Mysql优化----一条SQL百倍提升之旅

在实现业务逻辑的时候,有些复杂一点逻辑会用数据库子查询去实现,但是sql用子查询会带来性能问题,下面就一个例子来说明,怎么优化子查询,来提升查询速度

mysql> desc update t_student_info a 
    ->  set a.exstudentid='test01' 
    ->  where a.studentID in 
    ->  (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b);
 ---- -------------------- ---------------- ------------ ---------------- --------------- ------------- --------- ------ -------- ---------- ------------- 
| id | select_type        | table          | partitions | type           | possible_keys | key         | key_len | ref  | rows   | filtered | Extra       |
 ---- -------------------- ---------------- ------------ ---------------- --------------- ------------- --------- ------ -------- ---------- ------------- 
|  1 | UPDATE             | a              | NULL       | index          | NULL          | PRIMARY     | 24      | NULL | 221058 |   100.00 | Using where |
|  2 | DEPENDENT SUBQUERY |      | NULL       | index_subquery |    |  | 24      | func |    221 |   100.00 | Using index |
|  3 | DERIVED            | t_student_info | NULL       | ALL            | NULL          | NULL        | NULL    | NULL | 221058 |     1.00 | Using where |
 ---- -------------------- ---------------- ------------ ---------------- --------------- ------------- --------- ------ -------- ---------- ------------- 
3 rows in set (0.00 sec)

可以看到这个Update语句的执行计划,用的是DEPENDENT SUBQUERY,这样就需要循环的去执行这个只查询,效率会慢,能不能把这个只查询改一下,改成join查询呢,下面就是优化之后的sql写法

update t_student_info a set a.exstudentid='test01' where a.studentID in (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b)

mysql> desc update t_student_info a 
    ->        inner join 
    ->        (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b 
    ->        on a.studentID=b.studentID 
    ->        set a.exstudentid='test01';
 ---- ------------- ---------------- ------------ -------- --------------- --------- --------- ------------- -------- ---------- ------------- 
| id | select_type | table          | partitions | type   | possible_keys | key     | key_len | ref         | rows   | filtered | Extra       |
 ---- ------------- ---------------- ------------ -------- --------------- --------- --------- ------------- -------- ---------- ------------- 
|  1 | PRIMARY     |      | NULL       | ALL    | NULL          | NULL    | NULL    | NULL        |   2210 |   100.00 | NULL        |
|  1 | UPDATE      | a              | NULL       | eq_ref | PRIMARY       | PRIMARY | 24      | b.studentID |      1 |   100.00 | NULL        |
|  2 | DERIVED     | t_student_info | NULL       | ALL    | NULL          | NULL    | NULL    | NULL        | 221058 |     1.00 | Using where |
 ---- ------------- ---------------- ------------ -------- --------------- --------- --------- ------------- -------- ---------- ------------- 
3 rows in set (0.00 sec)

可以从执行计划中看到执行计划已经从DEPENDENT SUBQUERY变成了DERIVED,以驱动表去关联查询了,下面来看看实际执行效果

mysql> update t_student_info a set a.exstudentid='test01' where a.studentID in (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b);
Query OK, 0 rows affected (0.37 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a set a.exstudentid='test01' where a.studentID in (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b);
Query OK, 0 rows affected (0.39 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a inner join (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b on a.studentID=b.studentID set a.exstudentid='test01';
Query OK, 0 rows affected (0.07 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a inner join (select studentID from t_student_info where stdTYPE='8' and state=2 limit 10000,100) b on a.studentID=b.studentID set a.exstudentid='test01';
Query OK, 0 rows affected (0.07 sec)
Rows matched: 100  Changed: 0  Warnings: 0

为了排除因为物理读导致的干扰,没条sql都连续执行2遍,从执行结果可以看到,使用子查询的sql平均执行时间在370毫秒,而用inner join的sql平均执行时间在70毫秒,效率提升了5倍多,优化效果还是很明显的,小伙伴可能会觉得,才有5倍提升,其实优化之后的语句耗费时间的在limit 10000,100这里,如果改外limit 1,100大家再来看看对比效果

mysql> update t_student_info a inner join (select studentID from t_student_info where stdTYPE='8' and state=2 limit 1,100) b on a.studentID=b.studentID set a.exstudentid='test01';
Query OK, 0 rows affected (0.00 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a inner join (select studentID from t_student_info where stdTYPE='8' and state=2 limit 1,100) b on a.studentID=b.studentID set a.exstudentid='test01';
Query OK, 0 rows affected (0.00 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a set a.exstudentid='test01' where a.studentID in (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 1,100) b);
Query OK, 0 rows affected (0.31 sec)
Rows matched: 100  Changed: 0  Warnings: 0

mysql> update t_student_info a set a.exstudentid='test01' where a.studentID in (select studentID from (select studentID from t_student_info where stdTYPE='8' and state=2 limit 1,100) b);
Query OK, 0 rows affected (0.31 sec)
Rows matched: 100  Changed: 0  Warnings: 0

inner join的执行时间已经是几毫秒了,而子查询还是在310毫秒,这效果就分明显,提升了100多倍,这种方法优化,不仅适合in,还是适合exists的优化

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