Detailed explanation of the integration of PHP and Elasticsearch to realize full-text search function

With the development of the Internet, enterprises face increasingly large amounts of text data. How to quickly and accurately retrieve relevant content has become one of the important issues for enterprises in the information field. As an open source search engine based on Lucene, Elasticsearch has the characteristics of high availability, high scalability and fast retrieval, making it one of the preferred solutions for enterprise full-text retrieval. As a popular server-side programming language, PHP can also quickly carry out web development and API development, and has become one of the commonly used languages ​​​​integrated with Elasticsearch.

This article mainly explains the detailed steps of integrating PHP and Elasticsearch to realize the full-text search function.

1. Introduction to Elasticsearch

Elasticsearch is an open source search engine based on Lucene that can be used to quickly and accurately retrieve large amounts of text data. Elasticsearch adopts a distributed storage architecture, supports horizontal expansion, and can adapt to the needs of massive data storage and fast retrieval.

Elasticsearch provides a RESTful API interface, supports data interaction in JSON format, and can be integrated with commonly used programming languages. In Elasticsearch, data is stored according to documents. Each document contains multiple fields, and each field can be nested to contain other fields, making the data structure more flexible. At the same time, Elasticsearch supports full-text retrieval, exact matching, aggregation, analysis and other operations on documents.

2. Integration of PHP and Elasticsearch

1. Install the Elasticsearch-PHP library

Elasticsearch-PHP is the official PHP client library that encapsulates Elasticsearch The RESTful API interface makes it easy to operate Elasticsearch in PHP applications. We can install the library through Composer and execute the following command:

composer require elasticsearch/elasticsearch

2. Connect to Elasticsearch

Before connecting to Elasticsearch, you need to start the Elasticsearch service. To use the Elasticsearch-PHP library to connect to Elasticsearch in PHP, you need to instantiate the ElasticsearchClient object first, and set the connected Elasticsearch server IP and port:

require 'vendor/autoload.php';

$client = ElasticsearchClientBuilder::create()->setHosts(['http://127.0.0.1:9200'])->build();

Among them, the setHosts() method passes in an array parameter, each element Represents an Elasticsearch server, and multiple servers can be set up to achieve high availability and load balancing.

3. Create Index

In Elasticsearch, an index is a data structure used to store and retrieve similar data, similar to a table in a database. You can create an index named "my_index" through the following code:

$params = [
    'index' => 'my_index',
    'body' => [
        'settings' => [
            'number_of_shards' => 5, // 分片数
            'number_of_replicas' => 1, // 副本数
        ],
    ],
];

$response = $client->indices()->create($params);

Among them, in the $params array parameter, 'settings' represents the settings of the index, including information such as the number of shards and the number of copies. 'body' represents the mapping of the index. You can set the fields and types of the index in this parameter.

4. Add documents

Add documents in Elasticsearch, which can be achieved through the following code:

$params = [
    'index' => 'my_index',
    'id' => '1',
    'body' => [
        'title' => 'Elasticsearch PHP集成',
        'content' => 'Elasticsearch是一款基于Lucene的开源搜索引擎...'
    ]
];

$response = $client->index($params);

Among them, in the $params array parameter, 'index' Represents the index name of the document to be added; 'id' represents the unique identifier of the document, an optional parameter; 'body' represents the content of the document, and multiple fields and values ​​can be set.

5. Search for documents

Searching for documents in Elasticsearch can be achieved through the following code:

$params = [
    'index' => 'my_index',
    'body'  => [
        'query' => [
            'match' => [
                'title' => 'Elasticsearch PHP'
            ]
         ]
    ]
];

$response = $client->search($params);

Among them, in the $params array parameter, 'index' Indicates the index name of the document to be searched; 'body' indicates query conditions, and multiple query conditions and sorting rules can be set.

3. Full-text retrieval using PHP Elasticsearch

1. Establishing an index

Before using Elasticsearch to implement full-text retrieval, the data to be retrieved needs to be indexed first. When building an index, you can set the field to be retrieved to the text type, so that full-text indexing can be performed.

In this example, assume that the data to be retrieved is a student table, containing the fields id, name, age and score. We can create an index named "student" through the following code:

$params = [
    'index' => 'student',
    'body' => [
        'settings' => [
            'number_of_shards' => 5,
            'number_of_replicas' => 1,
        ],
        'mappings' => [
            'properties' => [
                'id' => ['type' => 'integer'],
                'name' => ['type' => 'text', 'analyzer' => 'ik_max_word'],
                'age' => ['type' => 'integer'],
                'score' => ['type' => 'double']
            ]
        ]
    ]
];

$response = $client->indices()->create($params);

Among them, the type of the 'name' field is set to text, and a word segmenter is specified. The Chinese word segmentation plug-in ik_max_word is used here, and you can Chinese text is processed in a way that maximizes word segmentation.

2. Add documents

After the index is created, you can add documents to the index. Suppose you want to add a student information, you can use the following code to achieve:

$params = [
    'index' => 'student',
    'body' => [
        'id' => 1,
        'name' => '张三',
        'age' => 18,
        'score' => 90.5
    ]
];

$response = $client->index($params);

You can add multiple documents to the index through loop addition.

3. Search for documents

After indexing and adding documents, full-text search can be performed. In this example, match query is used to achieve full-text search, which can be searched by entering keywords. This can be achieved through the following code:

$params = [
    'index' => 'student',
    'body'  => [
        'query' => [
            'match' => [
                'name' => '张三'
            ]
         ]
    ]
];

$response = $client->search($params);

Among them, the 'name' field is used for matching and can be replaced with other fields that require full-text retrieval. The information returned by the search results is in $response, and the query results can be obtained and displayed.

4. Summary

This article introduces the detailed steps for integrating PHP and Elasticsearch to realize the full-text search function. Through the steps of connecting to Elasticsearch, building indexes, adding documents, and searching documents, you can quickly and accurately retrieve large amounts of text data. When performing full-text search, it is recommended to use a word segmenter to segment Chinese to improve search accuracy and efficiency.

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