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） |
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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）
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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 idList = new ArrayList(); 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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