+----------+
 | customer_id | city     |
 +-------------+----------+
 | 163         | hangzhou |
 | 9you        | shanghai |
 | baidu       | hangzhou |
 | tx          | hangzhou |
 +-------------+----------+
 4 rows in set (0.00 sec)

 mysql> select * from table2;
 +----------+-------------+
 | order_id | customer_id |
 +----------+-------------+
 |        1 | 163         |
 |        2 | 163         |
 |        3 | 9you        |
 |        4 | 9you        |
 |        5 | 9you        |
 |        6 | tx          |
 |        7 | NULL        |
 +----------+-------------+
 7 rows in set (0.00 sec)

四 准备SQL逻辑查询测试语句

#查询来自杭州，并且订单数少于2的客户。
 SELECT a.customer_id, COUNT(b.order_id) as total_orders
 FROM table1 AS a
 LEFT JOIN table2 AS b
 ON a.customer_id = b.customer_id
 WHERE a.city = 'hangzhou'
 GROUP BY a.customer_id
 HAVING count(b.order_id) < 2
 ORDER BY total_orders DESC;

五 执行顺序分析
在这些SQL语句的执行过程中，都会产生一个虚拟表，用来保存SQL语句的执行结果（这是重点），我现在就来跟踪这个虚拟表的变化，得到最终的查询结果的过程，来分析整个SQL逻辑查询的执行顺序和过程。
执行FROM语句
第一步，执行FROM语句。我们首先需要知道最开始从哪个表开始的，这就是FROM告诉我们的。现在有了<left_table>和<right_table>两个表，我们到底从哪个表开始，还是从两个表进行某种联系以后再开始呢？它们之间如何产生联系呢？——笛卡尔积
关于什么是笛卡尔积，请自行Google补脑。经过FROM语句对两个表执行笛卡尔积，会得到一个虚拟表，暂且叫VT1（vitual table 1），内容如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 9you        | shanghai |        1 | 163         |
| baidu       | hangzhou |        1 | 163         |
| tx          | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        2 | 163         |
| baidu       | hangzhou |        2 | 163         |
| tx          | hangzhou |        2 | 163         |
| 163         | hangzhou |        3 | 9you        |
| 9you        | shanghai |        3 | 9you        |
| baidu       | hangzhou |        3 | 9you        |
| tx          | hangzhou |        3 | 9you        |
| 163         | hangzhou |        4 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| baidu       | hangzhou |        4 | 9you        |
| tx          | hangzhou |        4 | 9you        |
| 163         | hangzhou |        5 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| baidu       | hangzhou |        5 | 9you        |
| tx          | hangzhou |        5 | 9you        |
| 163         | hangzhou |        6 | tx          |
| 9you        | shanghai |        6 | tx          |
| baidu       | hangzhou |        6 | tx          |
| tx          | hangzhou |        6 | tx          |
| 163         | hangzhou |        7 | NULL        |
| 9you        | shanghai |        7 | NULL        |
| baidu       | hangzhou |        7 | NULL        |
| tx          | hangzhou |        7 | NULL        |
+-------------+----------+----------+-------------+

总共有28（table1的记录条数 * table2的记录条数）条记录。这就是VT1的结果，接下来的操作就在VT1的基础上进行。
执行ON过滤
执行完笛卡尔积以后，接着就进行ON a.customer_id = b.customer_id条件过滤，根据ON中指定的条件，去掉那些不符合条件的数据，得到VT2表，内容如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+

VT2就是经过ON条件筛选以后得到的有用数据，而接下来的操作将在VT2的基础上继续进行。
添加外部行
这一步只有在连接类型为OUTER JOIN时才发生，如LEFT OUTER JOIN、RIGHT OUTER JOIN和FULL OUTER JOIN。在大多数的时候，我们都是会省略掉OUTER关键字的，但OUTER表示的就是外部行的概念。
LEFT OUTER JOIN把左表记为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

RIGHT OUTER JOIN把右表记为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| NULL        | NULL     |        7 | NULL        |
+-------------+----------+----------+-------------+

FULL OUTER JOIN把左右表都作为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
| NULL        | NULL     |        7 | NULL        |
+-------------+----------+----------+-------------+

