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MySQL性能优化实战_MySQL

Jun 01, 2016 pm 01:54 PM
company develop database

过年这段时间由于线上数据库经常压力过大导致响应非常缓慢甚至死机,咬咬牙下大决心来解决效率不高的问题!

首先是由于公司秉承快速开发原则,频繁上线,导致每次忽视了性能问题!日积月累,所以导致系统越来越慢,所以如果你的系统查询语句本来就优化的很好了可能参考意义不大!

提取慢查询日志文件,应该在你的DataDir目录下面

通过程序处理慢查询文件,将文件格式的慢查询导入到数据库中:

1 mysql> desc slow_query;
2 +---------------+-------------+------+-----+---------+-------+
3 | Field         | Type        | Null | Key | Default | Extra |
4 +---------------+-------------+------+-----+---------+-------+
5 | Date          | varchar(32) | NO   |     |         |       | 查询发生的时间
6 | user          | varchar(64) | NO   |     |         |       |
7 | host          | varchar(64) | NO   |     |         |       |
8 | content       | text        | NO   |     |         |       | 将Statement进行Mask后的语句,便于Group By
9 | query_time    | int(11)     | NO   |     |         |       | 查询所用时间,直接性能指标
10 | lock_time     | int(11)     | YES  |     | 0       |       | 等待锁定的时间
11 | rows_sent     | int(11)     | YES  |     | 0       |       | 返回的结果行数
12 | rows_examined | int(11)     | YES  |     | 0       |       | 扫描行数
13 | statement     | text        | YES  |     | NULL    |       | 实际查询语句
14 +---------------+-------------+------+-----+---------+-------+ 

然后发挥您的想象力在这个表中尽力捕捉你想捕捉的,那类型语句压力最大、扫描行数最多、等锁最久……

比如:

优化后:

mysql> select sum(query_time)/count(*),count
(*),sum(query_time),min(Date),Max(Date) from slow where Date>'2008-02-20 22:50:52'and  Date+--------------------------+----------+-----------------+---------------------+---------------------+
| sum(query_time)/count(*) | count(*) | sum(query_time) | min(Date)           | Max(Date)           |
+--------------------------+----------+-----------------+---------------------+---------------------+
|                   5.7233 |     2197 |           12574 | 2008-02-20 22:51:16 | 2008-02-21 17:34:10 |
+--------------------------+----------+-----------------+---------------------+---------------------+
1 row in set (0.09 sec) 

优化前:

mysql> select sum(query_time)/count(*),count(*),sum(query_time),min(Date),Max(Date) from slow where Date>'2008-02-17 22:50:52' and  Date+--------------------------+----------+-----------------+---------------------+---------------------+
| sum(query_time)/count(*) | count(*) | sum(query_time) | min(Date)           | Max(Date)           |
+--------------------------+----------+-----------------+---------------------+---------------------+
|                   2.5983 |    16091 |           41810 | 2008-02-17 22:50:58 | 2008-02-18 17:34:34 |
+--------------------------+----------+-----------------+---------------------+---------------------+
1 row in set (0.15 sec)

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