python开发mysql:索引

一，索引管理

索引分类：
普通索引INDEX：加速查找

唯一索引：
    -主键索引PRIMARY KEY：加速查找+约束（不为空、不能重复）
    -唯一索引UNIQUE:加速查找+约束（不能重复）

联合索引：
    -PRIMARY KEY(id,name):联合主键索引
    -UNIQUE(id,name):联合唯一索引
    -INDEX(id,name):联合普通索引

1 创建索引
    - 在创建表时就创建
        create table s1(
        id int,
        name char(6),
        age int,
        email varchar(30),
        index(id)
        );
    - 在创建表后创建
        create index name on s1(name);#添加普通索引
        create unique index age on s1(age);#添加唯一索引
        alter table s1 add primary key(id);#添加主键索引
        create index name on s1(id,name);#添加联合普通索引
** 在创表的时候创建只能写在后面单写，因为他不是起约束的作用

2 删除索引
    drop index id on s1;
    drop index name on s1;
    alter table s1 add primary key(id,name);联合主键索引
    alter table s1 drop primary key;#删除主键索引

3 正确使用索引
    select sql_no_cache * from s1 where email='xxx'; #命中索引，速度很快
    select sql_no_cache * from s1 where email like '%old%'; #无法使用索引，速度依然很慢




4 存储过程，主要用来生成多数据，然后按照普通查询和索引查询对比一下查询的时间
#1. 准备表
create table s1(
id int,
name varchar(20),
gender char(6),
email varchar(50)
);

#2. 创建存储过程，实现批量插入记录
delimiter $$ #声明存储过程的结束符号为$$
create procedure auto_insert1()
BEGIN
    declare i int default 1;
    while(i<3000000)do
        insert into s1 values(i,concat('egon',i),'male',concat('egon',i,'@oldboy'));
        set i=i+1;
    end while;
END$$ #$$结束
delimiter ; #重新声明分号为结束符号

#3. 查看存储过程
show create procedure auto_insert1G

#4. 调用存储过程
call auto_insert1();

#5. 删除存储过程
drop procedure auto_insert1;

#6. 显示数据库中所有存储的存储过程基本信息，包括所属数据库，存储过程名称，创建时间等
show procedure status

二，索引使用

** 索引必须是一个明确的值才能体现其查询速度，例如where id=30521,如果是范围操作（大于，小于，between），就是还是需要循环判断，索引就不起作用

1 加索引提速
无索引
mysql> select count(*) from s1 where id=1000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.12 sec)

mysql> select count(*) from s1 where id>1000;
+----------+
| count(*) |
+----------+
|   298999 |
+----------+
1 row in set (0.12 sec)

有索引
mysql> create index a on s1(id)
    -> ;
Query OK, 0 rows affected (3.21 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where id=1000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where id>1000;
+----------+
| count(*) |
+----------+
|   298999 |
+----------+
1 row in set (0.12 sec)
** 索引必须是一个能查询明确的值才能体现其查询速度，


2 范围
#范围小的话，索引有用
mysql> select count(*) from s1 where id>1000 and id < 2000;
+----------+
| count(*) |
+----------+
|      999 |
+----------+
1 row in set (0.00 sec)

#范围大的话，索引没用
mysql> select count(*) from s1 where id>1000 and id < 300000;
+----------+
| count(*) |
+----------+
|   298999 |
+----------+
1 row in set (0.13 sec)
** 范围小可以体现索引的作用，大范围还是要逐个循环


3 区分度低的字段不能加索引
有索引
mysql> create index b on s1(name)
    -> ;
Query OK, 0 rows affected (3.21 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where name='xxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon';
+----------+
| count(*) |
+----------+
|   299999 |
+----------+
1 row in set (0.19 sec)
** 表内name都是egon这个值，所以有30万个egon，都是要一行一行去匹配

mysql> select count(*) from s1 where name='egon' and age=123123123123123;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.45 sec)

mysql> select count(*) from s1 where name='dfsdfdsfdfdsfdsfdsf' and age=123123123123123;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)
** 同上面结论

mysql> create index c on s1(age);
Query OK, 0 rows affected (3.03 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where name='egon' and age=123123123123123;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' and age=10;
+----------+
| count(*) |
+----------+
|   299999 |
+----------+
1 row in set (0.35 sec)
** 之所以加速，因为and是同时，也就是age右边可以瞬间定位，再比对nmae

mysql> select count(*) from s1 where name='egon' and age=10;
+----------+
| count(*) |
+----------+
|      999 |
+----------+
1 row in set (0.00 sec)
age=10 区分度高

mysql> select count(*) from s1 where name='egon' and agw>50;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.47 sec)

mysql> select count(*) from s1 where name='egon' and age>100 and age < 600;
+----------+
| count(*) |
+----------+
|      999 |
+----------+
1 row in set (0.00 sec)
** 区分度高原则，范围原则小，差异就小


