文章出处:http://inter12.iteye.com/blog/1430144
MYSQL的全表扫描,主键索引(聚集索引、第一索引),非主键索引(非聚集索引、第二索引),覆盖索引四种不同查询的分析
1.前置条件:
本次是基于小数据量,且数据块在一个页中的最理想情况进行分析,可能无具体的实际意义,但是可以借鉴到各种复杂条件下,因为原理是相同的,知小见大,见微知著!
打开语句分析并确认是否已经打开
- mysql> set profiling=1;
- Query OK, 0 rows affected (0.00 sec)
- mysql> select @@profiling;
- +-------------+
- | @@profiling |
- +-------------+
- | 1 |
- +-------------+
- 1 row in set (0.01 sec)
2.数据准备:
2.1全表扫描数据
- create table person4all(id int not null auto_increment, name varchar(30) not null, gender varchar(10) not null ,primary key(id));
- insert into person4all(name,gender) values("zhaoming","male");
- insert into person4all(name,gender) values("wenwen","female");
2.2根据主键查看数据
- create table person4pri(id int not null auto_increment, name varchar(30) not null, gender varchar(10) not null ,primary key(id));
- insert into person4pri(name,gender) values("zhaoming","male");
- insert into person4pri(name,gender) values("wenwen","female");
2.3根据非聚集索引查数据
- create table person4index(id int not null auto_increment, name varchar(30) not null, gender varchar(10) not null ,primary key(id) , index(gender));
- insert into person4index(name,gender) values("zhaoming","male");
- insert into person4index(name,gender) values("wenwen","female");
2.4根据覆盖索引查数据
- create table person4cindex(id int not null auto_increment, name varchar(30) not null, gender varchar(10) not null ,primary key(id) , index(name,gender));
- insert into person4cindex(name,gender) values("zhaoming","male");
- insert into person4cindex(name,gender) values("wenwen","female");
主要从以下几个方面分析:查询消耗的时间,走的执行计划等方面。
3.开工测试:
第一步:全表扫描
- mysql> select * from person4all ;
- +----+----------+--------+
- | id | name | gender |
- +----+----------+--------+
- | 1 | zhaoming | male |
- | 2 | wenwen | female |
- +----+----------+--------+
- 2 rows in set (0.00 sec)
查看其执行计划:
- mysql> explain select * from person4all;
- +----+-------------+------------+------+---------------+------+---------+------+------+-------+
- | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
- +----+-------------+------------+------+---------------+------+---------+------+------+-------+
- | 1 | SIMPLE | person4all | ALL | NULL | NULL | NULL | NULL | 2 | |
- +----+-------------+------------+------+---------------+------+---------+------+------+-------+
- 1 row in set (0.01 sec)
我们可以很清晰的看到走的是全表扫描,而没有走索引!
查询消耗的时间:
- mysql> show profiles;
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------+
- | Query_ID | Duration | Query |
- | 54 | 0.00177300 | select * from person4all |
- | 55 | 0.00069200 | explain select * from person4all |
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------+
全表扫描总共话了0.0017730秒
各个阶段消耗的时间是:
- mysql> show profile for query 54;
- +--------------------------------+----------+
- | Status | Duration |
- +--------------------------------+----------+
- | starting | 0.000065 |
- | checking query cache for query | 0.000073 |
- | Opening tables | 0.000037 |
- | System lock | 0.000024 |
- | Table lock | 0.000053 |
- | init | 0.000044 |
- | optimizing | 0.000022 |
- | statistics | 0.000032 |
- | preparing | 0.000030 |
- | executing | 0.000020 |
- | Sending data | 0.001074 |
- | end | 0.000091 |
- | query end | 0.000020 |
- | freeing items | 0.000103 |
- | storing result in query cache | 0.000046 |
- | logging slow query | 0.000019 |
- | cleaning up | 0.000020 |
- +--------------------------------+----------+
- 17 rows in set (0.00 sec)
第一次不走缓存的话,需要检查是否存在缓存中,打开表,初始化等操作,最大的开销在于返回数据。
第二步:根据主键查询数据。
- mysql> select name ,gender from person4pri where id in (1,2);
- +----------+--------+
- | name | gender |
- +----------+--------+
