PHP and Manticore Search Development Guide: Highly Customizable Search Filters

PHP and Manticore Search Development Guide: Highly Customized Search Filters

Introduction:
In modern web applications, search functionality is a crucial part. The quality of the search function directly affects the user's experience of the website. In order to achieve efficient search functions, developers need to choose an appropriate search engine and customize it according to their own needs. In this article, we will cover how to develop highly customized search filters using PHP and the Manticore Search search engine.

1. What is Manticore Search?
Manticore Search is a high-performance, free and open source full-text search engine. It is based on the Sphinx search engine and adds many new features and improvements, such as full-text search, distributed indexing, real-time index updates, etc. Manticore Search provides rich API and client support, which greatly simplifies the process for developers to use search functions.

2. Install and configure Manticore Search

1. Download and install Manticore Search: According to the guidelines of the official documentation, download and install the Manticore Search version suitable for your system.

2. Create an index: Use the tools provided by Manticore Search to create the index you need. For example, if you want to create an index for article search, you can use the following command:

   indexer --config /path/to/config.conf --rotate --all

3. Configure the search service: Edit the configuration file of Manticore Search and set parameters such as the listening port and index path. An example is as follows:

   searchd {
    listen = localhost:9306
    pid_file = /path/to/searchd.pid
    log = /path/to/searchd.log
    query_log = /path/to/query.log
   }

4. Start the search service: Use the following command to start the search service:

   searchd --config /path/to/config.conf

3. Use PHP to search

1. Install the PHP client library of Manticore Search (manticoresearch/manticoresearch):

   composer require manticoresearch/manticoresearch

2. Create a search connection:

   $client = new ManticoresearchClient(['host' => 'localhost', 'port' => 9308]);

3. Execute search query:

   $params = [
    'index' => 'articles',
    'body' => [
        'query' => [
            'match' => [
                'title' => 'PHP'
            ]
        ]
    ]
   ];
   
   $response = $client->search($params);

4. Customize search filters

1. ##Add filters based on keywords:

   $params = [
    'index' => 'articles',
    'body' => [
        'query' => [
            'match' => [
                'title' => 'PHP'
            ]
        ],
        'filter' => [
            'term' => [
                'category' => 'Tutorial'
            ]
        ]
    ]
   ];
   
   $response = $client->search($params);

2. Combine multiple filters:

   $params = [
    'index' => 'articles',
    'body' => [
        'query' => [
            'match' => [
                'title' => 'PHP'
            ]
        ],
        'filter' => [
            'bool' => [
                'must' => [
                    ['term' => ['category' => 'Tutorial']],
                    ['term' => ['author' => 'John']]
                ],
                'must_not' => [
                    ['term' => ['status' => 'Draft']]
                ]
            ]
        ]
    ]
   ];
   
   $response = $client->search($params);

3. Range filter:

   $params = [
    'index' => 'articles',
    'body' => [
        'query' => [
            'match' => [
                'title' => 'PHP'
            ]
        ],
        'filter' => [
            'range' => [
                'created_at' => [
                    'gte' => '2022-01-01',
                    'lte' => '2022-12-31'
                ]
            ]
        ]
    ]
   ];
   
   $response = $client->search($params);

Conclusion:

Introduction to this article Learn how to develop highly customized search filters using PHP and the Manticore Search search engine. Through the API and PHP client library provided by Manticore Search, we can easily implement various search needs, including keyword filtering, multiple filtering conditions, and range filtering. I hope this article will be helpful to developers when building efficient search capabilities.

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