4 mysql> create index d on s1(email);
Query OK, 0 rows affected (4.83 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where name='egon' and age=10 and id>3000 and email='xxxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)

mysql> drop index a on s1;
Query OK, 0 rows affected (0.10 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> drop index b on s1;
Query OK, 0 rows affected (0.09 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> drop index c on s1;
Query OK, 0 rows affected (0.09 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc s1;
+-------+-------------+------+-----+---------+-------+
| Field | Type        | Null | Key | Default | Extra |
+-------+-------------+------+-----+---------+-------+
| id    | int(11)     | NO   |     | NULL    |       |
| name  | char(20)    | YES  |     | NULL    |       |
| age   | int(11)     | YES  |     | NULL    |       |
| email | varchar(30) | YES  | MUL | NULL    |       |
+-------+-------------+------+-----+---------+-------+
4 rows in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' and age=10 and id>3000 and email='xxxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)
** 区分度高原则，范围原则小，差异就小,email最高


5 增加联合索引，关于范围查询的字段要放到后面
 select count(*) from s1 where name='egon' and age=10 and id>3000 and email='xxxx';
 index(name,email,age,id)

 select count(*) from s1 where name='egon' and age> 10 and id=3000 and email='xxxx';
index(name,email,id,age)

 select count(*) from s1 where name like 'egon' and age= 10 and id=3000 and email='xxxx';
index(email,id,age,name)

mysql> desc s1;
+-------+-------------+------+-----+---------+-------+
| Field | Type        | Null | Key | Default | Extra |
+-------+-------------+------+-----+---------+-------+
| id    | int(11)     | NO   |     | NULL    |       |
| name  | char(20)    | YES  |     | NULL    |       |
| age   | int(11)     | YES  |     | NULL    |       |
| email | varchar(30) | YES  |     | NULL    |       |
+-------+-------------+------+-----+---------+-------+
4 rows in set (0.00 sec)

mysql> create index xxx on s1(age,email,name,id);
Query OK, 0 rows affected (6.89 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where name='egon' and age=10 and id>3000 and email='xxxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)

6. 联合索引，最左前缀匹配，多用于and
index(id,age,email,name)
#条件中一定要出现id
id
id age
id email
id name

email #不行，最左边匹配
mysql> select count(*) from s1 where id=3000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.11 sec)

mysql> create index xxx on s1(id,name,age,email);
Query OK, 0 rows affected (6.44 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql>  select count(*) from s1 where id=3000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql>  select count(*) from s1 where name='egon';
+----------+
| count(*) |
+----------+
|   299999 |
+----------+
1 row in set (0.16 sec)

mysql>  select count(*) from s1 where email='egon3333@oldboy.com';
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.15 sec)

mysql>  select count(*) from s1 where id=1000 and email='egon3333@oldboy.com';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)

mysql>  select count(*) from s1 where email='egon3333@oldboy.com' and id=3000;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.00 sec)
** 最左匹配，如果没有Id就会有时间得到结果


6.索引列不能参与计算，参与计算，所以就没有意义，保持列“干净”
mysql>  select count(*) from s1 where id*3;
+----------+
| count(*) |
+----------+
|   299999 |
+----------+
1 row in set (0.16 sec)

** 用不上索引
like 函数 or 类型不一致 != > < order by

类型不一致
mysql> select count(*) from s1 where id='3000';
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set

mysql>  select count(*) from s1 where id=3000;
+----------+
| count(*) |
+----------+(0.11 sec)
|        1 |
+----------+
1 row in set (0.00 sec)

order by 模糊
select id from s1 order by id;

or 只有id是索引，必须是左右2边单独有索引才能提速，叫做索引合并
mysql>  select count(*) from s1 where id=1000 or email='xxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.13 sec)


慢查询
在Mysqld下面配置
slow-query-log=1  开
slow-query-log-file=slow.log 存放位置
long_query_time=3 超时限制3毫秒就会被记录

在cmd里面
set global slow-query-log=ON;
show variables like '%query%';
set session long_query_time=3;