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ES-DSL搜索

时间：2023-09-23 15:23:21浏览次数：30  
标签：String searchSourceBuilder description DSL 搜索 new studymodel ES name

先准备测试数据

 

创建映射：
post：http://localhost:9200/xc_course/doc/_mapping
{
                "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"
                    }
                }
            }


初始化文档：

http://localhost:9200/xc_course/doc/1
{
"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"
}
http://localhost:9200/xc_course/doc/2
{
"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"
}
http://localhost:9200/xc_course/doc/3
{
"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"
}
测试数据

DSL是ES提出的基于JSON的搜索方法

1.查询所有文档

　　POST　http://localhost:9200/xc_course/doc/_search

　　Body中的JSON数据

query--------搜索的方式

_source------设置要显示的字段
{
    "query":{
        "match_all":{}
    },
    "_source":["name","studymodel"]
}

返回的结果集说明：　

{
    "took": 11,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": 3,
        "max_score": 1,
        "hits": [
            {
                "_index": "xc_course",
                "_type": "doc",
                "_id": "1",
                "_score": 1,
                "_source": {
                    "studymodel": "201002",
                    "name": "Bootstrap开发"
                }
            },
            {
                "_index": "xc_course",
                "_type": "doc",
                "_id": "2",
                "_score": 1,
                "_source": {
                    "studymodel": "201001",
                    "name": "java编程基础"
                }
            },
            {
                "_index": "xc_course",
                "_type": "doc",
                "_id": "3",
                "_score": 1,
                "_source": {
                    "studymodel": "201001",
                    "name": "spring开发基础"
                }
            }
        ]
    }
}
返回的搜索结果 　　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。 　　对应的JavaApi实现 　　示例： 
@SpringBootTest
@RunWith(SpringRunner.class)
public class TestSearch {
    @Autowired
    RestHighLevelClient restHighLevelClient;

    @Autowired
    RestClient restClient;

    /**
     * 搜索全部记录
     */
    @Test
    public void testSearchALl() throws IOException, ParseException {
        //创建搜索请求对象
        SearchRequest searchRequest = new SearchRequest("xc_course");
            //搜索对象指定类型
            searchRequest.types("doc");
        //创建搜索源构建对象
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            //搜索源设置搜索方式
            searchSourceBuilder.query(QueryBuilders.matchAllQuery());          //QueryBuilders.matchAllQuery()-----搜索全部
            //设置源文档字段过滤------------第一个结果集包括哪些字段，第二个结果集不包括哪些字段
            searchSourceBuilder.fetchSource(new String[]{"name","studymodel","timestamp"},new String[]{});
        //搜索请求对象设置搜索源
        searchRequest.source(searchSourceBuilder);
        //执行搜索
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
            //获取匹配的搜索结果
            SearchHits hits = searchResponse.getHits();
            //匹配到的总记录数
            long totalHits = hits.getTotalHits();
            //匹配度高的文档
            SearchHit[] searchHits = hits.getHits();

        //日期格式化对象
        DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        //遍历输出
        for (SearchHit hit:searchHits) {
            //文档主键
            String id = hit.getId();
            //源文档内容
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            //之前设置了源文档字段过滤集，所以搜索不到
            String description = (String) sourceAsMap.get("description");
            String studymodel = (String) sourceAsMap.get("studymodel");
            Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
            //打印
            System.out.println(name);
            System.out.println(description);
            System.out.println(studymodel);
            System.out.println(timestamp);
        }
    }

}
jave实现DSL搜索全部记录

2.分页查询

　　ES支持分页查询，传入两个参数：from和size

　　from-----表示起始文档的下标

　　size------查询的文档数量

    POST 　　http://localhost:9200/xc_course/doc/_search

　　Body的JSON数据

 {
     "from":0,"size":1,
    "query":{
        "match_all":{}
    },
    "_source":["name","studymodel"]
}