添加外部行的工作就是在VT2表的基础上添加保留表中被过滤条件过滤掉的数据，非保留表中的数据被赋予NULL值，最后生成虚拟表VT3。
由于我在准备的测试SQL查询逻辑语句中使用的是LEFT JOIN，过滤掉了以下这条数据：
| baidu       | hangzhou |     NULL | NULL        |
现在就把这条数据添加到VT2表中，得到的VT3表如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

接下来的操作都会在该VT3表上进行。
执行WHERE过滤
对添加外部行得到的VT3进行WHERE过滤，只有符合<where_condition>的记录才会输出到虚拟表VT4中。当我们执行WHERE a.city = 'hangzhou'的时候，就会得到以下内容，并存在虚拟表VT4中：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

但是在使用WHERE子句时，需要注意以下两点：
由于数据还没有分组，因此现在还不能在WHERE过滤器中使用where_condition=MIN(col)这类对分组统计的过滤；
由于还没有进行列的选取操作，因此在SELECT中使用列的别名也是不被允许的，如：SELECT city as c FROM t WHERE c='shanghai';是不允许出现的。
执行GROUP BY分组
GROU BY子句主要是对使用WHERE子句得到的虚拟表进行分组操作。我们执行测试语句中的GROUP BY a.customer_id，就会得到以下内容(默认只显示组内第一条)：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| baidu       | hangzhou |     NULL | NULL        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+

得到的内容会存入虚拟表VT5中，此时，我们就得到了一个VT5虚拟表，接下来的操作都会在该表上完成。
执行HAVING过滤
HAVING子句主要和GROUP BY子句配合使用，对分组得到的VT5虚拟表进行条件过滤。当我执行测试语句中的HAVING count(b.order_id) < 2时，将得到以下内容：
+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| baidu       | hangzhou |     NULL | NULL        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+
这就是虚拟表VT6。
SELECT列表
现在才会执行到SELECT子句，不要以为SELECT子句被写在第一行，就是第一个被执行的。
我们执行测试语句中的SELECT a.customer_id, COUNT(b.order_id) as total_orders，从虚拟表VT6中选择出我们需要的内容。我们将得到以下内容：
+-------------+--------------+
| customer_id | total_orders |
+-------------+--------------+
| baidu       |            0 |
| tx          |            1 |
+-------------+--------------+
还没有完，这只是虚拟表VT7。
执行DISTINCT子句
如果在查询中指定了DISTINCT子句，则会创建一张内存临时表（如果内存放不下，就需要存放在硬盘了）。这张临时表的表结构和上一步产生的虚拟表VT7是一样的，不同的是对进行DISTINCT操作的列增加了一个唯一索引，以此来除重复数据。
由于我的测试SQL语句中并没有使用DISTINCT，所以，在该查询中，这一步不会生成一个虚拟表。
执行ORDER BY子句
对虚拟表中的内容按照指定的列进行排序，然后返回一个新的虚拟表，我们执行测试SQL语句中的ORDER BY total_orders DESC，就会得到以下内容：
+-------------+--------------+
| customer_id | total_orders |
+-------------+--------------+
| tx          |            1 |
| baidu       |            0 |
+-------------+--------------+
可以看到这是对total_orders列进行降序排列的。上述结果会存储在VT8中。
执行LIMIT子句
LIMIT子句从上一步得到的VT8虚拟表中选出从指定位置开始的指定行数据。对于没有应用ORDER BY的LIMIT子句，得到的结果同样是无序的，所以，很多时候，我们都会看到LIMIT子句会和ORDER BY子句一起使用。
MySQL数据库的LIMIT支持如下形式的选择：
LIMIT n, m
表示从第n条记录开始选择m条记录。而很多开发人员喜欢使用该语句来解决分页问题。对于小数据，使用LIMIT子句没有任何问题，当数据量非常大的时候，使用LIMIT n, m是非常低效的。因为LIMIT的机制是每次都是从头开始扫描，如果需要从第60万行开始，读取3条数据，就需要先扫描定位到60万行，然后再进行读取，而扫描的过程是一个非常低效的过程。所以，对于大数据处理时，是非常有必要在应用层建立一定的缓存机制（现在的大数据处理，大都使用缓存）