如何改进 MySQL 中的 Limit 子句

How to improve Limit clause in MySQL

我有 10k 行的 posts table,我想以此创建分页。所以我有下一个查询:

SELECT post_id
    FROM posts
    LIMIT 0, 10;

当我 Explain 该查询时,我得到下一个结果:

所以我不明白为什么 MySql 需要遍历 9976 行才能找到前 10 行?如果有人帮助我优化此查询,我将非常感激。

我也知道那个话题MySQL ORDER BY / LIMIT performance: late row lookups,但是即使我将查询修改为下一个,问题仍然存在:

SELECT  t.post_id
FROM    (
        SELECT  post_id
        FROM    posts
        ORDER BY
                post_id
        LIMIT 0, 10
        ) q 
JOIN    posts t 
ON      q.post_id = t.post_id

更新

@pala_ 的解决方案非常适合上述简单情况,但现在我正在使用 inner join 测试更复杂的查询。我的目的是将评论 table 与 post table 结合起来,不幸的是,当我解释新查询时,它仍然遍历 9976 行。

Select comm.comment_id 
from comments as comm 
    inner join (
        SELECT post_id 
        FROM posts 
        ORDER BY post_id 
        LIMIT 0, 10
    ) as paged_post on comm.post_id = paged_post.post_id;  

您是否知道这种 MySQL 行为的原因是什么?

试试这个:

SELECT post_id
    FROM posts
    ORDER BY post_id DESC
    LIMIT 0, 10;

通过 LIMIT 分页在没有排序的情况下没有多大意义,它应该可以解决您的问题。

mysql> explain select * from foo;
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| id | select_type | table | type  | possible_keys | key     | key_len | ref  | rows | Extra       |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
|  1 | SIMPLE      | foo   | index | NULL          | PRIMARY | 4       | NULL |   20 | Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
1 row in set (0.00 sec)

mysql> explain select * from foo limit 0, 10;
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| id | select_type | table | type  | possible_keys | key     | key_len | ref  | rows | Extra       |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
|  1 | SIMPLE      | foo   | index | NULL          | PRIMARY | 4       | NULL |   20 | Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
1 row in set (0.00 sec)

mysql> explain select * from foo order by id desc limit 0, 10;
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| id | select_type | table | type  | possible_keys | key     | key_len | ref  | rows | Extra       |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
|  1 | SIMPLE      | foo   | index | NULL          | PRIMARY | 4       | NULL |   10 | Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
1 row in set (0.00 sec)

关于您对评论加入的最后评论。你有 comment(post_id) 的索引吗?使用我的测试数据,我得到以下结果:

mysql> alter table comments add index pi (post_id);
Query OK, 0 rows affected (0.15 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> explain select c.id from  comments c inner join (select id from posts o order by id  limit 0, 10) p on c.post_id = p.id;
+----+-------------+------------+-------+---------------+---------+---------+------+------+--------------------------+
| id | select_type | table      | type  | possible_keys | key     | key_len | ref  | rows | Extra                    |
+----+-------------+------------+-------+---------------+---------+---------+------+------+--------------------------+
|  1 | PRIMARY     | <derived2> | ALL   | NULL          | NULL    | NULL    | NULL |   10 |                          |
|  1 | PRIMARY     | c          | ref   | pi            | pi      | 5       | p.id |    4 | Using where; Using index |
|  2 | DERIVED     | o          | index | NULL          | PRIMARY | 4       | NULL |   10 | Using index              |
+----+-------------+------------+-------+---------------+---------+---------+------+------+--------------------------+

table 尺寸参考:

mysql> select count(*) from posts;
+----------+
| count(*) |
+----------+
|    15021 |
+----------+
1 row in set (0.01 sec)

mysql> select count(*) from comments;
+----------+
| count(*) |
+----------+
|     1000 |
+----------+
1 row in set (0.00 sec)