PHP and Manticore Search Development: Key Performance Tweaks to Optimize Search Results

PHP and Manticore Search development: Key performance adjustments to optimize search results

Introduction: In the era of big data, key performance adjustments to optimize search results are very important. This article explains how to achieve this by developing with PHP and Manticore Search, and provides code examples.

Introduction:

With the rapid development of the Internet, search engines have become one of the main ways for people to obtain information. Therefore, how to improve the accuracy, speed and user experience of search results has become an important concern for enterprises and developers.

PHP is a popular server-side scripting language widely used for web development. Manticore Search is an open source, high-performance search engine that is fully compatible with the Sphinx search engine and has more new features and improvements.

In this article, we will focus on how to develop key performance adjustments using PHP and Manticore Search to optimize search results.

Part One: Install and Configure Manticore Search

First, we need to install Manticore Search and perform basic configuration. You can download the latest version of Manticore Search from the official website (https://manticoresearch.com/).

After the installation is complete, modify the Manticore Search configuration file (usually /etc/manticoresearch/manticore.conf) as follows:

indexer
{
  mem_limit = 1G
}

searchd
{
  listen = 127.0.0.1:9306:mysql41
  log = /var/log/manticoresearch/searchd.log
  query_log = /var/log/manticoresearch/query.log
}

Here are the main parameters such as memory limit and listening address. . After completing the configuration, start the Manticore Search service:

$ sudo systemctl start manticore

Part 2: Create an index and import data

Before searching, we need to create an index and import the data to be searched.

Suppose we have a database that stores movie information, and now we want to create an index so that users can search by the title and description of the movie. We can create an index by executing the following code example:

$index = new SphinxClient;
$index->SetServer('localhost', 9306);
$index->SetConnectTimeout(1);
$index->AddQuery('REPLACE INTO movies (id, title, description) VALUES (1, "The Shawshank Redemption", "Two imprisoned men bond over a number of years, finding solace and eventual redemption through acts of common decency.")');
$index->AddQuery('REPLACE INTO movies (id, title, description) VALUES (2, "The Godfather", "The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant son.")');
$index->RunQueries();

Here we use an open source Sphinx client library that provides methods to interact with Manticore Search.

Part Three: Search Optimization

Once we have completed the creation of the index and the import of data, we can start search optimization.

The following example shows how to use PHP and Manticore Search for basic search optimization:

$query = "redemption";
$search = new SphinxClient;
$search->SetServer('localhost', 9306);
$search->SetConnectTimeout(1);
$search->SetMatchMode(SPH_MATCH_EXTENDED);
$search->SetRankingMode(SPH_RANK_PROXIMITY_BM25);
$search->SetSortMode(SPH_SORT_RELEVANCE);
$result = $search->Query($query, 'movies');
while ($info = $search->GetArrayResult()) {
    foreach ($info['matches'] as $match) {
        $id = $match['id'];
        $weight = $match['weight'];
        // 处理搜索结果
    }
}

Here we set the matching mode to extended mode (SPH_MATCH_EXTENDED) and the ranking mode to BM25 mode (SPH_RANK_PROXIMITY_BM25) , the sorting method is relevance sorting (SPH_SORT_RELEVANCE).

Through the above optimization measures, we can obtain more accurate and faster search results.

Conclusion:

This article explains how to use PHP and Manticore Search to make key performance adjustments to search results. By installing and configuring Manticore Search, creating indexes and importing data, and performing search optimization, we can get a better search experience. Hopefully these examples will help developers optimize search results.

Reference materials:

• Manticore Search official website: https://manticoresearch.com/
• Sphinx client library: https://github.com/ pecl/sphinx

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