Elasticsearch 是一个分布式、高扩展、高实时的搜索与数据分析引擎。它能很方便的使大量数据具有搜索、分析和探索的能力。
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put/post请求:
http://localhost:9200/索引库名称
{ "settings":{ "index":{ "number_of_shards":1, # 分片数量,存储到不同的节点,提高处理能力和高可用性 刚开始是一个 这里没有集成 "number_of_replicas":0 # 每个节点的副本数量,提高 高可用性 } } } get http://localhost:9200/索引库名称 查询创建索引的信息 2.post http://localhost:9200/索引库名称/类型名称/_mapping post 请求:http://localhost:9200/xc_course/doc/_mapping ~~~java { "properties": { "name": { "type": "text" // varchar }, "description": { "type": "text" }, "studymodel": { "type": "keyword" } } } ~ 3.put 或Post http://localhost:9200/xc_course/doc/id值 (如果不指定id值ES会自动生成ID) http://localhost:9200/xc_course/doc/1 java { "name":"Bootstrap开发框架", "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。", "studymodel":"201001" } 4.根据课程id查询文档 发送:get http://localhost:9200/xc_course/doc/1 5. 发送 get http://localhost:9200/xc_course/doc/_search 查询全部的数据 6. 查询名称中包括spring 关键字的的记录 发送:get http://localhost:9200/xc_course/doc/_search?q=name:bootstrap 7.post 发送:localhost:9200/_analyze { "text":"郭", --这里没有写到main.dic文件中去就是一个一个的字 "analyzer":"ik_max_word" } {"text":"测试分词器,后边是测试内容:spring cloud实战", "analyzer":"ik_max_word" -- 分词器 精确一点 "analyzer":"ik_smart" -- 分词器 大体一下 } 8.GET: http://localhost:9200/(不止一个index那就要指定名字)_mapping 就是查看index 所有的属性和字段 { "gsx_frank": { "mappings": { "doc": { "properties": { "description": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "name": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "studymodel": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } } } } } } } body 请求体中的 application/json 9.delete请求:`http://localhost:9200/索引库名称` analyzer和search_analyzer 的区别 说明 分析器(analyzer)主要有两种情况会被使用: 插入文档时,将text类型的字段做分词然后插入倒排索引,。 在查询时,先对要查询的text类型的输入做分词,再去倒排索引搜索。 在索引(即插入文档)时,只会去看字段有没有定义analyzer,有定义的话就用定义的,没定义就用ES预设的。 在查询时,会先去看字段有没有定义search_analyzer,如果没有定义,就去看有没有analyzer,再没有定义,才会去使用ES预设的。 10. index 通过index属性指定是否索引。 默认为index=true,即要进行索引,只有进行索引才可以从索引库搜索到。 但是也有一些内容不需要索引,比如:商品图片地址只被用来展示图片,不进行搜索图片,此时可以将index设置为false。 删除索引,重新创建映射,将pic的index设置为false,尝试根据pic去搜索,结果搜索不到数据 "pic": { "type": "text", "index":false -- 这个字段就不可以被查到了 } 11. keyword关键字字段 上边介绍的text文本字段在映射时要设置分词器,keyword字段为关键字字段,通常搜索keyword是按照整体搜索,所以创建keyword字段的索引时是不进行分词的,比如:邮政编码、手机号码、身份证等。keyword字段通常用于过虑、排序、聚合等。 "price": { "type": "scaled_float", "scaling_factor": 100 比例因子 price*100 四首五入的去数值 },
took:本次操作花费的时间,单位为毫秒。 timed_out:请求是否超时 _shards:说明本次操作共搜索了哪些分片 hits:搜索命中的记录 hits.total : 符合条件的文档总数 hits.hits :匹配度较高的前N个文档 hits.max_score:文档匹配得分,这里为最高分 _score:每个文档都有一个匹配度得分,按照降序排列。 _source:显示了文档的原始内容。
package com.guoshuxiang.service; 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.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.support.master.AcknowledgedResponse; import org.elasticsearch.action.update.UpdateRequest; import org.elasticsearch.action.update.UpdateResponse; import org.elasticsearch.client.RequestOptions; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.xcontent.XContentType; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Service; import java.text.SimpleDateFormat; import java.util.Date; import java.util.HashMap; import java.util.Map; @Service public class EsService { @Autowired private RestHighLevelClient client; /** * index 和添加映射放 在 一起的 * * @throws Exception */ public void createIndex() throws Exception { // 创建一个index CreateIndexRequest createIndexRequest = new CreateIndexRequest("zg_love"); // 设置一个 微服务数量初始 1 备份数量 初始 0 