　　JaveClient示例：

 /**
     * 分页搜索记录
     */
    @Test
    public void testSearchPage() throws IOException, ParseException {
        //创建搜索请求对象
        SearchRequest searchRequest = new SearchRequest("xc_course");
        //搜索对象指定类型
        searchRequest.types("doc");
        //创建搜索源构建对象
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            //页码
            int page = 1;
            //每页记录数
            int size = 1;
            //计算记录起始下标
            int from = (page - 1) * size;
            //设置分页参数
            searchSourceBuilder.from(from);
            searchSourceBuilder.size(size);
        //搜索源设置搜索方式
        searchSourceBuilder.query(QueryBuilders.matchAllQuery());          //QueryBuilders.matchAllQuery()-----搜索全部
        //设置源文档字段过滤------------第一个结果集包括哪些字段，第二个结果集不包括哪些字段
        searchSourceBuilder.fetchSource(new String[]{"name","studymodel","timestamp"},new String[]{});
        //搜索请求对象设置搜索源
        searchRequest.source(searchSourceBuilder);
        //执行搜索
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        //获取匹配的搜索结果
        SearchHits hits = searchResponse.getHits();
        //匹配到的总记录数
        long totalHits = hits.getTotalHits();
        //匹配度高的文档
        SearchHit[] searchHits = hits.getHits();

        //日期格式化对象
        DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        //遍历输出
        for (SearchHit hit:searchHits) {
            //文档主键
            String id = hit.getId();
            //源文档内容
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            //之前设置了源文档字段过滤集，所以搜索不到
            String description = (String) sourceAsMap.get("description");
            String studymodel = (String) sourceAsMap.get("studymodel");
            Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
            //打印
            System.out.println(name);
            System.out.println(description);
            System.out.println(studymodel);
            System.out.println(timestamp);
        }
    }
分页搜索记录

3.TermQuery精确查询和根据ID查询

　　在搜索时会整体匹配关键字，不再将关键字分词

　POST      http://localhost:9200/xc_course/doc/_search

　　整体匹配：会将下面name里的值去整体与分词器里的词去匹配

　精确查询Body的JSON数据

 {
    "query":{
        "term":{
            "name":"spring"
        }
    },
    "_source":["name","studymodel"]
}

　根据ID查询Body的JSON数据

 {
    "query":{
        "ids":{
            "type":"doc",
            "values":["3","2","100"]
        }
    },
    "_source":["name","studymodel"]
}

　　JaveClient示例：

/**
     * 精确查询和根据ID查询
     */
    @Test
    public void testSearchTermQuery() throws IOException, ParseException {
        //创建搜索请求对象
        SearchRequest searchRequest = new SearchRequest("xc_course");
        //搜索对象指定类型
        searchRequest.types("doc");
        //创建搜索源构建对象
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        //搜索源设置搜索方式
                    //termQuery精确查询
                  //searchSourceBuilder.query(QueryBuilders.termQuery("name","spring"));          //termQuery-----精确查询
                    // searchSourceBuilder.query(QueryBuilders.termQuery("name","spring开发"));     //因为是整体精确查询，没有相匹配的值，搜不出来
                    //设置源文档字段过滤------------第一个结果集包括哪些字段，第二个结果集不包括哪些字段
                            //根据ID查询
                                //设置主键
                                String[] ids = new String[]{"1","2"};
                                searchSourceBuilder.query(QueryBuilders.termsQuery("_id",ids));          //注意：这里的QueryBuilders.termsQuery 是termsQuery
        searchSourceBuilder.fetchSource(new String[]{"name","studymodel","timestamp"},new String[]{});
        //搜索请求对象设置搜索源
        searchRequest.source(searchSourceBuilder);
        //执行搜索
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        //获取匹配的搜索结果
        SearchHits hits = searchResponse.getHits();
        //匹配到的总记录数
        long totalHits = hits.getTotalHits();
        //匹配度高的文档
        SearchHit[] searchHits = hits.getHits();

        //日期格式化对象
        DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        //遍历输出
        for (SearchHit hit:searchHits) {
            //文档主键
            String id = hit.getId();
            //源文档内容
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            //之前设置了源文档字段过滤集，所以搜索不到
            String description = (String) sourceAsMap.get("description");
            String studymodel = (String) sourceAsMap.get("studymodel");
            Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));
            //打印
            System.out.println(name);
            System.out.println(description);
            System.out.println(studymodel);
            System.out.println(timestamp);
        }
    }
精确查询和根据ID查询 
注意：根据ID查询这里的QueryBuilders.termsQuery 是termsQuery

 4.match Query---全文检索                                            match-----  n.比赛; 火柴; 敌手; 相配的人/物; 相似的东西

　POST　　http://localhost:9200/xc_course/doc/_search

　　全文检索提交的JSON数据1

 {
    "query":{
        "match":{
        "description":{
            "query":"spring开发",
            "operator":"or"
        }
    }
    }
}
query：搜索的关键字，对于英文关键字如果有多个单词则中间要用半角逗号分隔，而对于中文关键字中间可以用逗号分隔也可以不用。 operator：or 表示 只要有一个词在文档中出现则就符合条件，and表示每个词都在文档中出现则才符合条件。

