mysql性能优化

sql及索引优化

sql查询优化是日常工作中必不可少的，总体的优化思想是尽可能的减少IO操作和记录扫描行数

开启慢查询日志

查看慢查询日志是否打开

mysql> show variables like 'slow_query_log';

+----------------+-------+
| Variable_name | Value |
+----------------+-------+
| slow_query_log | OFF |
+----------------+-------+
1 row in set (0.00 sec)

mysql> set global slow_query_log=on;
Query OK, 0 rows affected (0.05 sec)

慢查询日志文件存储位置

mysql> show variables like '%slow_query_log_file%';
+---------------------+----------------------------------------------+
| Variable_name | Value |
+---------------------+----------------------------------------------+
| slow_query_log_file | C:xamppmysqldata80CEAE742547827-slow.log |
+---------------------+----------------------------------------------+
2 rows in set (0.00 sec)

是否记录没有使用索引的sql

mysql> show variables like '%log_queries_not_using%';
+-------------------------------+-------+
| Variable_name | Value |
+-------------------------------+-------+
| log_queries_not_using_indexes | OFF |

+-------------------------------+-------+
1 row in set (0.00 sec)

mysql> set global log_queries_not_using_indexes=on;
Query OK, 0 rows affected (0.00 sec)

执行时间大于N秒的SQL会被记录

mysql> show variables like '%long_query%';
+-----------------+-----------+
| Variable_name | Value |
+-----------------+-----------+
| long_query_time | 10.000000 |
+-----------------+-----------+
1 row in set (0.00 sec)

mysql> set global long_query_time=1;
Query OK, 0 rows affected (0.00 sec)

max和count语句优化

max和min优化通过对需要求最大值和最小值的字段建立索引，看下面的例子

索引前

mysql> explain select max(payment_date) from payment G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 16086 
Extra: NULL
1 row in set (0.00 sec)

mysql> create index ids_payment_date on payment(payment_date);
Query OK, 0 rows affected (0.30 sec)
Records: 0 Duplicates: 0 Warnings: 0

索引后

mysql> explain select max(payment_date) from payment G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away
1 row in set (0.00 sec)

Select tables optimized away表示sql已经是最优化了

group by语句优化

优化前

select actor.first_name, actor.last_name, count(*)
from sakila.film_actor
INNER JOIN sakila.actor USING(actor_id)
GROUP BY film_actor.actor_id

使用join子查询的方式优化后，actor表没有在使用文件排序和临时表

优化后

select actor.first_name, actor.last_name, c.cnt
from sakila.actor
INNER JOIN (
    select actor_id, count(*) as cnt from sakila.film_actor GROUP BY actor_id
) as c using(actor_id)

虽然优化后仍然扫描了200行的记录，但是actor表没有使用文件排序和临时表

limit查询优化

优化前

select film_id, description from sakila.film order by film_id limit 50, 5

优化后

select film_id, description from sakila.film where film_id > 50 and film_id <= 55 order by film_id limit 0, 5

从图中可以看出扫描记录数变成了5行，避免数据量大时扫描过多的记录

这中优化方法有个缺点，当记录是不连续的情况时，例如：删除51，52，53三条记录，这时50到55之间的记录就只有两条了

数据结构优化

系统配置优化

服务器硬件优化