带标签和 GROUP_CONCAT 的产品视图

发布于 2024-11-07 13:45:36 字数 931 浏览 1 评论 0原文

我在我的应用程序上使用 Sphinx 进行全文搜索。我使用 view 来过滤 products 表中的数据,并为该视图建立索引。现在,我在产品表下有一个硬编码字段及其相关标签,但这不太好,因为标签可能会发生变化,而且我每次都必须操作硬编码字段。

所以我想我可以使用 GROUP_CONCAT 创建视图,用如下语法列出所有相关标签:

SELECT p.id AS id, GROUP_CONCAT(t.tag SEPARATOR '|') AS tags,
UNIX_TIMESTAMP(p.created) AS created
FROM products p
INNER JOIN products_tags pt ON pt.product_id = p.id
INNER JOIN tags t ON t.id = pt.tag_id
AND p.deleted = 0
AND (p.images IS NOT NULL OR p.images <> '')
AND p.status LIKE 'listed'
GROUP BY p.id;

这个查询的问题是它需要很长时间才能运行。真的很慢。如果只检索一条记录,最多需要 5 秒。这是 EXPLAIN 输出:

1, SIMPLE, pt, ALL, , , , , 165029, Using temporary; Using filesort
1, SIMPLE, p, eq_ref, PRIMARY, PRIMARY, 4, trych_default.pt.product_id, 1, Using where
1, SIMPLE, t, eq_ref, PRIMARY, PRIMARY, 4, trych_default.pt.tag_id, 1, 

我想知道是否有任何方法可以改进查询,或者可能有更好的解决方案来解决我的问题。谢谢!

I use Sphinx for fulltext search on my app. I use a view to filter the data from a products table and Sphinx indexes this view. Right now I have a hard coded field under the products table with it's related tags, but that is not so good as tags might change and I would have to manipulate the hard coded field every time.

So I was thinking that I could create the view with GROUP_CONCAT, listing all the related tags for me with a syntax like this:

SELECT p.id AS id, GROUP_CONCAT(t.tag SEPARATOR '|') AS tags,
UNIX_TIMESTAMP(p.created) AS created
FROM products p
INNER JOIN products_tags pt ON pt.product_id = p.id
INNER JOIN tags t ON t.id = pt.tag_id
AND p.deleted = 0
AND (p.images IS NOT NULL OR p.images <> '')
AND p.status LIKE 'listed'
GROUP BY p.id;

The problem with this query is that it takes ages to run. It's really slow. To retrieve only one record, it takes up to 5 seconds. This is the EXPLAIN output:

1, SIMPLE, pt, ALL, , , , , 165029, Using temporary; Using filesort
1, SIMPLE, p, eq_ref, PRIMARY, PRIMARY, 4, trych_default.pt.product_id, 1, Using where
1, SIMPLE, t, eq_ref, PRIMARY, PRIMARY, 4, trych_default.pt.tag_id, 1, 

I wonder if there is any way to improve the query or maybe a better solution to my problem. Thanks!

如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。

扫码二维码加入Web技术交流群

发布评论

需要 登录 才能够评论, 你可以免费 注册 一个本站的账号。

评论(1

审判长 2024-11-14 13:45:36

您可能缺少索引。使用以下架构,相同的查询命中每个表的索引:

CREATE TABLE `products` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `deleted` tinyint(1) unsigned NOT NULL DEFAULT '0',
  `status` varchar(255) NOT NULL DEFAULT 'listed',
  `images` varchar(255) DEFAULT NULL,
  `created` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `tags` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `tag` varchar(255) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `products_tags` (
  `product_id` int(11) NOT NULL,
  `tag_id` int(11) NOT NULL DEFAULT '0',
  PRIMARY KEY (`product_id`,`tag_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

以下是 EXPLAIN 查询的结果:

EXPLAIN SELECT p.id AS id, GROUP_CONCAT(t.tag SEPARATOR '|') AS tags,
UNIX_TIMESTAMP(p.created) AS created
FROM products p
INNER JOIN products_tags pt ON pt.product_id = p.id
INNER JOIN tags t ON t.id = pt.tag_id
WHERE p.deleted = 0
AND (p.images IS NOT NULL OR p.images <> '')
AND p.status LIKE 'listed'
GROUP BY p.id;

+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
| id | select_type | table | type   | possible_keys | key     | key_len | ref            | rows | Extra       |
+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
|  1 | SIMPLE      | p     | index  | PRIMARY       | PRIMARY | 4       | NULL           |    1 | Using where |
|  1 | SIMPLE      | pt    | ref    | PRIMARY       | PRIMARY | 4       | test.p.id      |    1 | Using index |
|  1 | SIMPLE      | t     | eq_ref | PRIMARY       | PRIMARY | 4       | test.pt.tag_id |    1 |             |
+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
3 rows in set (0.00 sec)

You're probably missing an index. With the following schema, this same query hit the index for every table:

CREATE TABLE `products` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `deleted` tinyint(1) unsigned NOT NULL DEFAULT '0',
  `status` varchar(255) NOT NULL DEFAULT 'listed',
  `images` varchar(255) DEFAULT NULL,
  `created` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `tags` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `tag` varchar(255) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `products_tags` (
  `product_id` int(11) NOT NULL,
  `tag_id` int(11) NOT NULL DEFAULT '0',
  PRIMARY KEY (`product_id`,`tag_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

Here are the results of the EXPLAIN query:

EXPLAIN SELECT p.id AS id, GROUP_CONCAT(t.tag SEPARATOR '|') AS tags,
UNIX_TIMESTAMP(p.created) AS created
FROM products p
INNER JOIN products_tags pt ON pt.product_id = p.id
INNER JOIN tags t ON t.id = pt.tag_id
WHERE p.deleted = 0
AND (p.images IS NOT NULL OR p.images <> '')
AND p.status LIKE 'listed'
GROUP BY p.id;

+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
| id | select_type | table | type   | possible_keys | key     | key_len | ref            | rows | Extra       |
+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
|  1 | SIMPLE      | p     | index  | PRIMARY       | PRIMARY | 4       | NULL           |    1 | Using where |
|  1 | SIMPLE      | pt    | ref    | PRIMARY       | PRIMARY | 4       | test.p.id      |    1 | Using index |
|  1 | SIMPLE      | t     | eq_ref | PRIMARY       | PRIMARY | 4       | test.pt.tag_id |    1 |             |
+----+-------------+-------+--------+---------------+---------+---------+----------------+------+-------------+
3 rows in set (0.00 sec)
~没有更多了~
我们使用 Cookies 和其他技术来定制您的体验包括您的登录状态等。通过阅读我们的 隐私政策 了解更多相关信息。 单击 接受 或继续使用网站,即表示您同意使用 Cookies 和您的相关数据。
原文