public void test() throws IOException { # 创建一个Search 对象 SearchRequest searchRequest = new SearchRequest(); # 创建一个Builder 对象 对条件进行封装 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); # 查询条件: 字段名为text 内容含有19的数据 searchSourceBuilder.query(QueryBuilders.matchQuery("text", "19")); # 查询条件: 在上面条件的基础上 加上字段 jiage 内容含有329的数据 searchSourceBuilder.query(QueryBuilders.matchQuery("jiage", "329")); # 从搜索结果中取第0条开始的10条数据,数据量最多不要超过10000 会报错,有解决方案百度 searchSourceBuilder.from(0); searchSourceBuilder.size(10); # 排序根据字段id 按照正序排列 searchSourceBuilder.sort(new FieldSortBuilder("id").order(SortOrder.ASC)); searchSourceBuilder.fetchSource(false); # 参数,用于是否需要过滤 String[] includeFields = new String[]{"id", "dizhi","text","jiage"}; # 第1个参数是 需要显示的字段,第2个参数是需要过滤的字段 searchSourceBuilder.fetchSource(includeFields, null); # 进行构建 searchRequest.source(searchSourceBuilder); searchRequest.scroll(TimeValue.timeValueMinutes(1L)); SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); # 获取数据 数据可以是多种类型的 SearchHits hits = searchResponse.getHits(); SearchHit[] hits1 = hits.getHits(); List list = new ArrayList(); for (SearchHit hit : hits1) { list.add(hit.getSourceAsString()); } System.out.println(list); } } SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { // 结果的Index String index = hit.getIndex(); // 结果的type String type = hit.getType(); // 结果的ID String id = hit.getId(); // 结果的评分 float score = hit.getScore(); // 查询的结果 JSON字符串形式 String sourceAsString = hit.getSourceAsString(); // 查询的结果 Map的形式 Map<String, Object> sourceAsMap = hit.getSourceAsMap(); // Document的title String documentTitle = (String) sourceAsMap.get("title"); // 结果中的某个List List<Object> users = (List<Object>) sourceAsMap.get("user"); // 结果中的某个Map Map<String, Object> innerObject = (Map<String, Object>)sourceAsMap.get("innerObject"); }
boolQuery() 布尔查询,可以用来组合多个查询条件
fuzzyQuery() 相似度查询
matchAllQuery() 查询所有数据
regexpQuery() 正则表达式查询
termQuery() 词条查询
wildcardQuery() 模糊查询
等等.....
matchQuery可以简单理解为mysql中的like,但是我不知道我这么理解对不对,因为在elasticsearch中使用matchQuery查询时,他会对查询的field进行分词,打个比方,我们搜索"联想笔记本电脑",他可能会将他拆分为:“联想”,“电脑”,“联想电脑”,那么如果一个filed中包括 联想 两个字就可以被搜出来。当然我们进行查询的这个field的mapping必须是text类型。(如果是中文分词的话,还需要配置中文分词器),他的查询语句和上边基本相似
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); # matchQuery 匹配查询 searchSourceBuilder.query(QueryBuilders.matchQuery("text", "19")); # multiMatchQuery(Object text, String... fieldNames) 多个字段匹配某一个值 # 搜索name中或interest中包含有music的文档 (必须与music一致) public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.multiMatchQuery("music", "name", "interest")); } # wildcardQuery()模糊查询,?匹配单个字符,*匹配多个字符 # 搜索名字中含有jack文档 (name中只要包含jack即可) public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.wildcardQuery("name","*jack?*")); }
查询指定index和type中的所用记录,相当于sql:select * from sales
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.matchAllQuery()); }
我们在数据库中进行查询的时候,sql:select sales from tvs where brand = ‘小米’,那么在elasticsearch中的javaapi怎么写呢?这里我们用到一个termQuery,他相当于sql语句中的“=”,使用这个搜索一般是对索引中keyword的mapping进行等值搜索 term query 属于过滤器查询,可以处理数字(numbers)、布尔值(Booleans)、日期(dates)以及文本(text)。
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.termQuery("name", "张三")); } # terms 是多值判断 public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.termsQuery("name", "张三", "李四", "王五")); }
理解: 你会发现,使用“小别克老”没有查询出任何结果,而使用“小别克听”则查询出了我们需要的结果,这便matchPhraseQuery和matchQuery等的区别,在使用matchQuery等时,即使你传入的是“小别克老”,在执行查询时,“小别克老”会被分词器分词,例如paoding解析成“小别/别克/老”,而使用matchPhraseQuery时,“小别克老”并不会被分词器分词,而是直接以一个短语的形式查询,而如果你在创建索引所使用的field的value中没有这么一个短语(顺序无差,且连接在一起),那么将查询不出任何结果。
