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Optimizing MySQL query to avoid scanning a lot of rows

开发者 https://www.devze.com 2023-03-28 19:24 出处:网络
I am running an application that is using t开发者_如何学编程ablessimilar to the below tables. There are one tables for articles and there is another table for tags. I want to get the latest 30 article

I am running an application that is using t开发者_如何学编程ables similar to the below tables. There are one tables for articles and there is another table for tags. I want to get the latest 30 articles for a specific tag order by article id. for example "acer", the below query will do the job but it is not indexed correctly because it will scan a lot of rows if there are a lot of articles related to a specific tag. How to run a query to get the same result without scanning a large number of rows?

EXPLAIN SELECT title
FROM tag, article
WHERE tag = 'acer'
AND tag.article_id = article.id
ORDER BY tag.article_id DESC 
LIMIT 0 , 30 

Output

id  select_type     table   type    possible_keys   key     key_len     ref     rows    Extra
1   SIMPLE  tag     ref     tag     tag     92  const   220439  Using where; Using index
1   SIMPLE  article     eq_ref  PRIMARY     PRIMARY     4   testdb.tag.article_id   1 

The flollowing is the tables and sample data:

CREATE TABLE `article` (
  `id` int(11) NOT NULL auto_increment,
  `title` varchar(60) NOT NULL,
  `time_stamp` int(11) NOT NULL,
  PRIMARY KEY  (`id`)
) ENGINE=MyISAM  DEFAULT CHARSET=utf8 AUTO_INCREMENT=1000001 ;

-- 
-- Dumping data for table `article`
-- 

INSERT INTO `article` VALUES (1, 'Saudi Apple type D', 1313390211);
INSERT INTO `article` VALUES (2, 'Japan Apple type A', 1313420771);
INSERT INTO `article` VALUES (3, 'UAE Samsung type B', 1313423082);
INSERT INTO `article` VALUES (4, 'UAE Apple type H', 1313417337);
INSERT INTO `article` VALUES (5, 'Japan Samsung type D', 1313398875);
INSERT INTO `article` VALUES (6, 'UK Acer type B', 1313387888);
INSERT INTO `article` VALUES (7, 'Saudi Sony type D', 1313429416);
INSERT INTO `article` VALUES (8, 'UK Apple type B', 1313394549);
INSERT INTO `article` VALUES (9, 'Japan HP type A', 1313427730);
INSERT INTO `article` VALUES (10, 'Japan Acer type C', 1313400046);



CREATE TABLE `tag` (
  `tag` varchar(30) NOT NULL,
  `article_id` int(11) NOT NULL,
  UNIQUE KEY `tag` (`tag`,`article_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8;

-- 
-- Dumping data for table `tag`
-- 


INSERT INTO `tag` VALUES ('Samsung', 1);
INSERT INTO `tag` VALUES ('Acer', 2);
INSERT INTO `tag` VALUES ('Sony', 3);
INSERT INTO `tag` VALUES ('Apple', 4);
INSERT INTO `tag` VALUES ('Acer', 5);
INSERT INTO `tag` VALUES ('HP', 6);
INSERT INTO `tag` VALUES ('Acer', 7);
INSERT INTO `tag` VALUES ('Sony', 7);
INSERT INTO `tag` VALUES ('Acer', 7);
INSERT INTO `tag` VALUES ('Samsung', 9);


What makes you think the query will examine a large number of rows?

The query will scan exactly 30 records using the UNIQUE index on tag (tag, article_id), join the article to each record on PRIMARY KEY and stop.

This is exactly what your plan says.

