(已编辑)有关该应用程序的详细信息,请参阅: Simple but heavy application consuming a lot of resources. How to Optimize? (采用的解决方案是使用连接和全文搜索)
我有以下查询在25秒内运行大约500.000行。如果我删除了ORDER,则需要0.5秒。
Fisrt测试
保持ORDER
并删除所有t。和tu。列,查询需要7秒。
第二次测试
如果我在i.created_at字段中添加或删除INDEX,则响应时间保持不变。
QUERY:
**已编辑:我已注意到按顺序排列并按顺序排列查询(我在查询中也获得了一点点改变连接。增益为10秒,但完全是问题遗迹)。通过修改,EXPLAIN已停止返回filesort,但仍然返回“using temporary”**
SELECT SQL_NO_CACHE
DISTINCT `i`.`id`,
`i`.`entity`,
`i`.`created_at`,
`i`.`collected_at`,
`t`.`status_id` AS `twt_status_id`,
`t`.`user_id` AS `twt_user_id`,
`t`.`content` AS `twt_content`,
`tu`.`id` AS `twtu_id`,
`tu`.`screen_name` AS `twtu_screen_name`,
`tu`.`profile_image` AS `twtu_profile_image`
FROM `mtrt_items` AS `i`
LEFT JOIN `mtrt_users` AS `u` ON i.user_id =u.id
LEFT JOIN `twt_tweets_content` AS `t` ON t.id =i.id
LEFT JOIN `twt_users` AS `tu` ON u.id = tu.id
INNER JOIN `mtrt_items_searches` AS `r` ON i.id =r.item_id
INNER JOIN `mtrt_searches` AS `s` ON s.id =r.search_id
INNER JOIN `mtrt_searches_groups` AS `sg` ON sg.search_id =s.id
INNER JOIN `mtrt_search_groups` AS `g` ON sg.group_id =g.id
INNER JOIN `account_clients` AS `c` ON g.client_id =c.id
ORDER BY `i`.`created_at` DESC
LIMIT 100 OFFSET 0
以下是EXPLAIN
(已编辑):
+----+-------------+-------+--------+--------------------+-----------+---------+------------------------+------+------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+--------------------+-----------+---------+------------------------+------+------------------------------+
| 1 | SIMPLE | c | index | PRIMARY | PRIMARY | 4 | NULL | 1 | Using index; Using temporary |
| 1 | SIMPLE | g | ref | PRIMARY,client_id | client_id | 4 | clubr_new.c.id | 3 | Using index |
| 1 | SIMPLE | sg | ref | group_id,search_id | group_id | 4 | clubr_new.g.id | 1 | Using index |
| 1 | SIMPLE | s | eq_ref | PRIMARY | PRIMARY | 4 | clubr_new.sg.search_id | 1 | Using index |
| 1 | SIMPLE | r | ref | search_id,item_id | search_id | 4 | clubr_new.s.id | 4359 | Using where |
| 1 | SIMPLE | i | eq_ref | PRIMARY | PRIMARY | 8 | clubr_new.r.item_id | 1 | |
| 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 8 | clubr_new.i.user_id | 1 | Using index |
| 1 | SIMPLE | t | eq_ref | PRIMARY | PRIMARY | 4 | clubr_new.i.id | 1 | |
| 1 | SIMPLE | tu | eq_ref | PRIMARY | PRIMARY | 8 | clubr_new.u.id | 1 | |
+----+-------------+-------+--------+--------------------+-----------+---------+------------------------+------+------------------------------+
这是mtrt_items
表:
+--------------+-------------------------------------------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------------+-------------------------------------------------------+------+-----+---------+----------------+
| id | bigint(20) | NO | PRI | NULL | auto_increment |
| entity | enum('twitter','facebook','youtube','flickr','orkut') | NO | MUL | NULL | |
| user_id | bigint(20) | NO | MUL | NULL | |
| created_at | datetime | NO | MUL | NULL | |
| collected_at | datetime | NO | | NULL | |
+--------------+-------------------------------------------------------+------+-----+---------+----------------+
CREATE TABLE `mtrt_items` (
`id` bigint(20) NOT NULL AUTO_INCREMENT,
`entity` enum('twitter','facebook','youtube','flickr','orkut') COLLATE utf8_unicode_ci NOT NULL,
`user_id` bigint(20) NOT NULL,
`created_at` datetime NOT NULL,
`collected_at` datetime NOT NULL,
PRIMARY KEY (`id`),
KEY `mtrt_user_id` (`user_id`),
KEY `entity` (`entity`),
KEY `created_at` (`created_at`),
CONSTRAINT `mtrt_items_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `mtrt_users` (`id`) ON DELETE CASCADE
) ENGINE=InnoDB AUTO_INCREMENT=309650 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
twt_tweets_content
是MyISAM,也用于fulltext
次搜索:
+-----------+--------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-----------+--------------+------+-----+---------+-------+
| id | int(11) | NO | PRI | NULL | |
| user_id | int(11) | NO | MUL | NULL | |
| status_id | varchar(100) | NO | MUL | NULL | |
| content | varchar(200) | NO | MUL | NULL | |
+-----------+--------------+------+-----+---------+-------+
答案 0 :(得分:6)
不是将Order By
放入主查询中,而是将其包装起来,如下所示:
SELECT * FROM (
... your query
) ORDER BY `created at`
查看查询计划。您将发现在您的情况下,在执行外部联接之前,在表mtrt_items
上执行排序。在我部分提供的重写中,排序在外连接之后应用,并应用于更小的集合。
<强>更新强>
假设LIMIT正在应用于大型集合(500,000?),看起来您可以在执行任何连接之前执行顶部。
SELECT * from (
SELECT
`id`, ... `created_at`, ...
ORDER BY `i`.`created_at` DESC
LIMIT 100 OFFSET 0) as i
LEFT JOIN `mtrt_users` AS `u` ON i.user_id =u.id
LEFT JOIN `twt_tweets_content` AS `t` ON t.id =i.id
LEFT JOIN `twt_users` AS `tu` ON t.user_id = tu.id
INNER JOIN `mtrt_items_searches` AS `r` ON i.id =r.item_id
INNER JOIN `mtrt_searches` AS `s` ON s.id =r.search_id
INNER JOIN `mtrt_searches_groups` AS `sg` ON sg.search_id =s.id
INNER JOIN `mtrt_search_groups` AS `g` ON sg.group_id =g.id
INNER JOIN `account_clients` AS `c` ON g.client_id =c.id
GROUP BY i.id
答案 1 :(得分:0)
不要在初始查询中包含 VARCHAR / TEXT 字段。这将使用 MEMORY 引擎创建排序所需的TEMPORARY表,这将显着提高效率。您可以稍后使用其他查询收集文本字段,无需任何排序,只需在 PRIMARY KEY 字段中使用条件并合并脚本中的数据(假设您使用的是)。
还要删除任何实际上没有从中获取任何数据的 JOINs (INNER或OUTER)。