 PHP Page 2 - Performing Full-text and Boolean Searches with MySQL |
Running SELECT queries using a common approach - PHPWhen a database-driven web site grows past a certain size, it requires an internal search engine. If it is a very big site, it may be desirable for visitors to be able to use full-text searches and Boolean operators to find the information they need. This article, the first of a three-part series, explains why and shows you how to work with full-text and Boolean searches using MySQL and PHP 5.
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We can start learning about using full-text and Boolean searches with MySQL by developing a simple search engine. Our example will use the popular "LIKE" SQL statement to collect database information according to a specific search term entered by a fictional user. Having said that, this basic MySQL-based search engine could be implemented through the definition of two simple files, whose signatures are listed below: (definition of form.htm file) <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" <html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta http-equiv="Content-Type" content="text/html; charset=iso- <title>Example of simple MySQL search engine</title> <style type="text/css"> body{ padding: 0; margin: 0; background: #fff; } h1{ font: bold 16px Arial, Helvetica, sans-serif; color: #000; text-align: center; } p{ font: bold 11px Tahoma, Arial, Helvetica, sans-serif; color: #000; } #formcontainer{ width: 40%; padding: 10px; margin-left: auto; margin-right: auto; background: #6cf; } </style> </head> <body> <h1>Example of simple MySQL search engine</h1> <div id="formcontainer"> <form action="search.php" method="get"> <p>Enter search term here : <input type="text" name="searchterm" </form> </div> </body> </html> (definition of search.php file) <?php // define 'MySQL' class class MySQL{ private $conId; private $host; private $user; private $password; private $database; private $result; const OPTIONS=4; public function __construct($options=array()){ if(count($options)!=self::OPTIONS){ throw new } foreach($options as $parameter=>$value){ if(!$value){ throw new } $this->{$parameter}=$value; } $this->connectDB(); } // connect to MySQL private function connectDB(){ if(!$this->conId=mysql_connect($this- throw new } if(!mysql_select_db($this- throw new } } // run query public function query($query){ if(!$this->result=mysql_query throw new } return new Result($this,$this->result); } public function escapeString($value){ return mysql_escape_string($value); } } // define 'Result' class class Result { private $mysql; private $result; public function __construct(&$mysql,$result){ $this->mysql=&$mysql; $this->result=$result; } // fetch row public function fetchRow(){ return mysql_fetch_assoc($this->result); } // count rows public function countRows(){ if(!$rows=mysql_num_rows($this->result)){ return false; } return $rows; } // count affected rows public function countAffectedRows(){ if(!$rows=mysql_affected_rows($this- throw new Exception('Error counting affected rows'); } return $rows; } // get ID form last-inserted row public function getInsertID(){ if(!$id=mysql_insert_id($this->mysql- throw new } return $id; } // seek row public function seekRow($row=0){ if(!is_int($row)||$row<0){ throw new Exception('Invalid } if(!mysql_data_seek($this->result,$row)){ throw new Exception('Error } } } try{ // connect to MySQL $db=new MySQL(array $searchterm=$db->escapeString($_['searchterm']); $result=$db->query("SELECT * FROM articles WHERE if(!$result->countRows()){ echo 'No results were found.'; } else{ echo '<h2>Articles returned are as while($row=$result->fetchRow()){ echo '<p>Title: '.$row } } } catch(Exception $e){ echo $e->getMessage(); exit(); } ?> As you can see, the two files listed above implement a primitive MySQL-based search engine. The first file simply displays a web form for entering different search terms, and the second one performs the searching process against a sample "ARTICLES" database table. As shown above, this task is carried out by two MySQL-processing classes, which may already be familiar to you -- I've been using them with some of my previous PHP articles published on the prestigious Developer Shed network. However, the most important thing to notice here is the use of the traditional "LIKE" SQL statement inside the SELECT query. It allows us to retrieve the corresponding results from the database table according to a specified search term, as indicated below: $result=$db->query("SELECT * FROM articles WHERE title LIKE '% We'll assume that the sample "ARTICLES" database table has been previously populated with the following basic records: Id Title Author Content 1 This is the title of article 1 Alejandro Gervasio This is the content of article 1 If the search string "article 1" were entered in the corresponding web form, the search engine would return the following query result: Articles returned are as following: Title: This is the title of article 1 Author: Alejandro Gervasio You have probably used the "LIKE" statement hundreds of times before with your SELECT queries, so the previous example should be pretty easy to grasp. In this case, I built a basic but effective internal search engine that uses MySQL as its principal workhorse. That was quite simple to implement, right? Nevertheless, as the databases that integrate the back end of a given web site or PHP application grow in size, the queries performed using the familiar "LIKE" command can introduce a considerable overhead in the server. This doesn't even consider what happens when the SELECT statements involve the utilization of multiple databases and tables! Yes, certainly this kind of query may take several seconds to run, and as I said before, can seriously compromise the performance of the web server. Considering the aforementioned performance issue, here is where full-text searches come in. They can noticeably speed up the execution of large and complex queries, in this way improving the overall performance of the application in which they are used. However, the details on how to use full-text searches with MySQL will be discussed in the following section, so click on the link below and keep reading.
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