mysql之索引查询2

一 索引的创建

　索引减慢了 写的操作，优化了读取的时间

　index：普通索引，加速了查找的时间。

　fulltext：全文索引，可以选用占用空间非常大的文本信息的字段作为索引的字段。使用fulltext时需要借助第三方的软件sphinx专用去那问搜索。

　创建格式，创建表时加上索引：

　　create table 表名（字段1 类型 约束键，。。。。。）;

　　create table 表名（字段1 类型，。。。。，约束键）

mysql> create table t2(id int primary key auto_increment,
    ->                  name char(15) not null unique);
Query OK, 0 rows affected (0.24 sec)

mysql> desc t2;
+-------+----------+------+-----+---------+----------------+
| Field | Type     | Null | Key | Default | Extra          |
+-------+----------+------+-----+---------+----------------+
| id    | int(11)  | NO   | PRI | NULL    | auto_increment |
| name  | char(15) | NO   | UNI | NULL    |                |
+-------+----------+------+-----+---------+----------------+
2 rows in set (0.01 sec)

mysql> create table t3(id int,
    ->                  name char(15),
    ->                  index idx_id(id));
Query OK, 0 rows affected (0.24 sec)

mysql> desc t3;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  | MUL | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+
2 rows in set (0.01 sec)

　常用的索引约束键有：primary key    unique key，

　　　普通的索引有：index

　创建表后指定字段为索引字段：

　　create index 起名 on 表名（字段名）；

　　alter table 表名 add index 起名（字段名）；mysql

mysql> create table t4(id int ,
    ->                  name char(15));
Query OK, 0 rows affected (0.25 sec)

mysql> create table t5(id int,
    ->                  name char(15));
Query OK, 0 rows affected (0.33 sec)

mysql> desc t4;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  |     | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+
2 rows in set (0.03 sec)

mysql> create index idx_id on t4(id);
Query OK, 0 rows affected (0.25 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc t4;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  | MUL | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+
2 rows in set (0.01 sec)

mysql> alter table t5 add index idx_id(id);
Query OK, 0 rows affected (0.19 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc t5;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  | MUL | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+
2 rows in set (0.01 sec)

　删除索引：

　　drop index 索引名 on 表名

　　删除主键：alter table 表名 drop primary key；

mysql> desc t4;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  | MUL | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+
2 rows in set (0.01 sec)

mysql> drop index idx_id on t4;
Query OK, 0 rows affected (0.16 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc t4;
+-------+----------+------+-----+---------+-------+
| Field | Type     | Null | Key | Default | Extra |
+-------+----------+------+-----+---------+-------+
| id    | int(11)  | YES  |     | NULL    |       |
| name  | char(15) | YES  |     | NULL    |       |
+-------+----------+------+-----+---------+-------+

二 测试

　比较符号的测试：<   >   =   !=  >=  <=

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  |     | NULL    |       |
| name   | varchar(20) | YES  |     | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> select count(*) from s1 where id=370000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.17 sec)

mysql> create index idx_id on s1(id);
Query OK, 0 rows affected (1.17 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> select count(*) from s1 where id=370000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where id>370000;
+----------+
| count(*) |
+----------+
|     6220 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where id<370000;
+----------+
| count(*) |
+----------+
|   369999 |
+----------+
1 row in set (0.21 sec)

mysql> select count(*) from s1 where id!=370000;
+----------+
| count(*) |
+----------+
|   376219 |
+----------+
1 row in set (0.20 sec)

mysql> drop index idx_id on s1;
Query OK, 0 rows affected (0.13 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> create index idx_name on s1(name);
Query OK, 0 rows affected (2.19 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  |     | NULL    |       |
| name   | varchar(20) | YES  | MUL | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> select count(*) from s1 where name='egon';
+----------+
| count(*) |
+----------+
|   376220 |
+----------+
1 row in set (0.25 sec)

