With the continuous development of Internet technology, search engines are becoming more and more widely used. In the context of the Internet, search engines have become one of the main ways for users to obtain information. In this process, full-text search technology plays a crucial role. Full-text search indexes text content to quickly locate matching text when users query. There are many solutions to implement full-text search in PHP applications, and this article will focus on Redis' full-text search in PHP applications.

Redis is a high-performance non-relational in-memory database that supports a variety of data structures, including strings, hashes, lists, sets and ordered sets. Redis also provides many powerful features, such as publish/subscribe, transactions, Lua scripts, etc. Therefore, Redis is suitable for a variety of scenarios, such as caching, queues, real-time counting, distributed locks, etc. At the same time, Redis's high performance and high availability also make it one of the most commonly used data storage methods in PHP applications.

The basic principle of Redis to implement full-text search is to quickly locate text content during query by establishing an index. In the process of indexing, the text content needs to be decomposed into several words, and then a mapping relationship is established between these words and the identifiers of the text content. In the data structure that stores the index, each word corresponds to an ordered set, and this ordered set stores the identifier and the number of occurrences of the text content in which the word appears. When querying, first decompose the query string into several words, then obtain the identifier of the text content from the ordered set corresponding to the word, sort them according to the number of occurrences, and finally return the results.

In PHP applications, Redis has many ways to implement full-text search. The most commonly used ones are through the Sorted Set and Lua scripts provided by Redis. The specific implementation details are as follows:

1. Creating an index

The process of establishing an index is generally performed when the server starts, and the text content that needs to be indexed is read from the database. Then decompose it into several words, establish a mapping relationship between these words and the identifiers of the text content, and finally store the results in Redis. The specific code is as follows:

<?php
// 建立索引
function buildIndex($redis, $db)
{
    $sql = "SELECT id, title, content FROM article";
    $sth = $db->query($sql);

    while ($row = $sth->fetch(PDO::FETCH_ASSOC)) {
        $id = $row['id'];
        $title = $row['title'];
        $content = $row['content'];

        // 分解單詞
        $words = preg_split('/s+/', $title . ' ' . $content);
        $words = array_unique($words);

        foreach ($words as $word) {
            if (!$word) {
                continue;
            }

            $redis->zIncrBy('index:' . $word, 1, $id);
        }
    }
}
?>

2. Query

The query process is divided into two steps. First, the query string is decomposed into several words, and then the corresponding words are Obtain the identifier of the text content from the ordered collection, sort it according to the number of occurrences, and finally return the result. The specific code is as follows:

<?php
// 全文搜索
function search($redis, $query, $offset, $count)
{
    $words = preg_split('/s+/', $query);
    $words = array_unique($words);

    $tmpKeys = array();
    foreach ($words as $word) {
        if (!$word) {
            continue;
        }

        $tmpKey = 'idx:' . $word;
        $redis->zInter($tmpKey, array('index:' . $word), array(1));
        $tmpKeys[] = $tmpKey;
    }

    $redis->zUnion('idx:result', $tmpKeys, array(1));
    $redis->zRevRange('idx:result', $offset, $offset + $count - 1);
}
?>

3. Lua script

In order to reduce network transmission and improve query efficiency, you can use Lua script to encapsulate the query process into a command. The specific code is as follows:

<?php
// 全文搜索，使用 Lua 腳本實(shí)現(xiàn)
function search($redis, $query, $offset, $count)
{
    $script = "
        local words = redis.call('SPLIT', ARGV[1], '[^%w]+')
        local tmpKeys = {}
        for i, word in ipairs(words) do
            if word ~= '' then
                local tmpKey = 'idx:' .. word
                redis.call('ZINTERSTORE', tmpKey, 1, 'index:' .. word)
                table.insert(tmpKeys, tmpKey)
            end
        end
        redis.call('ZUNIONSTORE', 'idx:result', #tmpKeys, unpack(tmpKeys))
        return redis.call('ZREVRANGE', 'idx:result', ARGV[2], ARGV[3])
    ";

    return $redis->eval($script, 3, $query, $offset, $offset + $count - 1);
}
?>

Summary:

Redis implements full-text search in PHP applications. By establishing indexes, text content can be quickly located during queries, giving full play to the high performance and high availability of Redis. The advantages. By using the Sorted Set and Lua scripts provided by Redis, the full-text search task can be completed better, providing an efficient solution for PHP developers. However, it should be noted that when the amount of data is large, Redis may face the problem of insufficient memory. At this time, a reasonable data storage and indexing strategy needs to be designed to avoid Redis memory overflow.

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