elasticsearch-java客户端测试
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1、环境准备
(1)添加依赖
<dependency> <groupId>org.elasticsearch.client</groupId> <artifactId>elasticsearch-rest-high-level-client</artifactId> </dependency> <dependency> <groupId>org.elasticsearch</groupId> <artifactId>elasticsearch</artifactId> </dependency>
(2)配置文件
application.yml
server: port: ${port:40100} spring: application: service-search elasticsearch: hostlist: - 127.0.0.1:9200 #多个节点中间用逗号分隔[addr1,addr2]
(3)创建配置类
package com.search.config; import java.util.ArrayList; import java.util.List; import org.apache.http.HttpHost; import org.elasticsearch.client.RestClient; import org.elasticsearch.client.RestHighLevelClient; import org.springframework.boot.context.properties.ConfigurationProperties; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import lombok.Getter; import lombok.Setter; @Configuration @ConfigurationProperties(prefix="elasticsearch") @Getter @Setter public class ElasticSearchConfig { private List<String> hostlist; @Bean public RestHighLevelClient restHighLevelClient(){ List<HttpHost> httpHostList = new ArrayList<>(hostlist.size()); //封装es服务端地址 for(String host:hostlist){ HttpHost httpHost = new HttpHost(host.split(":")[0], Integer.parseInt(host.split(":")[1]), "http"); httpHostList.add(httpHost); } return new RestHighLevelClient(RestClient.builder(httpHostList.toArray(new HttpHost[0]))); } //把低级客户端也注入,但是基本不用 @Bean public RestClient restClient(){ List<HttpHost> httpHostList = new ArrayList<>(hostlist.size()); //封装es服务端地址 for(String host:hostlist){ HttpHost httpHost = new HttpHost(host.split(":")[0], Integer.parseInt(host.split(":")[1]), "http"); httpHostList.add(httpHost); } return RestClient.builder(httpHostList.toArray(new HttpHost[0])).build(); } }
2、索引管理测试
package com.search.test; import java.io.FileInputStream; import org.apache.commons.io.IOUtils; import org.elasticsearch.action.admin.indices.create.CreateIndexRequest; import org.elasticsearch.action.admin.indices.create.CreateIndexResponse; import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest; import org.elasticsearch.action.admin.indices.delete.DeleteIndexResponse; import org.elasticsearch.client.IndicesClient; import org.elasticsearch.client.RestClient; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.xcontent.XContentType; import org.junit.Test; import org.junit.runner.RunWith; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.test.context.SpringBootTest; import org.springframework.test.context.junit4.SpringRunner; @SpringBootTest @RunWith(SpringRunner.class) public class TestIndex { @Autowired RestHighLevelClient client; @Autowired RestClient restClient; //创建索引库 @Test public void testCreateIndex()throws Exception{ //创建索引请求对象、并设置索引名称 CreateIndexRequest createIndexRequest = new CreateIndexRequest("course"); //设置参数 Settings settings = Settings.builder().put("number_of_shards", 1) .put("number_of_replicas",0) .build(); createIndexRequest.settings(settings); FileInputStream is = new FileInputStream(this.getClass().getResource("/").getPath()+"mapping.json"); String mappingJson = IOUtils.toString(is); System.err.println(mappingJson); //设置映射 createIndexRequest.mapping("doc",mappingJson,XContentType.JSON); //创建索引操作对象 IndicesClient indices = client.indices(); CreateIndexResponse createIndexResponse = indices.create(createIndexRequest); //获得相应是否成功 boolean acknowledged = createIndexResponse.isAcknowledged(); System.out.println(acknowledged); } //删除索引库 @Test public void testDeleteIndex()throws Exception{ //穿建删除索引库请求对象 DeleteIndexRequest deleteIndexRequest = new DeleteIndexRequest("course"); //删除索引库 DeleteIndexResponse deleteIndexResponse= client.indices().delete(deleteIndexRequest); //删除结果 boolean acknowledged = deleteIndexResponse.isAcknowledged(); System.out.println(acknowledged); } }
mapping.json
{
"properties": {