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

注意事项：插入索引过和如果添加记录会改变树形的结构。

　　如果一个字段的重复率过高，如果条件成立，反而会拖慢查询的效率。如果条件不成立，查询时间会非常的块

　　尽量选择区分度较高的字段作为索引的字段。一般是在十条记录中有一条重复。

　　索引的字段不能够参与计算中，因为这样条件就不会明确，所以也要从第一条记录开始计算，这样就增大了查找的范围。这样也会非常耗时间的。

　逻辑符号的测试：  and  or  not

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  |     | NULL    |       |
| name   | varchar(20) | YES  | MUL | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> create index idx_id on s1(id);
Query OK, 0 rows affected (1.69 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  | MUL | NULL    |       |
| name   | varchar(20) | YES  | MUL | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> select * from s1 where id=370000 and name='egon';
+--------+------+--------+-------------------+
| id     | name | gender | email             |
+--------+------+--------+-------------------+
| 370000 | egon | male   | egon370000@oldboy |
+--------+------+--------+-------------------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' and id=370000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' or id=370000;
+----------+
| count(*) |
+----------+
|   376220 |
+----------+
1 row in set (0.83 sec)

mysql> select count(*) from s1 where id=370000 or name='egon';
+----------+
| count(*) |
+----------+
|   376220 |
+----------+
1 row in set (0.79 sec)

　在and的查找中：从左到右首先找到索引区分高的索引字段，如果条件成立，在去按照索引的字段去查找，如果不成立，就不会再去查找。and前面查找的条件如果不成立，那么查找的顺序就会非常的块，如果and前面的索引字段区分度低或者查找的范围大，同样也是耗费时间的，查找效率也会很低的。

　在or的查找中：从左到右一次查找记录，如果前面的条件成立，就不会查找后面的条件，如果前面的条件不成立，才会查找后面的条件。如果查找的索引字段区分度低，还是会拉低查找效率的，如果查找的索引字段区分度高的话，那就要看查找的范围，如果查找的范围过大，效率还是不会提升的，如果明确一个条件，或着范围小，这样就会提升查找的效率。

　范围的比较：in   between  like

mysql> select count(*) from s1 where id in (213,54343,354544);
+----------+
| count(*) |
+----------+
|        3 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where id between 100 and 3000;
+----------+
| count(*) |
+----------+
|     2901 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where id between 100 and 370000;
+----------+
| count(*) |
+----------+
|   369901 |
+----------+
1 row in set (0.19 sec)

mysql> select count(*) from s1 where id not in (1232,3423,24324);
+----------+
| count(*) |
+----------+
|   376217 |
+----------+
1 row in set (0.20 sec)

　联合索引的测试：and  or

　　联合索引就是将需要判断的字段联合起来创建一个索引。联合索引都是后面的字段联合第一个的。

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  |     | NULL    |       |
| name   | varchar(20) | YES  |     | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> create index idx_xxx on s1(name,gender,id,email);
Query OK, 0 rows affected (3.19 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> desc s1;
+--------+-------------+------+-----+---------+-------+
| Field  | Type        | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+-------+
| id     | int(11)     | YES  |     | NULL    |       |
| name   | varchar(20) | YES  | MUL | NULL    |       |
| gender | char(6)     | YES  |     | NULL    |       |
| email  | varchar(50) | YES  |     | NULL    |       |
+--------+-------------+------+-----+---------+-------+
4 rows in set (0.01 sec)

mysql> select count(*) from s1 where name='egon' and gender='male' and id>3000 and email='xxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.49 sec)

mysql> select count(*) from s1 where name='egon' and gender='male' and email='xxx' and id>3000;
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.49 sec)

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

mysql> select count(*) from s1 where name='egon' and gender='male' and id=3000;
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' and id=370000 and gender='male';
+----------+
| count(*) |
+----------+
|        1 |
+----------+
1 row in set (0.00 sec)

mysql> select count(*) from s1 where name='egon' and gender='male' and email='xxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.46 sec)

mysql> select count(*) from s1 where name='egon' and id=370000 and email='xxx';
+----------+
| count(*) |
+----------+
|        0 |
+----------+
1 row in set (0.30 sec)

　注意：如果联合索引的字段条件没有连续出现的话也会拖慢速度的。

　　什么叫做最左前缀：联合索引的查找顺序是从左到右依次查找，如果是and，查找出区分度高的索引字段先执行，如果条件成立在执行其他的条件，如果不成立，就不会执行其他的条件；如果是or，从左到右依次执行，如果条件成立就不会在去执行其他的索引条件。

　注意事项：应该将明确的条件字段放在右范围的条件字段的前面。

　　　　　　排序字段必须是索引字段。

　　　　　　对于联合索引，只要有第一个联合索引的字段，就会起作用，如果没有，就不会有效果。

　覆盖索引只要有联合索引的第一个字段就可以使用

　合并索引：创建多个单列索引，他们可以合并的使用，也可以单个使用。

详细资料访问：http://www.cnblogs.com/linhaifeng/articles/7274563.html#_label7