createIndexRequest.settings(Settings.builder().put("number_of_shards", "1").put("number_of_replicas", "0")); createIndexRequest.mapping("doc", "{\n" + "\t\"properties\": {\n" + "\t\t\"name\": {\n" + "\t\t\t\"type\": \"text\",\n" + "\t\t\t\"analyzer\": \"ik_max_word\",\n" + "\t\t\t\"search_analyzer\": \"ik_smart\"\n" + "\t\t},\n" + "\t\t\"description\": {\n" + "\t\t\t\"type\": \"text\",\n" + "\t\t\t\"analyzer\": \"ik_max_word\",\n" + "\t\t\t\"search_analyzer\": \"ik_smart\"\n" + "\t\t},\n" + "\t\t\"studymodel\": {\n" + "\t\t\t\"type\": \"keyword\"\n" + "\t\t},\n" + "\t\t\"price\": {\n" + "\t\t\t\"type\": \"float\"\n" + "\t\t},\n" + "\t\t\"timestamp\": {\n" + "\t\t\t\"type\": \"date\",\n" + "\t\t\t\"format\": \"yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis\"\n" + "\t\t}\n" + "\t}\n" + "}", XContentType.JSON); // 指定传过的条件是json的格式 CreateIndexResponse createIndexResponse = client.indices().create(createIndexRequest, RequestOptions.DEFAULT); System.out.println(createIndexResponse.isAcknowledged()); // 看看索引是否创建成功 } /** * 删除索引 * * @throws Exception */ public void deleteIndex() throws Exception { DeleteIndexRequest indexRequest = new DeleteIndexRequest("zg_love"); AcknowledgedResponse delete = client.indices().delete(indexRequest, RequestOptions.DEFAULT); System.out.println(delete.isAcknowledged()); } /** * 创建index 和 删除 index 都要用到 * XXXXIndexRequest * 直接对映射表操作的话就直接使用 * Get delete index update Request 的请求对(index)进行操作 */ /** * 添加一条数据 * @throws Exception * CreateIndexRequest IndexRequest * 前者是用来创建并配置索引的,后者是将数据与索引相关联,并且让数据可以被搜索。 */ public void addDoc() throws Exception { Map<String,Object> jsonMap = new HashMap<>(); jsonMap.put("name", "spring cloud实战"); jsonMap.put("description", "本课程主要从四个章节进行讲解: 1.微服务架构入门 2.spring cloud基础入门 3.实战Spring Boot 4.注册中心eureka。"); jsonMap.put("studymodel", "201001"); SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); jsonMap.put("timestamp", dateFormat.format(new Date())); jsonMap.put("price", 5.6f); // 添加数据的请求 index doc 1 不指定的话会自动添加一个 IndexRequest indexRequest = new IndexRequest("zg_love","doc","1"); indexRequest.source(jsonMap); // 数据源要放进去 要把条件放进去 IndexResponse indexResponse = client.index(indexRequest, RequestOptions.DEFAULT); System.out.println(indexResponse.status()); } /** * 修改一条数据 * @throws Exception */ public void update() throws Exception { UpdateRequest updateRequest = new UpdateRequest("zg_love","doc","1"); Map<String,Object> jsonMap = new HashMap<>(); jsonMap.put("name","spring love you"); updateRequest.doc(jsonMap); // 更新是doc的方法来使用的 UpdateResponse updateResponse = client.update(updateRequest, RequestOptions.DEFAULT); System.out.println(updateResponse.status()); } /** * 得到一条数据 * @throws Exception */ public void get() throws Exception{ GetRequest getRequest = new GetRequest("zg_love","doc","1"); // index 中存一条数据的就是 document -> 里面有好多 field的 字段 GetResponse documentFields = client.get(getRequest, RequestOptions.DEFAULT); Map<String, Object> sourceAsMap = documentFields.getSourceAsMap(); System.out.println(sourceAsMap); } /** * 删除一条数据 * @throws Exception */ public void delete() throws Exception{ DeleteRequest deleteRequest = new DeleteRequest("zg_love","doc","1"); DeleteResponse deleteResponse = client.delete(deleteRequest, RequestOptions.DEFAULT); System.out.println(deleteResponse.status()); } }
下面开始使用post 请求来查询数据 都是json 格式的形式来操作的
查询指定索引库指定类型下的文档。(通过使用此方法) 发送:post http://localhost:9200/xc_course/doc/_search { "query": { "match_all": {} // 换成java 代码来使用 在这里 } }
{ "from": 0, "size": 1, "query": { "match_all": {} }, "_source": ["name", "studymodel"] }
//设置分页参数 这几个参数是同级的 {} searchSourceBuilder.from((index - 1) * size); searchSourceBuilder.size(size);
{ "query": { "term": { "name": "java" //%java% } }, "_source": ["name", "studymodel"] }
//设置查询方式 (精准查询) %201002% TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201002");
{ "query": { "terms": { "price": [38.6,68.6] // 可以有多个值 } }, "_source": ["name", "studymodel"] }
// 这里有可变参数,不止一条数据 单个字段的多值查询 QueryBuilders.termsQuery("studymodel", stus); // 这里放的是数组
{ "query": { "match": { "description": { "query": "spring框架", "operator": "or", "minimum_should_match": "80%" } } } }
MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "spring开发框架");// 分词是中文和英文的状态小 , text 类型 并且设置了 ik分词器才可以的 matchQueryBuilder.operator(Operator.OR); // 指定操作是 or 多个条件满足一个就行了 matchQueryBuilder.minimumShouldMatch("80%"); // 提高精准度
{ "query": { "multi_match": { "query": "spring css", "minimum_should_match": "50%", "fields": ["name^10", "description"] } }
//设置查询方式 (分词查询) MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders .multiMatchQuery("spring框架", "name", "description"); // text field 参数 // 给field 增加 权重 multiMatchQueryBuilder.field("name", 10);
{ "query": { "bool": { "must": [{ // 还有可能是 should "multi_match": { "query": "spring框架", "minimum_should_match": "50%", "fields": ["name^10", "description"] } }, { "term": { "studymodel": "201002" } }] } } }
// 构建boolean的条件 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); //条件一 if (!StringUtils.isEmpty(keyword)) { // 多列查询 MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description"); // 设置权重 multiMatchQueryBuilder.minimumShouldMatch("50%"); // 分词反满一个就行 multiMatchQueryBuilder.operator(Operator.OR); // and 的关系 是并列下一个条件的 boolQueryBuilder.must(multiMatchQueryBuilder); } //条件二 if (!StringUtils.isEmpty(studymodel)) { // 精确查询结果 TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", studymodel); // and 构建多条件 boolQueryBuilder.must(termQueryBuilder); }
{ // 这么多要操作的filed "_source": ["name", "studymodel", "description", "price"], "query": { "bool": { "must": [{ "multi_match": { "query": "spring框架", "minimum_should_match": "50%", "fields": ["name^10", "description"] } }], "filter": [{ "term": { "studymodel": "201001" } }, { "range": { "price": { "gte": 60, "lte": 100 } } }] } } }
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("price"); // 这里是查询条件 rangeQueryBuilder.gte(min).lte(max); // 这里是最大最小的小于最大的 boolQueryBuilder.filter(rangeQueryBuilder); // 添加到过滤其中
"highlight": { // 这里和条件是一个级别的 最后都要放到 条件收集器中 "pre_tags": ["<span style=’color:red;’>"], "post_tags": ["</span>"], "fields": { "name": {}, "description": {} } }
//设置高亮对象 HighlightBuilder highlightBuilder = new HighlightBuilder(); // 开头标签 highlightBuilder.preTags("<span style='color:red;'>"); highlightBuilder.postTags("</span>"); // 后面的标签 highlightBuilder.fields().add(new HighlightBuilder.Field("name")); // 添加一个给高亮的条件 highlightBuilder.fields().add(new HighlightBuilder.Field("description")); searchSourceBuilder.highlighter(highlightBuilder); //最后将高亮并列在查询条件中
//获取高亮数据 Map<String, HighlightField> fieldMap = hit.getHighlightFields(); // 获取到键值对 HighlightField nameField = fieldMap.get("name"); //获取到关键的字 if (nameField != null) { // 不为空的 StringBuffer nameSbf = new StringBuffer(); // Text[] fragments = nameField.fragments(); // 取到那个一满足的字段 for (Text text : fragments) { nameSbf.append(text.toString()); // 循环满足的去拼接字符 } course.setName(nameSbf.toString()); // 最后添加到字段类型中去 }
"sort": [{ "studymodel": "desc" }, { "price": "asc" }]
//添加排序 searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)); // 排序调用 sort() filed的条件对象 在调用 升序和降序 searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.DESC)); searchSourceBuilder.aggregation(AggregationBuilders.terms("brandGroup").field("brand_name").size(50));
public void all() throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder sourceBuilder = new SearchSourceBuilder(); MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery(); sourceBuilder.query(matchAllQueryBuilder); searchRequest.source(sourceBuilder); SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); //一共有多少条数据 System.out.println("总的记录是" + totalHits); SearchHit[] searchHits = hits.getHits();//具体存放数据的地方 for (SearchHit hit : searchHits) { String id = hit.getId(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); System.out.println(sourceAsMap); } } /** * 获取分页的数据 分页 limit 是一个大的函数 和条件是同级关系 * * @param index 初始页码 * @param size 每页大小 * @throws Exception */ public void page(Integer index, Integer size) throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); // 构建大的条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.from((index - 1) * size); searchSourceBuilder.size(size); MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery(); searchSourceBuilder.query(matchAllQueryBuilder); // 封装的条件 searchRequest.source(searchSourceBuilder); // 最后条件放进去 SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总的条数" + totalHits); SearchHit[] hitsHits = hits.getHits(); for (SearchHit hit : hitsHits) { String id = hit.getId(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); System.out.println(sourceAsMap); } } /** * 精确查询就是这个数据必须在一起,才可以查到一条数据不然是找到不到数据的 * * @throws Exception */ public void term() throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", "spring"); searchSourceBuilder.query(termQueryBuilder); // 指定要查询的字段 searchSourceBuilder.fetchSource(new String[]{"name", "studymodel", "price"}, null); searchRequest.source(searchSourceBuilder); // 最后一定要带上条件啊不然就会查出全部的数据 SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总的数据 : " + totalHits + "条"); SearchHit[] hitsHits = hits.getHits(); for (SearchHit hit : hitsHits) { String id = hit.getId(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); System.out.println(sourceAsMap); } } /** * 单个列的精确查询 * * @throws Exception */ public void terms() throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 多条件精确查询数据 字段 具体的字 ... 可变参数 这里的数据 TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("name", "cloud"); searchSourceBuilder.query(termsQueryBuilder); searchRequest.source(searchSourceBuilder); SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总数据量:" + totalHits); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String id = hit.getId(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); System.out.println(sourceAsMap); } } /** * 分词查询数据 必须是text 类型的数据才可以的 * * @throws Exception */ public void match() throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 分子是match 来查询的 MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "spring开发入门"); matchQueryBuilder.operator(Operator.OR); // 默认就是 or的 关系 这里是分开的词有一个满足就行了 matchQueryBuilder.minimumShouldMatch("80%"); // 3 * 0.8 = 2.4 向下取整 2 至少有两个关键词才可以的 searchSourceBuilder.query(matchQueryBuilder); searchRequest.source(searchSourceBuilder); //执行请求获取响应 SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总数据量:" + totalHits); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String id = hit.getId(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); System.out.println(sourceAsMap); } } /** * 多列分词查询 * * @throws Exception */ public void mutilMatch() throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 这个词在两个关键字中来写啊 MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("实战语言", "name", "description"); multiMatchQueryBuilder.field("name", 10); // 扩大数据提高分数 优先在最前面 searchSourceBuilder.query(multiMatchQueryBuilder); searchRequest.source(searchSourceBuilder); //执行请求获取响应 SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总数据量:" + totalHits); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String id = hit.getId(); float score = hit.getScore(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); sourceAsMap.put("score", score); System.out.println(sourceAsMap); } } /** * 注意:range 和 term一次只能对一个 Field 设置范围过虑。 