"description": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"name": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"pic":{
"type":"text",
"index":false
},
"price": {
"type": "float"
},
"studymodel": {
"type": "keyword"
},
"timestamp": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
}
}
这里特别注意: 使用了比例因子浮点数 ,索引库创建成功之后,在head客户端,数据浏览的字段结构中没有展示,但是实际数据中是存在的,已经成功了
3、文档管理测试
package com.xuecheng.search.test; import java.io.FileInputStream; import java.io.InputStream; import java.util.HashMap; import java.util.Map; import org.apache.commons.io.IOUtils; import org.elasticsearch.action.delete.DeleteRequest; import org.elasticsearch.action.delete.DeleteResponse; 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.update.UpdateRequest; import org.elasticsearch.action.update.UpdateResponse; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.xcontent.XContentType; import org.junit.Test; import org.junit.runner.RunWith; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.test.context.SpringBootTest; import org.springframework.test.context.junit4.SpringRunner; @SpringBootTest @RunWith(SpringRunner.class) public class TestDocument { @Autowired private RestHighLevelClient client; //添加文档 @Test public void testAddDoc() throws Exception{ //加载准备好了的json数据 InputStream is = new FileInputStream(this.getClass().getResource("/").getPath()+"document.json"); String docJsonStr = IOUtils.toString(is); System.err.println(docJsonStr); //获取索引库对象 IndexRequest indexRequest = new IndexRequest("course","doc"); //特别注意doc不要掉、否则报错org.elasticsearch.action.ActionRequestValidationException: Validation Failed: 1: type is missing; indexRequest.source(docJsonStr, XContentType.JSON); //往索引库添加文档,这个动作也叫索引 IndexResponse indexResponse = client.index(indexRequest); //打印结果 System.out.println(indexResponse.getResult()); } /** * 查询文档(根据id查) * 结果 * { * "description":"Bootstrap是由Twitter推出的一个前台页面开发框架,在行业之中使用较为广泛。 * 此开发框架包 含了大量的CSS、JS程序代码,可以帮助开发者(尤其是不擅长页面开发的程序人员) * 轻松的实现一个不受浏览器限制的 精美界面效果。", * "name":"Bootstrap开发框架", * "studymodel":"201001", * "price":62.658 * } */ @Test public void testGetDoc()throws Exception{ GetRequest getRequest = new GetRequest("course", "doc", "TOFP1mcBf3IfcTiHcsXB"); GetResponse getResponse = client.get(getRequest); if(getResponse.isExists()){ String sourceAsString = getResponse.getSourceAsString(); System.out.println(sourceAsString); } } /** * 更新文档 * 打印结果: OK * 注意这里采用的是局部更新:只修改map中设置的字段,没有的不会更新。 * 更新文档的实际顺序是: 检索文档、标记删除、创建新文档、删除原文档 * 创建新文档就会重构索引(分词-重构倒排索引树) * */ @Test public void testUpdateDoc()throws Exception{ UpdateRequest updateRequest = new UpdateRequest("course", "doc", "TOFP1mcBf3IfcTiHcsXB"); Map<String, String> map = new HashMap<String,String>(); map.put("name", "Bootstrap框架"); updateRequest.doc(map); UpdateResponse updateResponse = client.update(updateRequest); System.out.println(updateResponse.status()); } /** * 删除文档 * 打印结果:DELETED */ @Test public void testDelDoc() throws Exception{ DeleteRequest deleteRequest = new DeleteRequest("course", "doc", "TOFP1mcBf3IfcTiHcsXB"); DeleteResponse deleteResponse = client.delete(deleteRequest); System.out.println(deleteResponse.getResult()); } }
4、搜索管理测试
准备数据
初始化文档:
{
"name": "Bootstrap开发",
"description": "Bootstrap是由Twitter推出的一个前台页面开发框架,是一个非常流行的开发框架,此框架集成了多种页面效果。此开发框架包含了大量的CSS、JS程序代码,可以帮助开发者(尤其是不擅长页面开发的程序人员)轻松的实现一个不受浏览器限制的精美界面效果。",
"studymodel": "201002",
"price":38.6,
"timestamp":"2018-04-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
{
"name": "java编程基础",
"description": "java语言是世界第一编程语言,在软件开发领域使用人数最多。",
"studymodel": "201001",
"price":68.6,
"timestamp":"2018-03-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
{
"name": "spring开发基础",
"description": "spring 在java领域非常流行,java程序员都在用。",
"studymodel": "201001",
"price":88.6,
"timestamp":"2018-02-24 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
测试
