自然语言全文本检索
缺省或者modifier被设置为in natural language mode,都是进行自然语言检索。对于表中的每一行,match()都会返回一个关联值。
mysql> CREATE TABLE articles (
-> id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
-> title VARCHAR(200),
-> body TEXT,
-> FULLTEXT ( title , body )
-> ) ENGINE=INNODB;
Query OK, 0 rows affected (0.04 sec)
mysql> INSERT INTO articles (title,body) VALUES
-> ('MySQL Tutorial','DBMS stands for DataBase ...'),
-> ('How To Use MySQL Well','After you went through a ...'),
-> ('Optimizing MySQL','In this tutorial we will show ...'),
-> ('1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),
-> ('MySQL vs. YourSQL','In the following database comparison ...'),
-> ('MySQL Security','When configured properly, MySQL ...');
Query OK, 6 rows affected (0.00 sec)
Records: 6 Duplicates: 0 Warnings: 0
mysql> select * from articles
-> where match(title,body)
-> against('database' in natural language mode);
+----+-------------------+------------------------------------------+
| id | title | body |
+----+-------------------+------------------------------------------+
| 1 | MySQL Tutorial | DBMS stands for DataBase ... |
| 5 | MySQL vs. YourSQL | In the following database comparison ... |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)
mysql>
缺省情况下,检索是大小写不敏感的。如果要想进行大小写敏感的检索,对于索引的列要进行二进制collation。比如字符集类型为latin1的列可以修改为Latin1_bin。
当match()被作为where子句的时候,返回的行会被自动排序,根据检索关联度进行排序。
mysql> INSERT INTO articles (title,body) VALUES
-> ('oracle Tutorial','DBMS stands for DataBase ...DataBase');
Query OK, 1 row affected (0.00 sec)
mysql> select * from articles
-> where match(title,body)
-> against('database' in natural language mode);
+----+-------------------+------------------------------------------+
| id | title | body |
+----+-------------------+------------------------------------------+
| 7 | oracle Tutorial | DBMS stands for DataBase ...DataBase |
| 1 | MySQL Tutorial | DBMS stands for DataBase ... |
| 5 | MySQL vs. YourSQL | In the following database comparison ... |
+----+-------------------+------------------------------------------+
3 rows in set (0.00 sec)
mysql>
可以查看一下匹配的次数:
#使用索引
mysql> SELECT
-> COUNT(*)
-> FROM
-> articles
-> WHERE
-> MATCH (title , body) AGAINST ('database' IN NATURAL LANGUAGE MODE);
+----------+
| COUNT(*) |
+----------+
| 2 |
+----------+
1 row in set (0.00 sec)
mysql>
#使用全表扫描
mysql> SELECT
-> COUNT(IF(MATCH (title , body) AGAINST ('database' IN NATURAL LANGUAGE MODE),
-> 1,
-> NULL)) AS count
-> FROM
-> articles;
+-------+
| count |
+-------+
| 3 |
+-------+
1 row in set (0.00 sec)
mysql>
对于自然语言全文本检索,match()中的列名必须和全文索引中的列相同。上例中,如果想对title或body分开检索,就需要分别创建全文索引。
上面的例子中,基本展示了如何使用match()。返回的结果根据关联值的降序排列。
下面的例子,展示如何显式输出关联值得大小。返回的行不是有序的,因为select语句既不包含where也没有order by。
mysql> SELECT
-> id,
-> MATCH (title , body) AGAINST ('database' IN NATURAL LANGUAGE MODE) AS score
-> FROM
-> articles;
+----+---------------------+
| id | score |
+----+---------------------+
| 1 | 0.22764469683170319 |
| 2 | 0 |
| 3 | 0 |
| 4 | 0 |
| 5 | 0.22764469683170319 |
| 6 | 0 |
+----+---------------------+
6 rows in set (0.00 sec)
mysql>
下面的例子更复杂,查询返回关联值得具体值,同时进行降序排序。为了实现这个目的,使用了match()两次。这样的语句不会有额外的开销,优化器会注意到两次match()调用是一样的,所以只会执行全文检索一次。
mysql> SELECT
-> id,
-> body,
-> MATCH (title , body) AGAINST ('Security implications of running MySQL as root' IN NATURAL LANGUAGE MODE) AS score
-> FROM
-> articles
-> WHERE
-> MATCH (title , body) AGAINST ('Security implications of running MySQL as root' IN NATURAL LANGUAGE MODE);
+----+------------------------------------------+----------------------------+
| id | body | score |
+----+------------------------------------------+----------------------------+
| 4 | 1. Never run mysqld as root. 2. ... | 0.6055193543434143 |
| 6 | When configured properly, MySQL ... | 0.6055193543434143 |
| 1 | DBMS stands for DataBase ... | 0.000000001885928302414186 |
| 2 | After you went through a ... | 0.000000001885928302414186 |
| 3 | In this tutorial we will show ... | 0.000000001885928302414186 |
| 5 | In the following database comparison ... | 0.000000001885928302414186 |
+----+------------------------------------------+----------------------------+
6 rows in set (0.00 sec)
mysql>
用双引号引起来的词组,检索匹配的结果只能是双引号中的字面值。全文检索会将双引号中的内容分解成单词,然后执行检索匹配。非单词字符是不需要匹配的,只是按照其中的单词顺序进行匹配,比如"test phrase"和"test, phrase"是匹配的。
全文检索会将字母、数字、下划线的组合当成一个word。但是也会将'当成一个word序列,不过一行只能有一个',比如会将aaa'bbb当成一个单词,但是aaa''bbb就不是一个单词了,而是两个。如果'放在开头或者结果,会被丢弃。
内嵌的文本解释器决定单词的开头和结尾,根据delimiter符号进行判断,比如逗号、空格、点号。如果不是根据delimiter分割的,比如中文,解释器就无法判断出单词的开头和结尾了。
所以,用户必须使用某些delimiter对文本进行处理后再检索。在5.7.6中可以使用插件ngram解释器来实现对中文、日文、韩文的支持,或者使用MeCab解释器来支持日文。
也可以自己编写插件解释器。示例代码位于plugin/fulltext目录。
在全文检索中,有些单词是被忽略的:
--太短的单词。默认最小长度是3个字符(innodb)、4个字符(myisam)。可以设置innodb中的innodb_ft_min_token_size、myisam中的ft_min_word_len
--stopword中的单词会被忽略。stopword是指那些类似the、some一样太普通以致被认为是没有什么语义值得单词。有一个内嵌stopword列表。也可以重新定义。
每个正确的单词在查询时都被会加权,根据其在集合和查询中的重要性。所以出现频率越高,权重就越低。单词的权重会被用来计算行的关联值。
全文检索如果本生行数就比较少,可能检索不出正确的结果。