- | zhaoming | male |
- | wenwen | female |
- +----------+--------+
- 2 rows in set (0.01 sec)
查看其执行计划:
- mysql> explain select name ,gender from person4pri where id in (1,2);
- +----+-------------+------------+-------+---------------+---------+---------+------+------+-------------+
- | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
- +----+-------------+------------+-------+---------------+---------+---------+------+------+-------------+
- | 1 | SIMPLE | person4pri | range | PRIMARY | PRIMARY | 4 | NULL | 2 | Using where |
- +----+-------------+------------+-------+---------------+---------+---------+------+------+-------------+
- 1 row in set (0.00 sec)
从执行计划中我们可以看出,走的是范围索引。
再看其执行消耗的时间:
- mysql> show profiles;
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------+
- | Query_ID | Duration | Query |
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------+
- | 63 | 0.00135700 | select name ,gender from person4pri where id in (1,2) |
- | 64 | 0.00079200 | explain select name ,gender from person4pri where id in (1,2) |
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------+
- 15 rows in set (0.01 sec)
这次查询消耗时间为0.00079200。
查看各个阶段消耗的时间:
- mysql> show profile for query 63;
- +--------------------------------+----------+
- | Status | Duration |
- +--------------------------------+----------+
- | starting | 0.000067 |
- | checking query cache for query | 0.000146 |
- | Opening tables | 0.000342 |
- | System lock | 0.000027 |
- | Table lock | 0.000115 |
- | init | 0.000056 |
- | optimizing | 0.000032 |
- | statistics | 0.000069 |
- | preparing | 0.000039 |
- | executing | 0.000022 |
- | Sending data | 0.000100 |
- | end | 0.000075 |
- | query end | 0.000022 |
- | freeing items | 0.000158 |
- | storing result in query cache | 0.000045 |
- | logging slow query | 0.000019 |
- | cleaning up | 0.000023 |
- +--------------------------------+----------+
- 17 rows in set (0.00 sec)
看出最大的消耗也是在Sending data,第一次也是需要一些初始化操作。
第三步:根据非聚集索引查询
- mysql> select name ,gender from person4index where gender in ("male","female");
- +----------+--------+
- | name | gender |
- +----------+--------+
- | wenwen | female |
- | zhaoming | male |
- +----------+--------+
- 2 rows in set (0.00 sec)
查看器执行计划:
- mysql> explain select name ,gender from person4index where gender in ("male","female");
- +----+-------------+--------------+-------+---------------+--------+---------+------+------+-------------+
- | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
- +----+-------------+--------------+-------+---------------+--------+---------+------+------+-------------+
- | 1 | SIMPLE | person4index | range | gender | gender | 12 | NULL | 2 | Using where |
- +----+-------------+--------------+-------+---------------+--------+---------+------+------+-------------+
- 1 row in set (0.00 sec)
可以看出,走的也是范围索引。同主键查询,那么就看其消耗时间了
- mysql> show profiles;
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
- | Query_ID | Duration | Query |
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
- | 68 | 0.00106600 | select name ,gender from person4index where gender in ("male","female") |
- | 69 | 0.00092500 | explain select name ,gender from person4index where gender in ("male","female") |
- +----------+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
- 15 rows in set (0.00 sec)
这个非主键索引消耗的时间为:0.00106600,可以看出略大于组件索引消耗的时间。
看其具体消耗的阶段:
- mysql> show profile for query 68 ;
- +--------------------------------+----------+
- | Status | Duration |
- +--------------------------------+----------+
- | starting | 0.000059 |
- | checking query cache for query | 0.000111 |
- | Opening tables | 0.000085 |