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.matchPhraseQuery("name", "张三")); }
如我我们需要查询的title中有“大话西游电影”,“大话西游小说”,使用prefixQuery查询“大话西游”,那么那两条数据就会出来
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.prefixQuery("title", "大话西游")); }
disMaxQuery适用于多个field的进行搜索,我们在多个field搜索时候,可能会遇到多个field匹配到了更多的词会在前面,而一个field匹配了更多的词就会排名靠后。disMax就是解决这个问题,dismax使搜索到的结果,应该是某一个field中匹配到了尽可能多的关键词,被排在前面;而不是尽可能多的field匹配到了少数的关键词,排在了前面
public void test() throws IOException { SearchRequest searchRequest = new SearchRequest(); SearchSourceBuilder searchSourceBuilder = newSearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.disMaxQuery().add(QueryBuilders.matchQuery("name", "张三"))); }
boolQuery用来将搜索的条件进行组合,即将多个组合条件组合在一起,常用的几种组合方式有must、should、mustNot,我们拿下面对应的sql语句举例子
# sql:select * from sales where brand = ‘小米‘ and color=‘红色‘,通过bool将两个查询条件组合, # must相当于sql中的= 必须匹配的意思 BoolQueryBuilder boolQuery = QueryBuilders.boolQuery(); boolQuery.must(QueryBuilders.termQuery("brand", "小米")) .must(QueryBuilders.termQuery("color", "红色")); # sql:select * from sales where brand = ‘小米‘ or color=‘红色‘;使用should相当于sql语句中的or BoolQueryBuilder boolQuery2 = QueryBuilders.boolQuery(); boolQuery2.should(QueryBuilders.termQuery("brand", "小米")) .should(QueryBuilders.termQuery("color", "红色")); # sql:select * from sales where brand = ‘小米‘ and color != ‘红色‘ mustNot相当于!= 必须不匹配 BoolQueryBuilder boolQuery3 = QueryBuilders.boolQuery(); boolQuery2.must(QueryBuilders.termQuery("brand", "小米")) .mustNot(QueryBuilders.termQuery("color", "红色")); # sql:select * from sales where (brand = ‘小米‘ or color = ‘红色‘) and brand != ‘长虹‘ BoolQueryBuilder boolQuery4 = QueryBuilders.boolQuery(); BoolQueryBuilder boolQuery5 = QueryBuilders.boolQuery(); boolQuery5.should(QueryBuilders.termQuery("brand", "小米")) .should(QueryBuilders.termQuery("color", "红色")); boolQuery4.must(boolQuery5) .mustNot(QueryBuilders.termQuery("brand", "长虹")); //设置查询条件 BoolQueryBuilder boolQuery = QueryBuilders.boolQuery(); if (StringUtils.isNotEmpty(text)) { //查询条件:字段名为text,内容含有text的数据 boolQuery.must(QueryBuilders.matchQuery("text", text)); } if (StringUtils.isNotEmpty(keywords)) { //查询条件:字段名为keywords,内容含有keywords的数据 boolQuery.must(QueryBuilders.matchQuery("keywords", keywords)); } if (StringUtils.isNotEmpty(topic)) { //查询条件:字段名为topic,内容含有topic的数据 boolQuery.must(QueryBuilders.matchQuery("topic", topic)); }
是范围查询,有时候,范围查询比精确值查询更有用,比如我想知道价格在20到40之间的商品;
range query可以处理数字(numbers)、日期(dates)以及字符串,不过字符串还是不要用范围查询的好,效率会很低;
对数字取范围没啥好说的, 就大于、大于等于、小于、小于等于四个符号加数字就可以;
# 闭区间查询 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").from(${fieldValue1}).to(${fieldValue2}); # 开区间查询 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").from(${fieldValue1}, false).to(${fieldValue2}, false); # 大于 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").gt(${fieldValue}); #大于等于 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").gte(${fieldValue}); # 小于 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").lt(${fieldValue}); # 小于等于 QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").lte(${fieldValue}); # 多条件案例 QueryBuilder qb1 = QueryBuilders.moreLikeThisQuery(new String[]{"${fieldName1}"}, new String[]{"${fieldValue1}"}, null); QueryBuilder qb2 = QueryBuilders.rangeQuery("${fieldName2}").gt("${fieldValue2}"); QueryBuilder qb3 = QueryBuilders.boolQuery().must(qb1).must(qb2);
原文:https://www.cnblogs.com/dispark/p/14048915.html