ElasticSearch如何使用以及java代码如何查询并排序ES中的数据（距离排序）返回距离

一.环境准备

1.elasticsearch压缩包、kibana插件、head-master插件，具体怎么安装配置，小伙伴们可以自行百度网上很多案例

可参考：https://blog.csdn.net/sinat_42338962/article/details/85227902

这里说一下，国内下载一般都很慢，可以参考这篇文章，博主都放在百度云，下载很方便

文章链接：https://blog.csdn.net/weixin_37281289/article/details/101483434

2.head插件使用，在elasticsearch-head-master根目录下执行npm run start，访问http://localhost:9100/即可查询并操作ES中数据，

3.kibana使用。在kibana/bin文件夹下，执行kibana.bat，访问http://localhost:5601/进行管理界面，在dev toos可进行操作数据，如下

4.查询数据之前首先要创建索引和定义数据类型，比如你想存放哪些字段（时间，经纬度，部门等）

PUT hbp
{
      "settings": {
        "number_of_shards": 5,
        "number_of_replicas": 1
    },
  "mappings": {

      "properties": {
         "id": {
            "type": "text"
            },
          "name": {
            "type": "text"
          },
          "dept": {
            "type": "text"
          },
          "location":{
            "type": "geo_point"
          },
          "pub_date":{
            "type": "date",
            "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd"
          }
    }
     
  }
}

5.再用脚本新增数据，或者用java代码连接es新增数据

PUT hbp/_doc/2
{
"name":"李四",
"pub_date":"2020-09-02 11:30:00",
"dept":"研发二部",
"location":{
  "lat":39.669607,
  "lon":118.257638
}
}

二：这里重点讲一下java根据距离范围查询并通过距离排序，当然下面代码中也有其他的查询和排序，仅供参考，这里需要先在pom.xml引入依赖，注意版本号一致

org.elasticsearch.client elasticsearch-rest-high-level-client 7.3.2 org.elasticsearch elasticsearch 7.3.2
接下来直接上代码

package com.zzht.esDemo;

import java.net.UnknownHostException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;

import org.junit.Test;

import org.apache.http.HttpHost;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.HttpAsyncResponseConsumerFactory;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.geo.GeoDistance;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.TransportAddress;
import org.elasticsearch.common.unit.DistanceUnit;
import org.elasticsearch.common.unit.TimeValue;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.GeoDistanceQueryBuilder;
import org.elasticsearch.index.query.GeoValidationMethod;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.sort.GeoDistanceSortBuilder;
import org.elasticsearch.search.sort.SortBuilders;
import org.elasticsearch.search.sort.SortOrder;
import org.elasticsearch.transport.client.PreBuiltTransportClient;

import java.io.IOException;
import java.net.InetAddress;
import java.net.UnknownHostException;

/**
 * es测试
 *
 */
public class EsDemo 
{
    private static final RequestOptions COMMON_OPTIONS;

    static {
        RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();

        // 默认缓存限制为100MB，此处修改为30MB。
        builder.setHttpAsyncResponseConsumerFactory(
                new HttpAsyncResponseConsumerFactory
                        .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024));
        COMMON_OPTIONS = builder.build();
    }
    
    
       protected RestHighLevelClient client =  new RestHighLevelClient(
               RestClient.builder(new HttpHost("127.0.0.1", 9200, "http")));;
       
       private String indexName = "hbp";
       private String type = "_doc";
       
    //从ES中查询数据
    @Test
    public void test1() throws IOException {
        Integer pageSize = 10;
        Integer PageNum = 0;
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        BoolQueryBuilder bq = QueryBuilders.boolQuery();
        //按时间范围查询
        QueryBuilder dateBuilder = QueryBuilders.rangeQuery("pub_date")
                .gte("2020-09-01 10:30:00").lte("2020-09-02 13:50:00").format("yyyy-MM-dd HH:mm:ss");//时间范围查询
    
        
        //根据id查询
        List<String> idList = new ArrayList<String>();
        idList.add("1");
        idList.add("2");
        idList.add("3");
//        idList.add("4");
//        idList.add("5");
        QueryBuilder idBuilder = QueryBuilders.termsQuery("_id", idList);
        // 以某点为中心，搜索指定范围
        GeoDistanceQueryBuilder distanceQueryBuilder = new GeoDistanceQueryBuilder("location");
        distanceQueryBuilder.point(39.662263, 118.197815);
        //查询单位：km
        distanceQueryBuilder.distance("6", DistanceUnit.KILOMETERS);
        //构建检索
        /*这里说明一下，distanceQueryBuilder就是距离查询条件，idBuilder就是id过滤条件，
        dateBuilder就是时间范围查询条件，可以定义一个或多个条件（QueryBuilder），下面的
        排序也是同理，可以构造多个sortBuilder*/
        QueryBuilder query = bq
//                .filter(distanceQueryBuilder)
//                .must(idBuilder)
                .filter(dateBuilder)
                ;
        searchSourceBuilder.query(query);

        //按时间排序
//      searchSourceBuilder.sort("pub_date", SortOrder.DESC);

        
        //按距离排序
        GeoDistanceSortBuilder distanceSort = SortBuilders.geoDistanceSort("location", 39.662263, 118.197815);
        distanceSort.order(SortOrder.ASC);
        distanceSort.geoDistance(GeoDistance.ARC);
        distanceSort.unit(DistanceUnit.KILOMETERS);
        distanceSort.validation(GeoValidationMethod.STRICT);
        
        searchSourceBuilder.sort(distanceSort);
        
        
        //查询es数据
        searchSourceBuilder.from(PageNum);
        searchSourceBuilder.size(pageSize);
        searchSourceBuilder.timeout(new TimeValue(100,TimeUnit.SECONDS));
        SearchRequest searchRequest = new SearchRequest("hbp");
        searchRequest.source(searchSourceBuilder);
        SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHits hits = response.getHits();
        for(SearchHit hit : hits){
            System.out.println(hit.getSourceAsString());
            System.out.println(hit.getSortValues()[0]);//获取排序的距离，index为排序的位置
        }
        
        
        
        
        //get方式数据查询 ,参数为Index,type和id
//        GetRequest  request = new GetRequest(indexName, "7");
//        GetResponse getResponse1 = client.get(request, COMMON_OPTIONS);
//        System.out.println(getResponse1.getSourceAsString());
        client.close();
    }
    
    
    
    
    
    
    
  //插入数据
    
    public void test2() throws IOException {
         String jsonStr = "{"name":"开发004","pub_date":"2020-09-05 18:00:00","dept":"研发一部","location":{"lon":118.250192,"lat":39.691231}}";
        IndexRequest request = new IndexRequest(indexName);    
        request.source(jsonStr, XContentType.JSON);
        IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);
        System.out.println(indexResponse.getResult());
    }

}


执行上面代码的test1方法，输出结果如下：

这个主要是根据经纬度来查询某个点方圆半径内的数据，比如附近5km内的餐馆

另外贴下根据父文档查询子文档代码写法

//父级查询结果返回字段设置
// FetchSourceContext fetchSourceContext = new FetchSourceContext(true,new String[]{“formObject”},null);
// HasParentQueryBuilder parentCondition = JoinQueryBuilders.hasParentQuery(“procinst”, //父文档type
// bqParent,false);//.innerHit(new InnerHitBuilder().setFetchSourceContext(fetchSourceContext));//设置父级（流程实例）返回字段
//
// queryChild.filter(parentCondition);

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