by Joe Stump

Have you ever wanted to search text stored in your database, but couldn't figure out how to do it efficiently? Are you lazy like me and don't enjoy maintaining reverse indexes, dictionaries, and word scores? You're in luck. The release of MySQL 4.0 has made searching text stored in databases available to the masses.

MySQL has had FULLTEXT searching in one form or another since version 3.23.23. FULLTEXT indices in MySQL allow database administrators and programmers to designate any character-based field (CHAR, VARCHAR, or TEXT) as a FULLTEXT index, which allows for complex text searching against data stored in those fields.

This feature is not to be confused with the LIKE function in MySQL. LIKE works more along the lines of a regular expression. On the other hand, FULLTEXT indices are fully indexed fields which support stopwords, boolean searches, and relevancy ratings.

This article assumes you have a working installation of MySQL, a good understanding of how MySQL works, and a basic understanding of web programming (with PHP, Perl, or something similar). Further, this article may not be of any interest to those who are already using FULLTEXT indices in a production environment.

How it Works

The MySQL team has made it extremely easy to add FULLTEXT searching to your tables. They are created much like regular KEY and PRIMARY KEY indices. For the purpose of this article we are going to make a basic blog table, put some data into it, and start searching. Before we get ahead of ourselves we need to create some tables.

Creating the tables

-- The main blog table with our FULLTEXT index
-- Nothing extreme here, but you get the idea
CREATE TABLE blog_entries
  title CHAR(255) NOT NULL DEFAULT '',
  PRIMARY KEY (entryID),
  KEY (posted),
  KEY (categoryID),

-- A category table so you can organize your posts and 
-- later do some fun searching based on such data.
CREATE TABLE blog_categories
  name CHAR(75) NOT NULL DEFAULT '',
  PRIMARY KEY (categoryID)

-- Add some data into your blog
INSERT INTO blog_categories VALUES (1,'Personal');
INSERT INTO blog_categories VALUES (2,'Work');
INSERT INTO blog_categories VALUES (3,'Editorials');

INSERT INTO blog_entries 
        'About miester',
        'I was born in michigan in 1980 in a small town called Adrian. 
         My mother is named Sue, while my father is named Mike. 
         They currently live in a small town called East Jordan. On April 
         27th, 2003 I will graduate from Eastern Michigan University with a 
         degree in Computer Information Systems.');

INSERT INTO blog_entries 
        'Today at work',
        'While I was at work today I was having some problems
        with the RAID array. It seems that we have a rogue cron script that 
        is causing problems. When I find out more info I will post it here.');

INSERT INTO blog_entries 
        'After I graduate I am taking a 2 week vacation. On my 
         agenda is a trip to Washington DC to see my girlfriend\'s sister 
         as well as throwing a few discs at the local disc golf course.');

INSERT INTO blog_entries 
        'I have had a horrible cold for the last few days. Today I drank a
         revive vitamin water with 150% of my daily dose of vitamin C. That
         should help things out.');

Querying the Data

Now that we have data in our tables we can begin to query it. There are some restrictions to FULLTEXT searching, which are covered below. You will want to read over the restrictions before you use FULLTEXT indices in a production environment. For now we are going to do a simple query for the word mother.

mysql> SELECT entryID,title
    -> FROM blog_entries
    -> WHERE MATCH (title,entry) AGAINST('mother');
| entryID | title         |
|       1 | About miester |
1 row in set (0.00 sec)

There are a few things to note when querying FULLTEXT indices. First, MySQL automatically orders the results by their relevancy rating. Second, queries that are longer than 20 characters will not be sorted. Third, and most importantly, the fields in the MATCH() should be identical to the fields listed in the table's FULLTEXT definition.

All other MySQL syntax works as you'd expect with a FULLTEXT search, meaning you can further limit your search terms. We could search blog entries based on posting date or category. If you let your imagination wander you can think of all sorts of ways to filter your data. Let's look for blog entries that only appear in the Personal category and match the term michigan.

mysql> SELECT E.entryID, E.title,
    -> FROM blog_entries AS E, blog_categories AS C
    -> WHERE E.categoryID=C.categoryID AND
    ->       MATCH (E.title, E.entry) AGAINST ('michigan') AND
    ->       E.categoryID=1;
| entryID | title         | name     |
|       1 | About miester | Personal |
1 row in set (0.00 sec)

Note that we not only did a join but also filtered the results based on the category. Another thing to note is that FULLLTEXT indices are not case sensitive. If you would like to use MySQL's relevancy rating in your code you can add the MATCH() ... AGAINST() clause to your SELECT statement as well.

