本文介绍了性能帮助:SUBQUERY与JOIN的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

这是我的问题:

子查询2.7 secs

SUBQUERY 2.7 secs

SELECT SQL_NO_CACHE
  item_id

  FROM
    mtrt_items_searches

  WHERE
    search_id IN (
            SELECT
            SQL_NO_CACHE
                search_id
                FROM
                    mtrt_searches_groups
                WHERE
                    client_id =1
                GROUP BY
                    search_id

        )

    LIMIT 0,350000

+----+--------------------+----------------------+-------+---------------+-----------+---------+-------+--------+--------------------------+
| id | select_type        | table                | type  | possible_keys | key       | key_len | ref   | rows   | Extra                    |
+----+--------------------+----------------------+-------+---------------+-----------+---------+-------+--------+--------------------------+
|  1 | PRIMARY            | mtrt_items_searches  | index | NULL          | search_id | 12      | NULL  | 367362 | Using where; Using index |
|  2 | DEPENDENT SUBQUERY | mtrt_searches_groups | ref   | client_id     | client_id | 4       | const |     13 | Using where; Using index |
+----+--------------------+----------------------+-------+---------------+-----------+---------+-------+--------+--------------------------+

仅子查询需要0.0009秒才能返回以下数据,然后用此数据替换子查询,查询将在0.2 secs中运行:

The subquery alone takes 0.0009 secs to return the following data, and replacing the subquery with this data, the query runs in 0.2 secs:

SELECT SQL_NO_CACHE
    item_id

    FROM
        mtrt_items_searches
    WHERE
        search_id IN (
            1,2,3,4,5,6,7,8,9,10,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35
        )

    LIMIT 0,350000

+----+-------------+---------------------+-------+---------------+-----------+---------+------+--------+--------------------------+
| id | select_type | table               | type  | possible_keys | key       | key_len | ref  | rows   | Extra                    |
+----+-------------+---------------------+-------+---------------+-----------+---------+------+--------+--------------------------+
|  1 | SIMPLE      | mtrt_items_searches | index | search_id     | search_id | 12      | NULL | 367362 | Using where; Using index |
+----+-------------+---------------------+-------+---------------+-----------+---------+------+--------+--------------------------+

最后在0.4 secs中运行的JOIN:

Finally the JOIN running in 0.4 secs:

   SELECT SQL_NO_CACHE
        r.item_id

        FROM
            mtrt_items_searches r
        INNER JOIN
            mtrt_searches_groups sg
                ON r.search_id =sg.search_id
        WHERE
            sg.client_id =1
        GROUP BY
            r.item_id

        LIMIT 0,350000

+----+-------------+-------+------+---------------------+-----------+---------+------------------------+-------+----------------------------------------------+
| id | select_type | table | type | possible_keys       | key       | key_len | ref                    | rows  | Extra                                        |
+----+-------------+-------+------+---------------------+-----------+---------+------------------------+-------+----------------------------------------------+
|  1 | SIMPLE      | sg    | ref  | search_id,client_id | client_id | 4       | const                  |    13 | Using index; Using temporary; Using filesort |
|  1 | SIMPLE      | r     | ref  | search_id           | search_id | 4       | clubr_new.sg.search_id | 26240 | Using index                                  |
+----+-------------+-------+------+---------------------+-----------+---------+------------------------+-------+----------------------------------------------+

我正在尝试执行子查询或0.2 secs中的联接.有可能吗?

I'm trying to do either the subquery or the join in 0.2 secs. Is it possible?

推荐答案

尝试以下查询:

SELECT STRAIGHT_JOIN item_id
FROM (
    SELECT DISTINCT search_id
    FROM mtrt_searches_groups
    WHERE client_id = 1
) JOIN mtrt_items_searches USING(search_id)
LIMIT 0,350000

这篇关于性能帮助:SUBQUERY与JOIN的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

09-13 04:25