mysql 相关搜索_MySQL单词搜索相关度排名

一个单词搜索的相关度排名,这个例子演示了一个单词搜索的相关度排名计算。

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 (0.56 sec)

mysql> INSERT INTO articles (title,body) VALUES

-> ('MySQL Tutorial','This database tutorial ...'),

-> ("How To Use MySQL",'After you went through a ...'),

-> ('Optimizing Your Database','In this database tutorial ...'),

-> ('MySQL vs. YourSQL','When comparing databases ...'),

-> ('MySQL Security','When configured properly, MySQL ...'),

-> ('Database, Database, Database','database database database'),

-> ('1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),

-> ('MySQL Full-Text Indexes', 'MySQL fulltext indexes use a ..');

Query OK, 8 rows affected (0.02 sec)

Records: 8 Duplicates: 0 Warnings: 0

mysql> SELECT id, title, body, MATCH (title,body) AGAINST ('database' IN BOOLEAN MODE) AS score FROM articles ORDER BY score DESC;

+----+------------------------------+-------------------------------------+---------------------+

+----+------------------------------+-------------------------------------+---------------------+

| 6 | Database, Database, Database | database database database | 1.0886961221694946 |

| 3 | Optimizing Your Database | In this database tutorial ... | 0.36289870738983154 |

| 1 | MySQL Tutorial | This database tutorial ... | 0.18144935369491577 |

| 2 | How To Use MySQL | After you went through a ... | 0 |

| 4 | MySQL vs. YourSQL | When comparing databases ... | 0 |

| 5 | MySQL Security | When configured properly, MySQL ... | 0 |

| 7 | 1001 MySQL Tricks | 1. Never run mysqld as root. 2. ... | 0 |

| 8 | MySQL Full-Text Indexes | MySQL fulltext indexes use a .. | 0 |

+----+------------------------------+-------------------------------------+---------------------+

8 rows in set (0.00 sec)

总共有8条记录，其中3条与数据库搜索词匹配。第一条记录(id 6)包含搜索词6次，相关度排名为1.0886961221694946。这个排名值计算使用TF的价值6(数据库搜索词出现6次记录id 6)和IDF值为0.42596873216370745,计算如下(8是记录的总数和3是包含搜索词的记录数量)

${IDF} = log10( 8 / 3 ) = 0.42596873216370745

mysql> select log10( 8 / 3 ) ;

+---------------------+

| log10( 8 / 3 ) |

+---------------------+

| 0.42596873216370745 |

+---------------------+

1 row in set (0.00 sec)

然后将TF和IDF值输入到排名公式中

${rank} = ${TF} * ${IDF} * ${IDF}

在MySQL命令行客户端执行计算将返回一个排名值1.088696164686938。

mysql> SELECT 6*log10(8/3)*log10(8/3);

+-------------------------+

| 6*log10(8/3)*log10(8/3) |

+-------------------------+

| 1.088696164686938 |

+-------------------------+

1 row in set (0.00 sec)

您可能会注意到SELECT ... MATCH ... AGAINST语句和MySQL命令行客户端所计算的排名值有差别(1.0886961221694946对1.088696164686938)。区别在于InnoDB内部是如何执行整数和浮点数/双精度类型转换的(以及相关的精度和四舍五的决定)，以及它们在其他地方是如何执行的，比如在MySQL命令行客户端或其他类型的计算器中。

多词搜索的相关度排名

这个示例演示了基于前面示例中使用的articles表和数据计算多单词全文搜索的相关度排名。

如果你搜索的是一个以上的单词，那么相关度排名值就是每个单词相关度排名值的总和，如下公式所示:

${rank} = ${TF} * ${IDF} * ${IDF} + ${TF} * ${IDF} * ${IDF}

执行两个搜索词('mysql tutorial')搜索将返回以下结果:

mysql> SELECT id, title, body, MATCH (title,body) AGAINST ('mysql tutorial' IN BOOLEAN MODE) AS score FROM articles ORDER BY score DESC;

+----+------------------------------+-------------------------------------+----------------------+

+----+------------------------------+-------------------------------------+----------------------+

| 1 | MySQL Tutorial | This database tutorial ... | 0.7405621409416199 |

| 3 | Optimizing Your Database | In this database tutorial ... | 0.3624762296676636 |

| 5 | MySQL Security | When configured properly, MySQL ... | 0.031219376251101494 |

| 8 | MySQL Full-Text Indexes | MySQL fulltext indexes use a .. | 0.031219376251101494 |