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In modern website development, search functionality is essential. However, when a user begins to enter a query keyword, the search engine usually waits for the user to complete the input and then performs a complete search. This reduces user experience and responsiveness, especially when you have large amounts of data.
In order to improve user experience and response speed, we can use the auto-complete search function. Using the autocomplete search feature, the site responds immediately and displays a number of possible search results based on the user's input and the most likely citations.
This article will introduce how to use PHP and Redis to implement the automatic completion search function.
PHP is a general-purpose programming language widely used for web development. Redis is a fast, in-memory key/value store database for caching and high-speed data access. We will use these two techniques to build an autocomplete search implementation.
First, we need to create an input box to capture the user's input and display possible search results. We can use HTML and JavaScript to implement these functions. When the user enters a query keyword in the input box, we can use JavaScript to request matching search results from the server and display them in the drop-down menu. AJAX technology is needed here to implement automated requests without refreshing the page.
Now, we need to send this request to the server side. We can use PHP to handle this task. First, we need to create a script on the server side to respond to AJAX requests. This script will process the user's input and utilize the Redis cache for data inspection.
Redis allows us to store keyword and reference counted key/value pairs in memory. When a search keyword is entered, we can immediately find the related keyword in memory and update the reference count. By using caching, we can improve the speed at which search results are retrieved.
The PHP script should proceed as follows:
The next step is to write PHP code to extract relevant search results . Assuming we store keywords and reference counts in a Redis database, we can use the following code to extract relevant search results:
$redis = new Redis();
$redis->connect(' 127.0.0.1', 6379);
$query = $_GET['query'];
$keywords = $redis->zRevRange('keywords', 0, -1, 'WITHSCORES' );
$results = array();
foreach ($keywords as $keyword => $score) {
if (stripos($keyword, $query) === 0) { $results[] = array( 'name' => $keyword, 'score' => $score ); }
}
usort($results , function($elem1, $elem2) {
return $elem2['score'] - $elem1['score'];
});
echo json_encode($results);
Here we use the zRevRange() method in Redis to extract all keywords key/value pairs, sorted from highest to lowest reference count. After that, we use the stripos() function to perform fuzzy matching, filter out relevant search results, and add them to the result set. Finally, we use the usort() function to sort the search results by reference count. Finally, we use the json_encode() function to convert the result to JSON format and return it to Javascript.
At this point, we have completed the basic function of using PHP and Redis to implement automatic completion search. This function allows users to not have to wait for the complete search to be completed before they can see the search results, which greatly improves the user experience and response. speed.
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