I just made this test script:

CREATE TABLE `article` (
  `id` int(11) NOT NULL auto_increment,
  `title` varchar(60) NOT NULL,
  `time_stamp` int(11) NOT NULL,
  PRIMARY KEY  (`id`)
) ENGINE=MyISAM  DEFAULT CHARSET=utf8 AUTO_INCREMENT=1000001 ;

CREATE TABLE `tag` (
  `tag` varchar(30) NOT NULL,
  `article_id` int(11) NOT NULL,
  UNIQUE KEY `tag` (`tag`,`article_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8;

INSERT
INTO    article
SELECT  id, CONCAT('Article ', id), UNIX_TIMESTAMP('2011-08-17' - INTERVAL id SECOND)
FROM    t_source;

INSERT
INTO    tag
SELECT  CASE fld WHEN 1 THEN CONCAT('tag', (id - 1) div 10 + 1) ELSE tag END AS tag, id
FROM    (
        SELECT  tag,
                id,
                FIELD(tag, 'Other', 'Acer', 'Sony', 'HP', 'Dell') AS fld,
                RAND(20110817) AS rnd
        FROM    (
                SELECT  'Other' AS tag
                UNION ALL
                SELECT  'Acer' AS tag
                UNION ALL
                SELECT  'Sony' AS tag
                UNION ALL
                SELECT  'HP' AS tag
                UNION ALL
                SELECT  'Dell' AS tag
                ) t
        JOIN    t_source
        ) q
WHERE   POWER(3, -fld) > rnd;

, where t_source is a table with 1M records in it, and run your query:

SELECT  *
FROM    tag t
JOIN    article a
ON      a.id = t.article_id
WHERE   t.tag = 'acer'
ORDER BY
        t.article_id DESC
LIMIT 30;

It was instant.


try ANSI join syntax:

SELECT title
FROM tag t
INNER JOIN article a
    ON t.article_id = a.id
WHERE
    t.tag = 'acer'
ORDER BY 
    tag.article_id DESC
LIMIT 0 , 30

then put an index on tag.tag. Assuming you have enough selectivity on that table, and article.id is a primary key, that should be pretty zippy.


I would suggest modifying the storage engine and schema to utilize foreign keys.

CREATE TABLE `article` (
  `id` int(11) NOT NULL auto_increment,
  `title` varchar(60) NOT NULL,
  `time_stamp` int(11) NOT NULL,
  PRIMARY KEY  (`id`)
) ENGINE=InnoDB  DEFAULT CHARSET=utf8 AUTO_INCREMENT=1000001 ;

CREATE TABLE `tag` (
 `id` int(11) NOT NULL auto_increment,
 `tag` varchar(30) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `article_tag` (
 `id` int(11) NOT NULL auto_increment,
 `article_id` int(11) NOT NULL,
 `tag_id` int(11) NOT NULL,
 PRIMARY KEY (`id`),
 FOREIGN KEY (`article_id`) REFERENCES article(id),
 FOREIGN KEY (`tag_id`) REFERENCES tag(id)
) ENGINE=Innodb;

Which results in a query like so:

EXPLAIN 
SELECT * FROM article 
    JOIN article_tag ON article.id = article_tag.id 
    JOIN tag ON article_tag.tag_id = tag.id 
WHERE tag.tag="Acer";
+----+-------------+-------------+--------+----------------+---------+---------+-------------------------+------+-------------+
| id | select_type | table       | type   | possible_keys  | key     | key_len | ref                     | rows | Extra       |
+----+-------------+-------------+--------+----------------+---------+---------+-------------------------+------+-------------+
|  1 | SIMPLE      | article_tag | ALL    | PRIMARY,tag_id | NULL    | NULL    | NULL                    |    1 |             |
|  1 | SIMPLE      | tag         | eq_ref | PRIMARY        | PRIMARY | 4       | temp.article_tag.tag_id |    1 | Using where |
|  1 | SIMPLE      | article     | eq_ref | PRIMARY        | PRIMARY | 4       | temp.article_tag.id     |    1 |             |
+----+-------------+-------------+--------+----------------+---------+---------+-------------------------+------+-------------+
3 rows in set (0.00 sec)


Edit: Add this index

UNIQUE KEY tag (article_id,tag)
0

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