不可以是多个 * @param keyword 分词的关键字 * @param studymodel 精确查询的关键字 * @throws Exception */ public void bool(String keyword, String studymodel) throws Exception { SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // boolean 这是大条件 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); // 这里逻辑相反 if (!StringUtils.isEmpty(keyword)) { //多列分词查询 MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description"); multiMatchQueryBuilder.minimumShouldMatch("50%"); multiMatchQueryBuilder.operator(Operator.OR); multiMatchQueryBuilder.field("description",10); boolQueryBuilder.must(multiMatchQueryBuilder); // } // must 是全都满足条件的 上下两个条件都满足才行的 if (!StringUtils.isEmpty(studymodel)) { // 精确查询 TermsQueryBuilder termQueryBuilder = QueryBuilders.termsQuery("studymodel", studymodel); boolQueryBuilder.must(termQueryBuilder); } searchSourceBuilder.query(boolQueryBuilder); searchRequest.source(searchSourceBuilder); //执行请求获取响应 SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总数据量:" + totalHits); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String id = hit.getId(); float score = hit.getScore(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); sourceAsMap.put("id", id); sourceAsMap.put("score",score); System.out.println(sourceAsMap); } } public List<Course> filter(String keyword, String studymodel, Double min, Double max) throws Exception{ SearchRequest searchRequest = new SearchRequest("zg_love"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); // 这里是原始数据 在这个数据上开始过滤数据 if (! StringUtils.isEmpty(keyword)){ MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description"); multiMatchQueryBuilder.minimumShouldMatch("50%"); multiMatchQueryBuilder.field("description",10); boolQueryBuilder.must(multiMatchQueryBuilder); } if(!StringUtils.isEmpty(studymodel)){ TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("studymodel", studymodel); boolQueryBuilder.filter(termsQueryBuilder); } if (min != null && max != null){ RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("price"); rangeQueryBuilder.gte(min).lte(max); boolQueryBuilder.filter(rangeQueryBuilder); } // 排序这是一个方法 在这里 所以直接写在 大的条件构造器中 searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)); searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC)); HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.preTags("<span style='color:red;'>"); highlightBuilder.postTags("</span>"); // // //搜索 数据 另一种写法 // SearchRequestBuilder searchRequestBuilder = client.prepareSearch("blog2"). // setTypes("article").setQuery(QueryBuilders.termQuery("title","搜索 ")); // //高亮定义 // searchRequestBuilder.addHighlightedField("title");//对title字段进行高亮显示 // searchRequestBuilder.setHighlighterPreTags("<em>");//前置元素 // searchRequestBuilder.setHighlighterPostTags("</em>");//后置元素 // SearchResponse searchResponse = searchRequestBuilder.get(); // 这里用自己还是不行的 还要用内名对象来操作 highlightBuilder.fields().add(new HighlightBuilder.Field("name")); highlightBuilder.fields().add(new HighlightBuilder.Field("description")); searchSourceBuilder.query(boolQueryBuilder); searchSourceBuilder.highlighter(highlightBuilder); // 将高亮放进去 searchRequest.source(searchSourceBuilder); SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); // 如果要写前端的话这里的展示数据就不要写了 SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("总数据量: " + totalHits); SearchHit[] searchHits = hits.getHits(); List<Course> list = new ArrayList<>(); for (SearchHit hit : searchHits) { String id = hit.getId(); String json = hit.getSourceAsString(); // 里面的字段一一对应赋值 Course course = JSON.parseObject(json, Course.class); // 这里是满足高亮的数据 Map<String, HighlightField> highlightFields = hit.getHighlightFields(); HighlightField nameField = highlightFields.get("name"); if (nameField != null){ StringBuffer nameBuf = new StringBuffer(); // 获取到原有内容中 每个高亮显示 集中位置fragment就是高亮片段 可能不止有一处高亮 Text[] fragments = nameField.fragments(); // for (Text text : fragments) { nameBuf.append(text.toString()); } course.setName(nameBuf.toString()); } HighlightField description = highlightFields.get("description"); if (description != null){ StringBuffer dSbf = new StringBuffer(); // text 类型的数据 文本类型要转化为String 在java中使用 Text[] text = description.fragments(); for (Text t : text) { dSbf.append(t.toString()); } course.setName(dSbf.toString()); } course.setId(id); list.add(course); } return list; }