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。

MySQL的四种不同查询的分析

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。

MySQL的四种不同查询的分析

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;

秒客网

MySQL的四种不同查询的分析

相关文章