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_insert1\G

 #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='';
 +----------+
 | 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;