MySQL的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;
原文链接：http://inter12.iteye.com/blog/1430144