How to use Java to develop a full-text search application based on Elasticsearch

How to use Java to develop a full-text retrieval application based on Elasticsearch

Full-text retrieval is a very important technology in today's information age. It can quickly and accurately retrieve data from Search a large amount of text data for keywords or related information that users need. As an open source distributed search engine, Elasticsearch has been widely used for its efficient full-text retrieval capabilities, real-time data analysis and scalability. This article will introduce how to use Java to develop a full-text search application based on Elasticsearch, and provide specific code examples.

1. Preparation work
   Before starting development, we need to prepare the following work:
2. Install the Java development environment (JDK)
3. Install the Elasticsearch server, and Start the service
4. Import the Elasticsearch Java client library, for example, use Maven to import the following dependencies:

<dependencies>
  <dependency>
    <groupId>org.elasticsearch</groupId>
    <artifactId>elasticsearch</artifactId>
    <version>7.10.0</version>
  </dependency>
</dependencies>

2. Create the Elasticsearch client
   First, we need to create a Client used to connect to the Elasticsearch server. You can create a client instance using the following code:

import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;

public class ElasticsearchClient {
    public static RestHighLevelClient createClient() {
        // 配置Elasticsearch服务器地址
        RestClientBuilder builder = RestClient.builder(new HttpHost("localhost", 9200, "http"));
        // 创建高级客户端实例
        RestHighLevelClient client = new RestHighLevelClient(builder);
        return client;
    }
}

3. Create Index
   Next, we need to create an index (Index) to store our document data. Indexes are similar to tables in a database, and we can store different types of document data in different indexes. You can use the following code to create an index:

import org.elasticsearch.action.admin.indices.create.CreateIndexRequest;
import org.elasticsearch.action.admin.indices.create.CreateIndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import org.elasticsearch.common.xcontent.XContentFactory.*;

public class IndexCreator {
    public static void createIndex(String indexName) {
        try {
            RestHighLevelClient client = ElasticsearchClient.createClient();
            
            // 创建索引请求
            CreateIndexRequest request = new CreateIndexRequest(indexName);
            
            // 设置索引的映射规则
            XContentBuilder mappingBuilder = XContentFactory.jsonBuilder();
            mappingBuilder.startObject();
            mappingBuilder.startObject("properties");
            mappingBuilder.startObject("title");
            mappingBuilder.field("type", "text");
            mappingBuilder.endObject();
            mappingBuilder.startObject("content");
            mappingBuilder.field("type", "text");
            mappingBuilder.endObject();
            mappingBuilder.endObject();
            mappingBuilder.endObject();
            
            request.mapping(mappingBuilder);
            
            // 执行创建索引请求
            CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);
            
            // 处理响应结果
            if (response.isAcknowledged()) {
                System.out.println("索引创建成功：" + indexName);
            } else {
                System.out.println("索引创建失败：" + indexName);
            }
            
            // 关闭客户端连接
            client.close();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

4. Index document
   After having the index, we can store the document data into the index. A document is similar to a record in a database. We can store multiple documents under the same index. You can use the following code to store document data in the index:

import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.xcontent.XContentType;

public class DocumentIndexer {
    public static void indexDocument(String indexName, String documentId, String title, String content) {
        try {
            RestHighLevelClient client = ElasticsearchClient.createClient();
            
            // 创建文档索引请求
            IndexRequest request = new IndexRequest(indexName);
            request.id(documentId);
            request.source("title", title);
            request.source("content", content);
            
            // 执行文档索引请求
            IndexResponse response = client.index(request, RequestOptions.DEFAULT);
            
            // 处理响应结果
            if (response.status().getStatus() == 201) {
                System.out.println("文档索引成功：" + documentId);
            } else {
                System.out.println("文档索引失败：" + documentId);
            }
            
            // 关闭客户端连接
            client.close();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

5. Search for documents
   With the document index, we can search for documents containing keywords through full-text retrieval. . You can use the following code to perform document search:

import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.QueryBuilders.*;
import org.elasticsearch.search.builder.SearchSourceBuilder;

public class DocumentSearcher {
    public static void searchDocument(String indexName, String keyword) {
        try {
            RestHighLevelClient client = ElasticsearchClient.createClient();
            
            // 创建搜索请求
            SearchRequest request = new SearchRequest(indexName);
            SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
            sourceBuilder.query(QueryBuilders.matchQuery("content", keyword));
            request.source(sourceBuilder);
            
            // 执行搜索请求
            SearchResponse response = client.search(request, RequestOptions.DEFAULT);
            
            // 处理响应结果
            if (response.getHits().getTotalHits().value > 0) {
                System.out.println("搜索结果：");
                for (SearchHit hit : response.getHits().getHits()) {
                    System.out.println(hit.getSourceAsString());
                }
            } else {
                System.out.println("未找到相关文档");
            }
            
            // 关闭客户端连接
            client.close();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Using the above code example, we can complete the development of a full-text retrieval application based on Elasticsearch. By creating an index, indexing documents, and searching documents, we can achieve efficient and accurate full-text retrieval. Of course, in addition to the basic functions shown above, Elasticsearch also supports various advanced queries, aggregate analysis, distributed deployment and other features, and can be further developed and expanded according to specific needs. I hope this article is helpful to you, and I wish you greater success in the field of full-text retrieval!

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