　　全文检索提交的JSON数据2

 {
    "query":{
        "match":{
        "description":{
            "query":"spring开发框架",
            "minimum_should_match":"80%"
        }
    }
    }
}
spring开发框架”会被分为三个词：spring、开发、框架 设置"minimum_should_match": "80%"表示，三个词在文档的匹配占比为80%，即3*0.8=2.4，向上取整得2，表示至少有两个词在文档中要匹配成功。

 　　JavaClient示例： 

/**
     * MatchQuery
     */
    @Test
    public void MatchQuery() throws IOException {
        //搜索请求对象
        SearchRequest searchRequest = new SearchRequest("xc_course");
        //搜索对象指定类型
        searchRequest.types("doc");
        //搜索源创建对象
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            //设置搜索源搜索方式
            searchSourceBuilder.query(QueryBuilders.matchQuery("description","spring开发框架")
                                                                .minimumShouldMatch("80%"));
        //请求对象设置搜索源
        searchRequest.source(searchSourceBuilder);
        //执行搜索
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        //获取匹配的搜索结果
        SearchHits hits = searchResponse.getHits();
        //匹配的总数
        long totalHits = hits.getTotalHits();
        //匹配的搜索结果
        SearchHit[] searchHits = hits.getHits();
        //遍历输出
        for (SearchHit hit:searchHits) {
            //文档主键
            String id = hit.getId();
            //源文档内容
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            //之前设置了源文档字段过滤集，所以搜索不到
            String description = (String) sourceAsMap.get("description");
            String studymodel = (String) sourceAsMap.get("studymodel");
            //打印
            System.out.println(name);
            System.out.println(description);
            System.out.println(studymodel);
        }
    }
MatchQuery---全文检索

5.MultiQuery---多字段匹配　　　　　　Multi---复选

　　POST      http://localhost:9200/xc_course/doc/_search

JSON数据：

 {
    "query":{
        "multi_match":{
            "query":"spring开发框架",
            "minimum_should_match":"50%",
            "fields":["name^10","description"]
            }
    }
}
　　上面拿关键字 “spring css”去匹配name 和description字段 　　提升boost，通常关键字匹配上name的权重要比匹配上description的权重高，这里可以对name的权重提升 　　name^10” 表示权重提升10倍，执行上边的查询，发现name中包括spring关键字的文档排在前边。 JavaClient： 
/**
     * MultiQuery  --多字段匹配
     */
   /* MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框架",
            "name", "description")
            .minimumShouldMatch("50%");
    multiMatchQueryBuilder.field("name",10);//提升boost*/

6.布尔查询

布尔查询对应于Lucene的BooleanQuery查询，实现将多个查询组合起来。 　　POST  　　http://localhost:9200/xc_course/doc/_search JSON数据： 
{
    "_source" : [ "name", "studymodel", "description"],
    "from" : 0, "size" : 1,
    "query": {
    "bool" : {
        "must":[
                {
                "multi_match" : {
        "query" : "spring框架",
        "minimum_should_match": "50%",
        "fields": [ "name^10", "description" ]
            }
            },
                {
                    "term":{
                    "studymodel" : "201001"
                    }
                }
            ]
        }
    }
}
　　must：表示必须，多个查询条件必须都满足。（通常使用must） 　　should：表示或者，多个查询条件只要有一个满足即可。 　　must_not：表示非 JavaClient示例： 
//BoolQuery，将搜索关键字分词，拿分词去索引库搜索
    @Test
    public void testBoolQuery() throws IOException {
        //创建搜索请求对象
        SearchRequest searchRequest = new SearchRequest("xc_course");
        searchRequest.types("doc");
        //创建搜索源配置对象
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.fetchSource(new String[]{"name", "pic", "studymodel"}, new String[]{});
        //multiQuery
        String keyword = "spring开发框架";
        MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框架",
                "name", "description")
                .minimumShouldMatch("50%");
        multiMatchQueryBuilder.field("name", 10);
        //TermQuery
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201001");
        //布尔查询
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        boolQueryBuilder.must(multiMatchQueryBuilder);
        boolQueryBuilder.must(termQueryBuilder);
        //设置布尔查询对象
        searchSourceBuilder.query(boolQueryBuilder);
        searchRequest.source(searchSourceBuilder);//设置搜索源配置
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        SearchHits hits = searchResponse.getHits();
        SearchHit[] searchHits = hits.getHits();
        for (SearchHit hit : searchHits) {
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            System.out.println(sourceAsMap);
        }
    }
布尔查询

