https://blog.csdn.net/qq_42383787/article/details/89476236
public void test() throws IOException {
-
-
SearchRequest searchRequest = new SearchRequest();
-
-
-
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);
-
-
-
searchSourceBuilder.sort(new FieldSortBuilder("id").order(SortOrder.ASC));
-
-
searchSourceBuilder.fetchSource(false);
-
-
-
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);
-
-
-
searchRequest.source(searchSourceBuilder);
-
searchRequest.scroll(TimeValue.timeValueMinutes(1L));
-
-
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
-
-
-
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) {
-
-
String index = hit.getIndex();
-
-
String type = hit.getType();
-
-
-
-
float score = hit.getScore();
-
-
String sourceAsString = hit.getSourceAsString();
-
-
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
-
-
String documentTitle = (String) sourceAsMap.get("title");
-
-
List<Object> users = (List<Object>) sourceAsMap.get("user");
-
-
Map<String, Object> innerObject = (Map<String, Object>)sourceAsMap.get("innerObject");
-
QueryBuilder 常用来配合 Search 查询来使用
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.....
1.matchQuery 匹配查询:
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();
-
-
-
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?*"));
-
2.matchAllQuery 查询所用
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());
-
3.termQuery等值搜索
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"));
-
-
-
-
-
-
public void test() throws IOException {
-
SearchRequest searchRequest = new SearchRequest();
-
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
-
searchSourceBuilder.query(QueryBuilders.termsQuery("name", "张三", "李四", "王五"));
-
4.matchPhraseQuery短语搜索
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"));
-
5.prefixQuery前缀搜索
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"));
-
6.disMaxQuery
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")));
-
7.boolQuery 组合查询条件
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,
-
-
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"));
-
-
-
-
-
-
-
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
-
if (StringUtils.isNotEmpty(text)) {
-
-
boolQuery.must(QueryBuilders.matchQuery("text", text));
-
-
if (StringUtils.isNotEmpty(keywords)) {
-
-
boolQuery.must(QueryBuilders.matchQuery("keywords", keywords));
-
-
if (StringUtils.isNotEmpty(topic)) {
-
-
boolQuery.must(QueryBuilders.matchQuery("topic", topic));
-
8.rangeQuery属于过滤器查询
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;
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").from(${fieldValue1}).to(${fieldValue2});
-
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").from(${fieldValue1}, false).to(${fieldValue2}, false);
-
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").gt(${fieldValue});
-
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").gte(${fieldValue});
-
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").lt(${fieldValue});
-
-
-
QueryBuilder qb1 = QueryBuilders.rangeQuery("${fieldName}").lte(${fieldValue});
-
-
-
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);
ES QueryBuilder
原文:https://www.cnblogs.com/wen-/p/13808401.html