mysql的分页比较简单,只需要limit offset,length就可以获取数据了,但是当offset和length比较大的时候,mysql明显性能下降
1.子查询优化法
先找出第一条数据,然后大于等于这条数据的id就是要获取的数据
缺点:数据必须是连续的,可以说不能有where条件,where条件会筛选数据,导致数据失去连续性
实验下
- mysql> set profiling=1;
- Query OK, 0 rows affected (0.00 sec)
-
- mysql> select count(*) from Member;
- +
- | count(*) |
- +
- | 169566 |
- +
- 1 row in set (0.00 sec)
-
- mysql> pager grep !~-
- PAGER set to 'grep !~-'
-
- mysql> select * from Member limit 10, 100;
- 100 rows in set (0.00 sec)
-
- mysql> select * from Member where MemberID >= (select MemberID from Member limit 10,1) limit 100;
- 100 rows in set (0.00 sec)
-
- mysql> select * from Member limit 1000, 100;
- 100 rows in set (0.01 sec)
-
- mysql> select * from Member where MemberID >= (select MemberID from Member limit 1000,1) limit 100;
- 100 rows in set (0.00 sec)
-
- mysql> select * from Member limit 100000, 100;
- 100 rows in set (0.10 sec)
-
- mysql> select * from Member where MemberID >= (select MemberID from Member limit 100000,1) limit 100;
- 100 rows in set (0.02 sec)
-
- mysql> nopager
- PAGER set to stdout
-
-
- mysql> show profiles\G
- *************************** 1. row ***************************
- Query_ID: 1
- Duration: 0.00003300
- Query: select count(*) from Member
-
- *************************** 2. row ***************************
- Query_ID: 2
- Duration: 0.00167000
- Query: select * from Member limit 10, 100
- *************************** 3. row ***************************
- Query_ID: 3
- Duration: 0.00112400
- Query: select * from Member where MemberID >= (select MemberID from Member limit 10,1) limit 100
-
- *************************** 4. row ***************************
- Query_ID: 4
- Duration: 0.00263200
- Query: select * from Member limit 1000, 100
- *************************** 5. row ***************************
- Query_ID: 5
- Duration: 0.00134000
- Query: select * from Member where MemberID >= (select MemberID from Member limit 1000,1) limit 100
-
- *************************** 6. row ***************************
- Query_ID: 6
- Duration: 0.09956700
- Query: select * from Member limit 100000, 100
- *************************** 7. row ***************************
- Query_ID: 7
- Duration: 0.02447700
- Query: select * from Member where MemberID >= (select MemberID from Member limit 100000,1) limit 100
mysql> set profiling=1;
Query OK, 0 rows affected (0.00 sec)
mysql> select count(*) from Member;
+----------+
| count(*) |
+----------+
| 169566 |
+----------+
1 row in set (0.00 sec)
mysql> pager grep !~-
PAGER set to 'grep !~-'
mysql> select * from Member limit 10, 100;
100 rows in set (0.00 sec)
mysql> select * from Member where MemberID >= (select MemberID from Member limit 10,1) limit 100;
100 rows in set (0.00 sec)
mysql> select * from Member limit 1000, 100;
100 rows in set (0.01 sec)
mysql> select * from Member where MemberID >= (select MemberID from Member limit 1000,1) limit 100;
100 rows in set (0.00 sec)
mysql> select * from Member limit 100000, 100;
100 rows in set (0.10 sec)
mysql> select * from Member where MemberID >= (select MemberID from Member limit 100000,1) limit 100;
100 rows in set (0.02 sec)
mysql> nopager
PAGER set to stdout
mysql> show profiles\G
*************************** 1. row ***************************
Query_ID: 1
Duration: 0.00003300
Query: select count(*) from Member
*************************** 2. row ***************************
Query_ID: 2
Duration: 0.00167000
Query: select * from Member limit 10, 100
*************************** 3. row ***************************
Query_ID: 3
Duration: 0.00112400
Query: select * from Member where MemberID >= (select MemberID from Member limit 10,1) limit 100
*************************** 4. row ***************************
Query_ID: 4
Duration: 0.00263200
Query: select * from Member limit 1000, 100
*************************** 5. row ***************************
Query_ID: 5
Duration: 0.00134000
Query: select * from Member where MemberID >= (select MemberID from Member limit 1000,1) limit 100
*************************** 6. row ***************************
Query_ID: 6
Duration: 0.09956700
Query: select * from Member limit 100000, 100
*************************** 7. row ***************************
Query_ID: 7
Duration: 0.02447700
Query: select * from Member where MemberID >= (select MemberID from Member limit 100000,1) limit 100
从结果中可以得知,当偏移1000以上使用子查询法可以有效的提高性能。
2.倒排表优化法 倒排表法类似建立索引,用一张表来维护页数,然后通过高效的连接得到数据
缺点:只适合数据数固定的情况,数据不能删除,维护页表困难
3.反向查找优化法 当偏移超过一半记录数的时候,先用排序,这样偏移就反转了
缺点:order by优化比较麻烦,要增加索引,索引影响数据的修改效率,并且要知道总记录数
,偏移大于数据的一半
引用
limit偏移算法:
正向查找: (当前页 - 1) * 页长度
反向查找: 总记录 - 当前页 * 页长度
做下实验,看看性能如何
总记录数:1,628,775
每页记录数: 40
总页数:1,628,775 / 40 = 40720
中间页数:40720 / 2 = 20360
第21000页
正向查找SQL:
- SELECT * FROM `abc` WHERE `BatchID` = 123 LIMIT 839960, 40
SELECT * FROM `abc` WHERE `BatchID` = 123 LIMIT 839960, 40
时间:1.8696 秒
反向查找sql:
- SELECT * FROM `abc` WHERE `BatchID` = 123 ORDER BY InputDate DESC LIMIT 788775, 40
SELECT * FROM `abc` WHERE `BatchID` = 123 ORDER BY InputDate DESC LIMIT 788775, 40
时间:1.8336 秒
第30000页
正向查找SQL:
- SELECT * FROM `abc` WHERE `BatchID` = 123 LIMIT 1199960, 40
SELECT * FROM `abc` WHERE `BatchID` = 123 LIMIT 1199960, 40
时间:2.6493 秒
反向查找sql:
- SELECT * FROM `abc` WHERE `BatchID` = 123 ORDER BY InputDate DESC LIMIT 428775, 40
SELECT * FROM `abc` WHERE `BatchID` = 123 ORDER BY InputDate DESC LIMIT 428775, 40
时间:1.0035 秒
注意,反向查找的结果是是降序desc的,并且InputDate是记录的插入时间,也可以用主键联合索引,但是不方便。
4.limit限制优化法 把limit偏移量限制低于某个数。。超过这个数等于没数据,我记得alibaba的dba说过他们是这样做的
5.只查索引法 总结:limit的优化限制都比较多,所以实际情况用或者不用只能具体情况具体分析了。页数那么后,基本很少人看的。。。