- | System lock | 0.000023 |
- | Table lock | 0.000067 |
- | init | 0.000183 |
- | optimizing | 0.000031 |
- | statistics | 0.000139 |
- | preparing | 0.000035 |
- | executing | 0.000020 |
- | Sending data | 0.000148 |
- | end | 0.000024 |
- | query end | 0.000019 |
- | freeing items | 0.000043 |
- | storing result in query cache | 0.000042 |
- | logging slow query | 0.000017 |
- | cleaning up | 0.000020 |
- +--------------------------------+----------+
- 17 rows in set (0.00 sec)
看几个关键词的点;init,statistics,Sending data 这几个关键点上的消耗向比较主键的查询要大很多,特别是Sending data。因为若是走的非聚集索引,那么就需要回表进行再进行一次查询,多消耗一次IO。
第四部:根据覆盖索引查询数据
- mysql> select gender ,name from person4cindex where gender in ("male","female");
- +--------+----------+
- | gender | name |
- +--------+----------+
- | female | wenwen |
- | male | zhaoming |
- +--------+----------+
- 2 rows in set (0.01 sec)
这里需要注意的是,我的字段查询顺序变了,是gender,name而不在是前面的name,gender,这样是为了走覆盖索引。具体看效果吧
还是先看执行计划:
- mysql> explain select gender ,name from person4cindex where gender in ("male","female");
- +----+-------------+---------------+-------+---------------+------+---------+------+------+--------------------------+
- | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
- +----+-------------+---------------+-------+---------------+------+---------+------+------+--------------------------+
- | 1 | SIMPLE | person4cindex | index | NULL | name | 44 | NULL | 2 | Using where; Using index |
- +----+-------------+---------------+-------+---------------+------+---------+------+------+--------------------------+
- 1 row in set (0.00 sec)
最后栏Extra中表示走的就是覆盖索引。
看消耗的时间吧:
- mysql> show profiles;
- +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+
- | Query_ID | Duration | Query |
- +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+
- | 83 | 0.00115400 | select gender ,name from person4cindex where gender in ("male","female") |
- | 84 | 0.00074000 | explain select gender ,name from person4cindex where gender in ("male","female") |
- +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+
我们看到消耗的时间是0.00115400,看这个数字好像挺高的,那么都花在什么地方了呢?
看下具体的消耗情况:
- mysql> show profile for query 83 ;
- +--------------------------------+----------+
- | Status | Duration |
- +--------------------------------+----------+
- | starting | 0.000083 |
- | checking query cache for query | 0.000113 |
- | Opening tables | 0.000039 |
- | System lock | 0.000026 |
- | Table lock | 0.000075 |
- | init | 0.000128 |
- | optimizing | 0.000193 |
- | statistics | 0.000056 |
- | preparing | 0.000038 |
- | executing | 0.000021 |
- | Sending data | 0.000121 |
- | end | 0.000042 |
- | query end | 0.000021 |
- | freeing items | 0.000112 |
- | storing result in query cache | 0.000043 |
- | logging slow query | 0.000021 |
- | cleaning up | 0.000022 |
- +--------------------------------+----------+
- 17 rows in set (0.00 sec)
很惊奇吧,在初始化和优化上消耗了这么多时间,取数据基恩差不多。
总结:
有了上面这些数据,那么我们整理下吧。未存在缓存下的数据。
看这个表,全表扫描最慢,我们可以理解,同时主键查询比覆盖所有扫描慢也还能接受,但是为什么主键扫描会比非主键扫描慢?而且非主键查询需要消耗的1次查询的io+一次回表的查询IO,理论上是要比主键扫描慢,而出来的数据缺不是如此。那么就仔细看下是个查询方式在各个主要阶段消耗的时间吧。
查询是否存在缓存,打开表及锁表这些操作时间是差不多,我们不会计入。具体还是看init,optimizing等环节消耗的时间。
1.从这个表中,我们看到非主键索引和覆盖索引在准备时间上需要开销很多的时间,预估这两种查询方式都需要进行回表操作,所以花在准备上更多时间。
2.第二项optimizing上,可以清晰知道,覆盖索引话在优化上大量的时间,这样在二级索引上就无需回表。
3. Sendingdata,全表扫描慢就慢在这一项上,因为是加载所有的数据页,所以花费在这块上时间较大,其他三者都差不多。
4. 非主键查询话在freeingitems上时间最少,那么可以看出它在读取数据块的时候最少。
5.相比较主键查询和非主键查询,非主键查询在Init,statistics都远高于主键查询,只是在freeingitems开销时间比主键查询少。因为这里测试数据比较少,但是我们可以预见在大数据量的查询上,不走缓存的话,那么主键查询的速度是要快于非主键查询的,本次数据不过是太小体现不出差距而已。
6.在大多数情况下,全表扫描还是要慢于索引扫描的。
tips:
过程中的辅助命令:
1.清楚缓存
reset query cache ;
flush tables;
2.查看表的索引:
show index from tablename;