package com.xuecheng.search.test; import org.elasticsearch.action.search.SearchRequest; import org.elasticsearch.action.search.SearchResponse; import org.elasticsearch.client.RestClient; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.index.query.BoolQueryBuilder; import org.elasticsearch.index.query.MatchQueryBuilder; import org.elasticsearch.index.query.MultiMatchQueryBuilder; import org.elasticsearch.index.query.QueryBuilders; import org.elasticsearch.index.query.TermQueryBuilder; import org.elasticsearch.index.query.TermsQueryBuilder; import org.elasticsearch.search.SearchHit; import org.elasticsearch.search.SearchHits; import org.elasticsearch.search.builder.SearchSourceBuilder; import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder; import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder.Field; import org.elasticsearch.search.sort.FieldSortBuilder; import org.elasticsearch.search.sort.SortOrder; import org.junit.Test; import org.junit.runner.RunWith; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.test.context.SpringBootTest; import org.springframework.test.context.junit4.SpringRunner; @SpringBootTest @RunWith(SpringRunner.class) public class TeseSearch { @Autowired RestHighLevelClient client; @Autowired RestClient restClient; /** * 查询type下所有文档 * 打印结果: * {"studymodel":"201002","name":"Bootstrap开发"} {"studymodel":"201001","name":"java编程基础"} {"studymodel":"201001","name":"spring开发基础"} 对应http请求json { "query": { "match_all": {} }, "_source": ["name","studymodel"] } */ @Test public void testSearchAll()throws Exception{ //1、构造sourceBuild(source源) SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.fetchSource(new String[]{"name","studymodel"}, new String[]{}) .query(QueryBuilders.matchAllQuery()); //2、构造查询请求对象 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //3、client 执行查询 SearchResponse searchResponse = client.search(searchRequest); //4、打印结果 SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 分页查询type下所有文档 * * json 参数 * { * "from":0, * "size":1, * "query": { * "match_all": {} * }, * "_source": ["name","studymodel"] * } * * 打印结果 * {"studymodel":"201002","name":"Bootstrap开发"} {"studymodel":"201001","name":"java编程基础"} */ @Test public void testSearchAllByPage()throws Exception{ //1、构造sourceBuild SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.fetchSource(new String[]{"name","studymodel"}, new String[]{}) .query(QueryBuilders.matchAllQuery()) .from(0).size(2);//分页查询,下表从0开始 //2、构造searchRequest请求对象 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //3、client执行请求 SearchResponse searchResponse = client.search(searchRequest); //4、打印结果 SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * term query: 精确查询、在搜索是会精确匹配关键字、搜索关键字不分词 * * json 参数 * { * * "query": { * "term": { * name: "spring" * } * }, * "_source": ["name","studymodel"] * } */ @Test public void testTermQuery()throws Exception{ //1、设置queryBuilder TermQueryBuilder termQueryBuild = QueryBuilders.termQuery("name","spring"); //2、设置sourceBuilder SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(termQueryBuild)//设置Term query查询 .fetchSource(new String[]{"name","studymodel"}, new String[]{}); //3、构造searchRequest SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //4、client发出请求 SearchResponse searchResponse = client.search(searchRequest); //5、打印结果 SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 根据id精确查询:根据提供的多个id去匹配 * * json 参数 * { * query{ "ids": { "type": "doc", "values": ["TeH_2WcBH5cUK","TuEB2mcBf3IfcTiHccWJ"] } * }, * "_source": ["name","studymodel"] * } */ @Test public void testIdsQuery()throws Exception{ //1、够着queryBuild //构造idList,注意数组每个元素必须是一个完整的id能匹配的上,第一条没有记录匹配上,第二条中 String[] idList = new String[]{"TeH_2WcBH5cUK","TuEB2mcBf3IfcTiHccWJ"}; TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("_id",idList);//特别注意用termsQuery,不要用termQuery //2、构造sourceBuilder SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(termsQueryBuilder) .fetchSource(new String[]{"name","studymodel"}, new String[]{});; //3、构造searchRequest SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //4、client执行 SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); //5、打印结果 for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * match Query就是全文检索,收缩方式就是先将搜索字符串分词、然后到索引分词列表去匹配 * json 参数 * { * query{ * "match": { * "descrition":{ //还是需要指定字段的,description是字段名 * "query": "世界第一", * "operate": "or" //or表示分词之后,只要有一个匹配即可,and表示分词在文档中都匹配才行 * } * }, * "_source": ["name","studymodel"] * } * } */ @Test public void testmatchQuery()throws Exception{ //queryBuild MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "世界第一"); //searchSorcebuilder SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(matchQueryBuilder) .fetchSource(new String[]{"name","studymodel"}, new String[]{}); //searchRequest SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //client->search SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); //print end for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * minimum_should_match: * or只能表示只要匹配一个即可、minimum_should_match可以指定文档匹配词的占比,注意这个占比的基数是搜索字符串分词的个数 * json 参数 * { * query{ * "match": { * "descrition":{ //还是需要指定字段的,description是字段名 * "query": "spring开发", * "minimun_should_match": "80%" * } * }, * "_source": ["name","studymodel"] * } * } */ @Test public void testMinimumShouldMatchQuery()throws Exception{ //queryBuild MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "世界第一") .minimumShouldMatch("80%"); //searchSourceBuilder SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(matchQueryBuilder) .fetchSource(new String[]{"name","studymodel"}, new String[]{}); //searchRequest SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * multi_match Query: * 用于一次匹配多个File进行全文检索、前面match都是一个Field * 多个字段可以通过提升boost(权重),来提高得分,实现排序靠前 * * json 参数 * { * query{ * "multi_match": { * "query": "spring css", //搜索字符串 * "minimum_should_match": "50%", * "fields": ["name^10","description"] //设置匹配name 和 description字段,将boost的boost提10倍 * } * } * } */ @Test public void testMultiMatchQuery()throws Exception{ //queryBuilder MultiMatchQueryBuilder matchQueryBuilder = QueryBuilders.multiMatchQuery("Spring框架","name","description") .minimumShouldMatch("50%")//设置百分比 .field("name", 10);//提升boost //searchSourceBuild SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(matchQueryBuilder); //searchRequest SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(searchSourceBuilder); //search SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 布尔查询 * 对应lucene的Boolean查询、实现将多个查询条件结合起来 * 三个参数: * must:只有符合所有查询的文档才被查询出来,相当于AND * should:至少符合其中一个,相当于OR * must_not:不能符合任意查询条件,相当于NOT * * json 参数 * { * "_source": ["name","pic"], * "from": 0, * "size": 1, * query{ * bool:{ * must: [ * { * "multi_match": { * "query": "spring框架", * "minimum_should_match": "50%", * "fields": ["name^10","description"] * } * },{ * "term": { * "studymodel": "201001" * } * } * ] * } * } * } */ @Test public void testBooleanQuery()throws Exception{ //1、够着QueryBuild //构造multiQureyBuilder MultiMatchQueryBuilder multiQueryBuilder = QueryBuilders.multiMatchQuery("Spring框架","name","description") .minimumShouldMatch("50%")//设置百分比 .field("name", 10); //构造termQueryBuilder TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201001"); //构造booleanQueryBuilder BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery() .must(multiQueryBuilder) .must(termQueryBuilder); //2、构造查询源 SearchSourceBuilder ssb = new SearchSourceBuilder(); ssb.fetchSource(new String[]{"name","pic"}, new String[]{}); ssb.query(boolQueryBuilder); //3、构造请求对象查询 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); searchRequest.source(ssb); //4、client执行查询 SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 过滤器: * 过滤器判断的是文档是否匹配,不去计算和判断文档的匹配度得分,所以过滤器性能比查询高、方便缓存 * 推荐尽量使用过滤器、或则过滤器搭配查询使用 * 过滤器使用的前提是bool查询 * 过滤器可以单独使用,但是不能提点multi Query, 因为过滤器每个Query都是单字段过滤 * * json 参数 * { * "_source": ["name","pic"], * "from": 0, * "size": 1, * query{ * bool:{ * must: [ * { * "multi_match": { * "query": "spring框架", * "minimum_should_match": "50%", * "fields": ["name^10","description"] * } * } * ], * fileter: [ * { * term: {"studymodel": "21001"} //针对字段进行过滤 * },{ * range: { //针对范围进行过滤 * "price": {"gte":60,"lte":100} * } * } * ] * } * } * } */ @Test public void testFileter()throws Exception{ //1、构造QueryBuild //构造multiQureyBuilder MultiMatchQueryBuilder multiQueryBuilder = QueryBuilders.multiMatchQuery("Spring框架","name","description") .minimumShouldMatch("50%")//设置百分比 .field("name", 10); //构造booleanQueryBuilder BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery() .must(multiQueryBuilder); //过滤 boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel", "201001")) .filter(QueryBuilders.rangeQuery("price").gte(60).lte(100)); //2、构造查询源 SearchSourceBuilder ssb = new SearchSourceBuilder(); ssb.fetchSource(new String[]{"name","pic"}, new String[]{}); ssb.query(boolQueryBuilder); //3、构造请求对象查询 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); searchRequest.source(ssb); //4、client执行查询 SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 排序: * 可以设置排序字段对查询结果进行排序 * keyword 、date 、float 等可以加 * 注意text 不能加 * * json 参数 * { * "_source": ["name","pic","description","price], * query{ * bool:{ * fileter: [ //过滤器也可以单独使用,但是只能用于单个字段 * { * term: {"studymodel": "21001"} //针对字段进行过滤 * },{ * range: { //针对范围进行过滤 * "price": {"gte":60,"lte":100} * } * } * ] * } * }, * "sort": [ * { * "studymodel": "desc" * },{ * "price": "asc" * } * ] * } */ @Test public void testSort()throws Exception{ //1、构造QueryBuild //构造booleanQueryBuilder BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); //过滤 boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel", "201001")) .filter(QueryBuilders.rangeQuery("price").gte(60).lte(100)); //2、构造查询源 SearchSourceBuilder ssb = new SearchSourceBuilder(); ssb.fetchSource(new String[]{"name","pic","studymodel","price"}, new String[]{}); ssb.query(boolQueryBuilder); ssb.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)); ssb.sort(new FieldSortBuilder("price").order(SortOrder.ASC)); //3、构造请求对象查询 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); searchRequest.source(ssb); //4、client执行查询 SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getSourceAsString()); } } /** * 高亮显示: * 将搜索结果中的一个或多个字突出显示,以便向用户展示匹配的关键字的位置 * * json 参数 */ @Test public void testHighlight()throws Exception{ //1、构造QueryBuild MultiMatchQueryBuilder multiQueryBuilder = QueryBuilders.multiMatchQuery("开发框架", "name","description") .field("name", 10) .minimumShouldMatch("50%"); //构造booleanQueryBuilder BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery() .must(multiQueryBuilder); //过滤 boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel", "201001")) .filter(QueryBuilders.rangeQuery("price").gte(60).lte(100)); //2、设置高亮 //设置标签 HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.preTags("<tag>")//设置签缀 .postTags("</tag>");//设置后缀 //设置高亮字段 highlightBuilder.fields().add(new Field("name")); highlightBuilder.fields().add(new Field("description")); //3、构造查询源 SearchSourceBuilder ssb = new SearchSourceBuilder(); ssb.fetchSource(new String[]{"name","pic","studymodel","price"}, new String[]{}) .query(boolQueryBuilder) .sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)) .sort(new FieldSortBuilder("price").order(SortOrder.ASC)) .highlighter(highlightBuilder); //4、构造请求对象查询 SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc") .source(ssb); //5、client执行查询 SearchResponse searchResponse = client.search(searchRequest); //6、取出高亮字段 SearchHits hits = searchResponse.getHits(); for(SearchHit hit:hits){ System.out.println(hit.getHighlightFields()); } } }