ThinkPHP6 full-text search function implementation guide: comprehensive search data

ThinkPHP6 Full-text Search Function Implementation Guide: Comprehensive Search Data

Introduction
Full-text search is an important data retrieval technology that can quickly find items containing specified keywords The data. In web application development, we often need to implement full-text search functions to improve user experience and data query efficiency. This article will introduce how to use the ThinkPHP6 framework to implement the full-text search function and provide specific code examples.

1. Install Elasticsearch
   Elasticsearch is a powerful open source search engine that provides full-text search, distributed search and analysis functions. First, we need to install Elasticsearch and start it. For specific operations, please refer to the official Elasticsearch documentation.
2. Configuring the database
   In ThinkPHP6, we can use the database to store data that requires full-text search. First, you need to configure the database connection information in the config/database.php file.

// 数据库配置
'database'  => [
    // 数据库类型
    'type'     => 'mysql',
    // 服务器地址
    'hostname' => '127.0.0.1',
    // 数据库名
    'database' => 'your_database',
    // 用户名
    'username' => 'your_username',
    // 密码
    'password' => 'your_password',
    // 端口
    'hostport' => '3306',
    // 数据库连接参数
    'params'   => [],
    // 数据库编码默认采用utf8
    'charset'  => 'utf8',
    // 数据库表前缀
    'prefix'   => 'your_prefix_',
],

3. Install the Elasticsearch plug-in
   In ThinkPHP6, we can use the topthink/think-elasticsearch extension to conveniently operate Elasticsearch. First, you need to use Composer to install the extension:

composer require topthink/think-elasticsearch

Then, you need to configure the Elasticsearch connection information in the config/service.php file:

// Elasticsearch配置
'elastic' => [
    // Elasticsearch服务器地址
    'host' => '127.0.0.1',
    // Elasticsearch服务器端口
    'port' => 9200,
    // Elasticsearch用户名
    'username' => 'your_username',
    // Elasticsearch密码
    'password' => 'your_password',
    // Elasticsearch索引前缀
    'prefix' => 'your_index_prefix_',
],

4. Create index and model
   First, we need to create an index to store the data that requires full-text search. Execute the following command in the command line:

php think elasticsearch:makeIndex Article

This will create an index named article. Next, we need to create a data table corresponding to the index in the database and create a model to operate the data table. Execute the following command:

php think make:model model/Article

This creates a data table and model named Article. In the model class, we need to define the index and field mapping relationship of Elasticsearch, as well as some fields that require full-text search:

namespace appmodel;

use thinkesModel;

class Article extends Model
{
    // Elasticsearch索引名称
    protected $index = 'article';

    // Elasticsearch映射关系
    protected $mapping = [
        'properties' => [
            'title' => [
                'type' => 'text',
                'analyzer' => 'ik_max_word',
            ],
            'content' => [
                'type' => 'text',
                'analyzer' => 'ik_max_word',
            ],
        ],
    ];

    // 全文搜索字段
    protected $searchFields = ['title', 'content'];
}

5. Index data
   After inserting the data into the database, we need to Indexed into Elasticsearch for full-text search. In the model class, you can use the index method to implement data indexing, for example:

use appmodelArticle;

// 获取要索引的数据
$data = Article::where('status', 1)->select();

// 索引数据
Article::index($data);

6. Search data
   When we need to search for data, we can use the model class The search method performs full-text search. For example, search for articles containing the keyword "ThinkPHP" in the title:

use appmodelArticle;

$keyword = 'ThinkPHP';
$articles = Article::search($keyword)->select();

foreach ($articles as $article) {
    echo $article->title;
    echo $article->content;
}

Summary
Through the above steps, we can implement the full-text search function in the ThinkPHP6 framework. Using Elasticsearch as a search engine and cooperating with the database operation of ThinkPHP6 can realize comprehensive search of data and improve query efficiency. Hope this article can be helpful to you.

Reference link:

• Elasticsearch official document: https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
• ThinkPHP6 official documentation: https://www.kancloud.cn/manual/thinkphp6_0/1037649

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