A full-text search allows a search of multiple text columns. If you are setting up a search of a series of articles or a site with lots of product-related content, a MySQL FULLTEXT search can make it very easy to find articles or products related to the keywords used by a searcher.
FULLTEXT searches are only available with a MyISAM table type.
Full-text searching is performed using MATCH() ... AGAINST syntax. MATCH() takes a comma-separated list that names the columns to be searched. AGAINST takes a string to search for, and an optional modifier that indicates what type of search to perform. The search string must be a literal string, not a variable or a column name
Example
mysql> CREATE TABLE articles (
-> id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
-> title VARCHAR(200),
-> body TEXT,
-> FULLTEXT (title,body)
-> );
Query OK, 0 rows affected (0.00 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');
+----+-------------------+------------------------------------------+
| id | title | body |
+----+-------------------+------------------------------------------+
| 5 | MySQL vs. YourSQL | In the following database comparison ... |
| 1 | MySQL Tutorial | DBMS stands for DataBase ... |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)
By default, the search is performed in case-insensitive fashion. However, you can perform a case-sensitive full-text search by using a binary collation for the indexed columns.
When MATCH() is used in a WHERE clause, as in the example shown earlier, the rows returned are automatically sorted with the highest relevance first. Relevance values are non-negative floating-point numbers. Zero relevance means no similarity. Relevance is computed based on the number of words in the row, the number of unique words in that row, the total number of words in the collection, and the number of documents (rows) that contain a particular word.
To simply count matches, you could use a query like this:
mysql> SELECT COUNT(*) FROM articles
-> WHERE MATCH (title,body)
-> AGAINST ('database');
+----------+
| COUNT(*) |
+----------+
| 2 |
+----------+
1 row in set (0.00 sec)
However, you might find it quicker to rewrite the query as follows:
mysql> SELECT
-> COUNT(IF(MATCH (title,body) AGAINST ('database'), 1, NULL))
-> AS count
-> FROM articles;
+-------+
| count |
+-------+
| 2 |
+-------+
1 row in set (0.00 sec)
The first query sorts the results by relevance whereas the second does not. However, the second query performs a full table scan and the first does not. The first may be faster if the search matches few rows; otherwise, the second may be faster because it would read many rows anyway.
The next example shows how to retrieve the relevance values explicitly. Returned rows are not ordered because the SELECT statement includes neither WHERE nor ORDER BY clauses:
mysql> SELECT id, MATCH (title,body) AGAINST ('Tutorial')
-> FROM articles;
+----+-----------------------------------------+
| id | MATCH (title,body) AGAINST ('Tutorial') |
+----+-----------------------------------------+
| 1 | 0.65545833110809 |
| 2 | 0 |
| 3 | 0.66266459226608 |
| 4 | 0 |
| 5 | 0 |
| 6 | 0 |
+----+-----------------------------------------+
6 rows in set (0.00 sec)
