实例1 使用索引优化DISTINCT操作

create table m11 (a int, b int, c int, d int, primary key(a)) engine=INNODB;

insert into m11 values (1,1,1,1),(2,2,2,2),(3,3,3,3),(4,4,4,4),(5,5,5,5),(6,6,6,6),(7,7,7,7),(8,8,8,8);

explain select distinct(a) from m11;

mysql> explain select distinct(a) from m11;

代码如下:

+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+| 1 | SIMPLE | m11 | NULL | index | PRIMARY | PRIMARY | 4 | NULL | 1 | 100.00 | Using index |+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+

2 这是使用索引优化DISTINCT操作的典型实例.

实例2 使用索引不能优化DISTINCT操作

create table m31 (a int, b int, c int, d int, primary key(a)) engine=MEMORY;

insert into m31 values (1,1,1,1),(2,2,2,2),(3,3,3,3),(4,4,4,4),(5,5,5,5),(6,6,6,6),(7,7,7,7),(8,8,8,8);

explain select distinct(a) from m31;

 mysql> explain select distinct(a) from m31;

代码如下:

+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+| 1 | SIMPLE | m31 | NULL | ALL | NULL | NULL | NULL | NULL | 8 | 100.00 | NULL |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+

2 对比实例1的建表语句,只是存储引擎不同.

3 为什么主键索引没有起作用? 难道MEMORY存储引擎上的索引不可使用?

实例3 使用索引可以优化DISTINCT操作的Memory表

create table m33 (a int, b int, c int, d int, INDEX USING BTREE (a)) engine=MEMORY;

insert into m33 values (1,1,1,1),(2,2,2,2),(3,3,3,3),(4,4,4,4),(5,5,5,5),(6,6,6,6),(7,7,7,7),(8,8,8,8);

explain select distinct(a) from m33;

 mysql> explain select distinct(a) from m33;

+----+-------------+-------+------------+-------+---------------+------+---------+------+------+----------+-------+| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |+----+-------------+-------+------------+-------+---------------+------+---------+------+------+----------+-------+| 1 | SIMPLE | m33 | NULL | index | NULL | a | 5 | NULL | 8 | 100.00 | NULL |+----+-------------+-------+------------+-------+---------------+------+---------+------+------+----------+-------+
说明:
1 'a'列上存在主键索引,MySQL可以利用索引(key列值表明使用了主键索引)完成了DISTINCT操作.

2 对比实例2,可以发现,二者都使用了Memory引擎. 但实例3指名使用Btree类型的索引.

3 实例2没有指定使用什么类型的索引,MySQL将采用默认值. MySQL手册上说:

As indicated by the engine name, MEMORY tables are stored in memory. They use hash indexes by default, which makes them very fast for single-value lookups, and very useful for creating temporary tables.

结论:

1 看索引对查询的影响,要注意索引的类型.

2 HASH索引适合等值查找,但不适合需要有序的场景,而Btree却适合有序的场景.

3 看查询执行计划,发现索引没有被使用,需要进一步考察索引的类型.

DISTINCT不能选择多个字段的解决方法
在实际应用中，我们经常要选择数据库某表中重复数据，通常我们是使用DISTINCT函数。

但DISTINCT只能对一个字段有效，比如：

sql="select DISTINCT title from Table where id>0"

当我们需要列出数据中的另一列，比如：

sql="select DISTINCT title,posttime from Table where id>0" 

得出的结果就不是我们想要的了，所以我们需要用另外的方法来解决这个问题。

下面的是我写的SQL语句，我不知道是不是很好，但愿有更好的人拿出来分享一下：

写法一：

sql = "Select DISTINCT(title),posttime From Table1 Where id>0"

写法二：

sql = "Select title,posttime From Table1 Where id>0 group by title,posttime"

写法三：

sql="select title,posttime from Table where id in (select min(id) from Table group by title)"