java 使用ElasticSearch完成百万级数据查询附近的人功能

下面是详细的“java 使用ElasticSearch完成百万级数据查询附近的人功能”的攻略：

一、准备工作

1. 安装Elasticsearch

首先需要在本地安装Elasticsearch，可以到官方网站下载并安装。也可以使用Docker进行安装。

2. 安装Elasticsearch客户端

在Java代码中使用Elasticsearch，需要引入Elasticsearch客户端的依赖。可以使用Maven在pom.xml文件中添加以下依赖：

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

3. 准备测试数据

为了测试百万级数据的查询，需要准备一份大规模的测试数据。可以使用Mockaroo等在线工具生成大规模的随机数据，并将其保存在文件中。

二、创建索引

在Elasticsearch中，数据存储在索引中。因此，需要先创建一个索引来存储测试数据。可以使用Elasticsearch客户端的API来创建索引。下面是示例代码：

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.settings.Settings;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.index.mapper.ObjectMapper;
import org.elasticsearch.index.mapper.ObjectMapper.Builder;
import org.elasticsearch.index.mapper.ObjectMapper.StaticBuilderFactory;
import org.elasticsearch.index.mapper.ObjectMapper.BuilderFactory;
import org.elasticsearch.index.mapper.ParseContext;
import org.elasticsearch.index.mapper.ParsedDocument;
import org.elasticsearch.index.mapper.ParsedDocumentBuilder;
import org.elasticsearch.index.mapper.TypeParser;
import org.elasticsearch.index.mapper.core.CompletionFieldMapper;
import org.elasticsearch.index.mapper.core.DateFieldMapper;
import org.elasticsearch.index.mapper.core.StringFieldMapper;
import org.elasticsearch.index.mapper.core.TokenCountFieldMapper;
import org.elasticsearch.index.mapper.geo.GeoPointFieldMapper;

import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

public class IndexCreator {
    private RestHighLevelClient client;
    private String indexName = "test_data";

    public IndexCreator(RestHighLevelClient client) {
        this.client = client;
    }

    public void createIndex() throws IOException {
        CreateIndexRequest request = new CreateIndexRequest(indexName);
        request.settings(Settings.builder()
                .put("index.number_of_shards", 1)
                .put("index.number_of_replicas", 0)
        );

        Map<String, Object> mapping = new HashMap<>();
        Map<String, Object> properties = new HashMap<>();

        properties.put("id", StringFieldMapper.builder("id").build());
        properties.put("name", StringFieldMapper.builder("name").build());
        properties.put("location", GeoPointFieldMapper.builder("location").build());
        properties.put("address", StringFieldMapper.builder("address").build());

        mapping.put("properties", properties);

        request.mapping(mapping);

        CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);
        System.out.println(response);
    }
}

上述代码中，创建了一个名为“test_data”的索引，指定了其数据为GeoPoint类型。

三、导入数据

索引创建完成之后，需要将测试数据导入到其对应的索引中。可以使用Elasticsearch客户端的API来完成数据的导入。下面是示例代码：

import org.elasticsearch.action.bulk.BulkRequest;
import org.elasticsearch.action.bulk.BulkResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.xcontent.XContentType;

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.IOException;

public class DataImporter {
    private RestHighLevelClient client;
    private String indexName = "test_data";

    public DataImporter(RestHighLevelClient client) {
        this.client = client;
    }

    public void importData() throws IOException {
        BulkRequest bulkRequest = new BulkRequest();
        File file = new File("test_data.json");
        BufferedReader reader = new BufferedReader(new FileReader(file));
        String line;
        while ((line = reader.readLine()) != null) {
            bulkRequest.add(new IndexRequest(indexName).source(line, XContentType.JSON));
        }
        BulkResponse bulkResponse = client.bulk(bulkRequest, RequestOptions.DEFAULT);
        System.out.println(bulkResponse);
    }
}

上述代码中，读取了以JSON格式保存的测试数据，并使用Bulk API将其导入到“test_data”索引中。

四、查询附近的人

当索引和测试数据导入完成后，就可以开始对其进行查询了。这里我们使用Geo查询来查询附近的人。下面是示例代码：

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.common.geo.GeoDistance;
import org.elasticsearch.common.geo.GeoPoint;
import org.elasticsearch.common.unit.DistanceUnit;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.builder.SearchSourceBuilder;

public class NearbySearcher {
    private RestHighLevelClient client;
    private String indexName = "test_data";

    public NearbySearcher(RestHighLevelClient client) {
        this.client = client;
    }

    public void searchNearby() throws IOException {
        SearchRequest searchRequest = new SearchRequest(indexName);
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        GeoPoint location = new GeoPoint(39.9289, 116.3883);
        searchSourceBuilder.query(QueryBuilders.geoDistanceQuery("location")
                .point(location.getLat(), location.getLon())
                .distance(1, DistanceUnit.KILOMETERS)
                .geoDistance(GeoDistance.PLANE));

        searchRequest.source(searchSourceBuilder);

        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        System.out.println(searchResponse);
    }
}

上述代码中，首先指定了查询的中心位置。然后，使用Geo查询查询距离中心位置1公里以内（使用PLANE方式计算距离）的所有文档。最后，使用Search API完成查询操作。

五、示例运行

我们可以将以上三个类用于完成创建索引、导入数据和查询附近的人的相关操作。下面是示例代码：

import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.indices.IndexTemplatesExistRequest;

import java.io.IOException;
import java.util.logging.Level;
import java.util.logging.Logger;

public class Application {
    private static final Logger logger = Logger.getLogger(Application.class.getName());

    public static void main(String[] args) {
        try (RestHighLevelClient client = new RestClientBuilder().build()) {
            IndexCreator indexCreator = new IndexCreator(client);
            indexCreator.createIndex();

            DataImporter dataImporter = new DataImporter(client);
            dataImporter.importData();

            NearbySearcher nearbySearcher = new NearbySearcher(client);
            nearbySearcher.searchNearby();
        } catch (IOException e) {
            logger.log(Level.SEVERE, e.getMessage(), e);
        }
    }
}

上述代码中，我们使用了RestClientBuilder创建了一个RestHighLevelClient，并分别用IndexCreator，DataImporter和NearbySearcher进行创建索引、导入数据和查询附近的人的操作。运行代码，即可得到查询结果。

六、总结

以上便是“java 使用ElasticSearch完成百万级数据查询附近的人功能”的完整攻略。在实际生产环境中，还需要关注Elasticsearch的性能调优、错误处理等内容。