mysql> SELECT E.entryID, E.title,,
    ->        MATCH (E.title, E.entry) AGAINST ('michigan') AS score
    -> FROM blog_entries AS E, blog_categories AS C
    -> WHERE E.categoryID=C.categoryID AND
    ->       MATCH (E.title, E.entry) AGAINST ('michigan') AND
    ->       E.categoryID=1;
| entryID | title         | name     | score           |
|       1 | About miester | Personal | 1.2635315656662 |
1 row in set (0.00 sec)

Boolean Searches

Probably the most anticipated feature in MySQL 4.0's FULLTEXT is the ability to do boolean searches without having to process the query strings. This means you can add +s and -s to your queries, along with a host of other commands, and MySQL will interpret them for you.

mysql> SELECT E.entryID,E.title,
    -> FROM blog_entries AS E, blog_categories AS C
    -> WHERE E.categoryID=C.categoryID AND
    ->       MATCH (E.title,E.entry) AGAINST ('+vacation -washington' IN BOOLEAN MODE) AND
    ->       E.categoryID=1;
| entryID | title     | name     |
|       4 | Vacation! | Personal |
1 row in set (0.00 sec)

We have two entries with the word vacation in the title, but since we removed washington, entryID 4 does not show up in the result. You can read all about IN BOOLEAN MODE on MySQL's FULLTEXT manual page.

Related Reading

MySQL Pocket Reference
By George Reese


A few restrictions affect MySQL FULLTEXT indices. Some of the default behaviors of these restrictions can be changed in your my.cnf or using the SET command.

Altering FULLTEXT's Default Behavior

There are several ways to alter the default behavior of FULLTEXT. MySQL has some tips for fine tuning the FULLTEXT search, but the details are a little sparse. The most common problem is the four character minimum word length on queries. Before we go over that, let's review the variables associated with the FULLTEXT searching.

| Variable_name            | Value          |
| ft_boolean_syntax        | + -><()~*:""&| |
| ft_min_word_len          | 2              |
| ft_max_word_len          | 254            |
| ft_max_word_len_for_sort | 20             |
| ft_stopword_file         | (built-in)     |
5 rows in set (0.00 sec)

The variable we wish to change is ft_min_word_len. According to the manual we should be able to change this via the SET VARIABLE command, but, in reality, this does not work. After asking the mailing list about this problem I was told this had to be specified as a startup option. To change the minimum query string to three characters, start the MySQL server as follows.

$ cd /path/to/mysql
$ ./bin/safe_mysqld --user=mysql -O ft_min_word_len=3 &

After you have restarted your MySQL server (don't forget to change your startup scripts) you have to rebuild the FULLTEXT indices. The manual suggests the following command:

-- Replace tbl_name with the name of your table
mysql> REPAIR TABLE tbl_name QUICK;

After you have rebuilt your indices, you should be able to search with query strings of three or more characters instead of the default four character limit.

Having fun with MySQL FULLTEXT Searching

I'll save the implementation details for a later article, but here are some interesting ways in which you could use MySQL FULLTEXT searching to finding data on your website more interesting.


A great way to add cross referencing to articles would be to store a query (i.e., linux for a post about Debian GNU/Linux) with each article. If an article had a query, PHP could then perform a FULLTEXT search, returning those results as "Related Articles". Furthermore, you could use PHP to create an advanced search script that allowed users to search the database based on category, criteria, pricing, etc.


ispell is a great tool for open source developers to use to make their applications more user friendly. By adding ispell to your search engine, you can check the spelling of each query, offering alternate queries if the query was spelled wrong. Everyone's favorite search engine does something similar.

Looking towards the Future

According to the manual, the MySQL team has a lot they still want to implement into FULLTEXT searching. Here is a brief overview of those enhancements:

The proximity operators will really make FULLTEXT searching impressive. This will allow you to do searches on words based on how close together they are. For example, if you currently searched for 'mysql search' you would get results even where mysql and search appear at opposite ends of the document. With proximity operators, the scoring algorithm gauges how close together the words are. Documents where mysql and search appeared directly next to one another would score higher than documents where they were not close together.

Stemming is a great way to make search engines smarter. This would allow MySQL to search for words that share the same lexical root. For example, queries for running would return documents with ran and run as well as running.


As you can see, the possibilities of FULLTEXT are almost endless. For those of us looking for an easy and powerful solution to our searching woes, MySQL has come up with an answer.

Joe Stump is the Lead Architect for Digg where he spends his time partitioning data, creating internal services, and ensuring the code frameworks are in working order.

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