MySQL索引优化的实际案例分析_MySQL

案例一：

一条sql执行非常的慢，执行时间为：

root@test 02:00:44
 
SELECT * FROM test_order_desc WHERE END_TIME>now() ORDER BY GMT_CREATE DESC,count_num DESC LIMIT 12, 12;
 
+---------+-----------+------------+------+---------------------+---------------------+-------------------
Data1.....................................................................................................
 
Data2.....................................................................................................
 
+---------+-----------+------------+------+---------------------+---------------------+-------------------
12 ROWS IN SET (0.49 sec)

执行计划如下：

root@test_db01:53:23
 
EXPLAIN SELECT * FROM test_order_desc WHERE END_TIME > now()
 ORDER BY GMT_CREATE DESC,count_num DESC LIMIT 12, 12;
 
+----+-------------+----------+-------+-----------------+-----------------+---------+------+--------+-----
 
| id | select_type | TABLE  | TYPE | possible_keys  | KEY  | key_len | REF | ROWS  | Extra   |
 
+----+-------------+----------+-------+-----------------+-----------------+---------+------+--------+-----
 
| 1 | SIMPLE   | test_order_desc | range | ind_hot_endtime | ind_hot_endtime | 9    | NULL | 113549 | USING WHERE; USING filesort |
 
+----+-------------+----------+-------+-----------------+-----------------+---------+------+--------+-----

Ind_hot_endtime索引为：

root@test_db01:52:45:SHOW INDEX FROM test_order_desc;
 
Ind_hot_endtime(end_time,count_num)

在注意到sql中满足过滤条件end_time>now()的有113549行，在加上剩余的条件中含有order by，这样会造成排序的结果集非常的大，执行非常的耗费资源；于是分析sql，在sql中包括了order by desc limit这样的排序条件后，新增适当的索引满足排序的条件，同时由于有limit的限制结果集，当扫描到满足条件的行数后退出查询，那么我们来看看优化效果：

添加索引：

root@test 02:01:06:ALTER TABLE test_order_desc ADD INDEX ind_gmt_create(gmt_create,count_num);
 
Query OK, 211945 ROWS affected (6.71 sec)
 
Records: 211945 Duplicates: 0 Warnings: 0

再次执行sql，观察其执行时间：

root@test 02:01:35:
 
SELECT * FROM test_order_desc WHERE END_TIME > now()  ORDER BY GMT_CREATE DESC,count_num DESC LIMIT 12, 12;
 
+---------+-----------+------------+------+---------------------+---------------------+
col2...................................................................................
 
+---------+-----------+------------+------+---------------------+---------------------+
 
Data1..................................................................................
 
Data2..................................................................................
 
+---------+-----------+------------+------+---------------------+---------------------+
 
12 ROWS IN SET (0.00 sec)

可以看到执行时间已经降到了毫秒以下,查看其执行计划：

root@test 02:01:42:
 
EXPLAIN SELECT * FROM test_order_desc WHERE END_TIME > now() ORDER BY GMT_CREATE DESC,count_num DESC LIMIT 12, 12;
 
+----+-------------+----------+-------+-----------------+----------------+---------+------+------+-------------+
 
| id | select_type | TABLE  | TYPE | possible_keys  | KEY | key_len | REF | ROWS | Extra |
 
+----+-------------+----------+-------+-----------------+----------------+---------+------+------+--------
 
| 1 | SIMPLE   | test_order_desc | INDEX | ind_hot_endtime | ind_gmt_create | 14   | NULL | 48 | USING WHERE |

可以看到优化器已经选择了ind_gmt_create索引扫描，这样的话就避免了对结果集进行排序的过程，同时优化器预估扫描14行数据就会得到满足查询条件的数据（END_TIME > now()），执行计划非常的理想。

root@127.0.0.1 : test_db 16:05:15:
EXPLAIN SELECT b.*,a.*,k.*  FROM instance b LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;

案例二：

root@127.0.0.1 : test_db 16:05:15:
EXPLAIN SELECT b.*,a.*,k.*  FROM instance b LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;

B表的idx_uid_stat_inid的索引列包括了（user_id，status，instance_no）：

我们从执行计划上分析来看，表的连接顺序为：b—>r_a—>a—>k，可以看到执行计划的第一行中需要扫描49212行的数据,同时由于status采用的是in的方式，instance_no即使在索引中也用不上，这样就导致了排序使用到了临时表,这也是导致sql执行慢的原因。我们看到sql中的最后一个排序为order by b.instance_no asc limit 37300,50，这里我们好像可以看到优化的曙光，调整数据库的索引以满足B表的排序需求：

root@127.0.0.1 : test_db 16:05:04 ALTER TABLE instance ADD INDEX ind_user_id(user_id,instance_no);
Query OK, 0 ROWS affected (0.56 sec)

调整索引后查看执行计划：

root@127.0.0.1 : test_db 16:09:42
EXPLAIN SELECT b.*,a.*,k.*  FROM instance b LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;

我们加上force index强制走我们新加的索引：

root@127.0.0.1 : test_db 16:10:24
EXPLAIN SELECT b.*,a.*,k.*  FROM instance b force INDEX (ind_user_id) LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;

可以看到在加上提示符后，使用到了我们新加的索引，扫描的行数为54580行，执行时间：

root@127.0.0.1 : test_db 16:10:30
SELECT b.*,a.*,k.*  FROM instance b force INDEX (ind_user_id) LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;
(0.49 sec)

原始的执行时间：

root@127.0.0.1 : test_db 16:10:51:
SELECT b.*,a.*,k.*  FROM instance b  LEFT OUTER JOIN image a ON b.image_id=a.image_id LEFT OUTER JOIN key_pair k ON b.key_pair_id=k.key_pair_id LEFT OUTER JOIN region_alias r_a ON r_a.region_no=b.region_no WHERE b.STATUS IN (1,8) AND  b.user_id = 21 AND r_a.big_region_no='regeion_xx' ORDER BY b.instance_no ASC LIMIT 37300,50;
(1.28 sec)

总结：
Order by desc/asc limit的优化技术有时候在你无法建立很好索引的时候，往往会得到意想不到的优化效果，但有时候有一定的局限性，优化器可能不会按照你既定的索引路径扫描，优化器需要考虑到查询列的过滤性以及limit的长度，当查询列的选择性非常高的时候，使用sort的成本是不高的，当查询列的选择性很低的时候，那么使用order by +limit的技术是很有效的。