如何改进 MySQL 中的 Limit 子句

Question

我有一个有 10k 行的 posts 表，我想通过它创建分页。因此，我为此目的进行了下一个查询：

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MySQL ORDER BY / LIMIT performance: late row lookups那个话题，但是即使我把查询修改为下一个，问题依然存在：

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。我的目的是将评论表与 post 表连接起来，不幸的是，当我解释新查询时仍然遍历 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;  

你知道这种 MySQL 行为的原因是什么吗？

Answer 1

试试这个：

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

通过LIMIT 进行分页没有任何意义，但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)

关于您最近一次关于评论加入的 cmets。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              |
+----+-------------+------------+-------+---------------+---------+---------+------+------+--------------------------+

以及表格大小参考：

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)