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Recently I had an idea how to illustrate how myisam_suggest works by a comparison with a normal printed book’s index:

“AutoSuggest” for a printed book

Image you have a thick book with hundreds of thousands of words in it. Now you want to know all words beginning with “fu” for some reason (= AutoSuggest).

Without the (full-text) index on the book’s last pages, you’d have to read the whole book, remember all words, sort them alphabetically, erase duplicates and then look at the words beginning with “fu”. A very time-intensive process.

However, if an index is available, you can just scroll to the … Continue Reading

In “1/3 Implementing an AutoSuggest feature using MySQL fulltext indices” I described how you can use a MyISAM full-text index to extract search words for an AutoSuggest feature. Then, in “2/3 myisam_suggest: an AutoComplete tool for MySQL fulltext indices” I wrote how to install and use myisam_suggest to extract these search words in practice.

Here you will find how to use AJAX AutoSuggest together with my tool “myisam_suggest”.
For a demo, see www.gimpusers.com. Enter some characters (e.g. “brus”) into the search field on the top of the page.
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As I’ve written in my previous post “1/3 Implementing an AutoSuggest feature using MySQL fulltext indices”, it’s possible to use the MySQL/MyISAM full-text index to extract search words for an AutoSuggest feature with great performance (because the index tree is used actually). This tool, called myisam_suggest, is my first implementation of this.
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The MySQL full-text index

Current MySQL versions provide a full-text index (FTI) which is generally used to index and search MyISAM (the default storage engine in MySQL) tables like this:

SELECT id, content FROM documents WHERE MATCH(content) AGAINST (“tes*” IN BOOLEAN MODE)

Internally, every indexed (text) column of a row is splitted into its words. Continue Reading