今天本来想看下mysql的一条语句在MYSQL引擎中是如何的处理,无意中发现了很多其他的东西,就整理下吧。
查看SQL的执行情况:
1.通过show processlist 来查看系统的执行情况!
mysql> show processlist ; +----+------+-----------+-------+---------+------+-------+------------------+ | Id | User | Host | db | Command | Time | State | Info | +----+------+-----------+-------+---------+------+-------+------------------+ | 41 | root | localhost | mysql | Query | 0 | NULL | show processlist | +----+------+-----------+-------+---------+------+-------+------------------+ 1 row in set (0.00 sec)
该命令一般用于实时的去查看系统中运行较慢的SQL。
2.通过profiling来进行查看
这个命令是查看SQL的执行时间,能很直观的看出快慢。
2.1查看系统值:0代表还是关闭着分析功能
mysql> select @@profiling;
+-------------+
| @@profiling |
+-------------+
| 0 |
+-------------+
1 row in set (0.00 sec)
2.2打开工具
mysql> set profiling=1; Query OK, 0 rows affected (0.00 sec) mysql> select @@profiling; +-------------+ | @@profiling | +-------------+ | 1 | +-------------+ 1 row in set (0.00 sec)
2.3准备基础数据
create table name ( id int not null auto_increment, first_name varchar(30) not null, last_name varchar(30) not null, primary key (id), index (last_name,first_name) ) insert into name(first_name,last_name) values("xue","zhaoming") insert into name(first_name,last_name) values("xue","zhaoyue") commit; select * from name ; select * from name ;
2.4 好戏开始了
mysql> show profiles; +----------+------------+----------------------------------------------------------------+ | Query_ID | Duration | Query | +----------+------------+----------------------------------------------------------------+ | 8 | 0.00074500 | insert into name(first_name,last_name) values("xue","zhaoyue") | | 9 | 0.00021200 | commit | | 10 | 0.00063700 | select * from name | | 11 | 0.00026100 | select * from name
通过上面的大家可以很清晰的看到在执行两边的select * from name语句的时候实际执行的效率是不一样。那么我们来具体看看为什么不一样的。
mysql> SHOW PROFILE FOR QUERY 10; +--------------------------------+----------+ | Status | Duration | +--------------------------------+----------+ | starting | 0.000048 | | checking query cache for query | 0.000231 | ---检查是否在缓存中 | Opening tables | 0.000024 | ---打开表 | System lock | 0.000014 | ---锁系统 | Table lock | 0.000032 | ---锁表 | init | 0.000027 | ---初始化 | optimizing | 0.000013 | ---优化查询 | statistics | 0.000019 | | preparing | 0.000018 | ---准备 | executing | 0.000011 | ---执行 | Sending data | 0.000075 | | end | 0.000014 | | query end | 0.000010 | | freeing items | 0.000057 | | storing result in query cache | 0.000022 | ---将结果放到缓存中 | logging slow query | 0.000010 | --- | cleaning up | 0.000012 | +--------------------------------+----------+ 17 rows in set (0.00 sec)
具体的查询过程如上面所示,那么为什么第二次的查看就快了呢?简单,看下第二次的查询信息
mysql> SHOW PROFILE FOR QUERY 11; +--------------------------------+----------+ | Status | Duration | +--------------------------------+----------+ | starting | 0.000084 | | checking query cache for query | 0.000028 | | checking privileges on cached | 0.000028 | | sending cached result to clien | 0.000081 | | logging slow query | 0.000019 | | cleaning up | 0.000021 | +--------------------------------+----------+ 6 rows in set (0.00 sec)
对比两个执行过程,我们可以很清晰的看到为什么第二次的查看快了,因为是直接从缓存中查找数据了。
以上具体的信息都是从 INFORMATION_SCHEMA.PROFILING 这张表中取得的。这张表记录了所有的各个步骤的执行时间及相关信息。若是希望得到所有的执行结果。
select * from INFORMATION_SCHEMA.PROFILING where query_id = 11;
查看一次查询消耗的总时间:
select min(seq), sum(duration) from information_schema.profiling where query_id = 2
3.查看slow_log表 + mysqldumpslow 工具查看慢日志
内容以后再补上。详细的说明可以看下面的文档:
http://dev.mysql.com/doc/refman/5.1/en/slow-query-log.html
4.第三方工具了
这个就是自己写脚本来监控了,可以采用perl来搞。
5.还有就是用explain来查看具体的执行计划。
mysql> explain select * from name; +----+-------------+-------+------+---------------+------+---------+------+------+-------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+------+---------------+------+---------+------+------+-------+ | 1 | SIMPLE | name | ALL | NULL | NULL | NULL | NULL | 2 | | +----+-------------+-------+------+---------------+------+---------+------+------+-------+ 1 row in set (0.00 sec)
针对这个会在后面补上一个完整的如何查看计划的文档。