7.过滤器查询

过虑是针对搜索的结果进行过虑，过虑器主要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，所以过虑器性能比查询要高，且方便缓存，推荐尽量使用过虑器去实现查询或者过虑器和查询共同使用。 　　POST　　http://localhost:9200/xc_course/doc/_search JSON数据： 
{
    "_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}}}
        ]
        }
    }
}
　　range：范围过虑，保留大于等于60 并且小于等于100的记录。 　　term：项匹配过虑，保留studymodel等于"201001"的记录。 　　注意：range和term一次只能对一个Field设置范围过虑。 JavaClient示例： 
 //布尔查询使用过虑器
    @Test
    public void testFilter() throws IOException {
        SearchRequest searchRequest = new SearchRequest("xc_course");
        searchRequest.types("doc");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        //source源字段过虑
        searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"},
                new String[]{});
        searchRequest.source(searchSourceBuilder);
        //匹配关键字
        MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框架", "name", "description");
        //设置匹配占比
                multiMatchQueryBuilder.minimumShouldMatch("50%");
        //提升另个字段的Boost值
        multiMatchQueryBuilder.field("name",10);
        searchSourceBuilder.query(multiMatchQueryBuilder);
        //布尔查询
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        boolQueryBuilder.must(searchSourceBuilder.query());
        //过虑
        boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel", "201001"));
        boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(60).lte(100));
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        SearchHits hits = searchResponse.getHits();
        SearchHit[] searchHits = hits.getHits();
        for (SearchHit hit : searchHits) {
            String index = hit.getIndex();
            String type = hit.getType();
            String id = hit.getId();
            float score = hit.getScore();
            String sourceAsString = hit.getSourceAsString();
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            String studymodel = (String) sourceAsMap.get("studymodel");
            String description = (String) sourceAsMap.get("description");
            System.out.println(name);
            System.out.println(studymodel);
            System.out.println(description);
        }
    }
过滤器

8.排序

可以在字段上添加一个或多个排序，支持在keyword、date、float等类型上添加，text类型的字段上不允许添加排序。  POST　　http://localhost:9200/xc_course/doc/_search

JSON数据：

过虑0--10元价格范围的文档，并且对结果进行排序，先按studymodel降序，再按价格升序 
{
    "_source" : [ "name", "studymodel", "description","price"],
    "query": {
        "bool" : {
            "filter": [
        { "range": { "price": { "gte": 0 ,"lte" : 100}}}
                ]
                                }
                },
        "sort" : [
            {
            "studymodel" : "desc"
            },
            {
            "price" : "asc"
            }            
        ]
}

JavaClient示例：

/**
     * 排序
     * @throws IOException
     */
    @Test
    public void testSort() throws IOException {
        SearchRequest searchRequest = new SearchRequest("xc_course");
        searchRequest.types("doc");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    //source源字段过虑
        searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"},
                new String[]{});
        searchRequest.source(searchSourceBuilder);
    //布尔查询
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
    //过虑
        boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100));
        //排序
        searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC));   //降序 DESC
        searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC));         //升序 ESC
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        SearchHits hits = searchResponse.getHits();
        SearchHit[] searchHits = hits.getHits();
        for (SearchHit hit : searchHits) {
            String index = hit.getIndex();
            String type = hit.getType();
            String id = hit.getId();
            float score = hit.getScore();
            String sourceAsString = hit.getSourceAsString();
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
            String name = (String) sourceAsMap.get("name");
            String studymodel = (String) sourceAsMap.get("studymodel");
            String description = (String) sourceAsMap.get("description");
            System.out.println(name);
            System.out.println(studymodel);
            System.out.println(description);
        }
    }
排序

9.高亮

高亮显示可以将搜索结果一个或多个字突出显示，以便向用户展示匹配关键字的位置。 
　　POST　　 http://127.0.0.1:9200/xc_course/doc/_search  JSON数据： 
{
    "_source" : [ "name", "studymodel", "description","price"],
    "query": {
        "bool" : {
            "must":[
            {
                "multi_match" : {
                "query" : "开发框架",
                "minimum_should_match": "50%",
                "fields": [ "name^10", "description" ],
                "type":"best_fields"
                }
                }
        ],
        "filter": [
        { "range": { "price": { "gte": 0 ,"lte" : 100}}}
            ]
            }
            },
        "highlight":{
            "pre_tags": ["<tag>"],
            "post_tags": ["</tag>"],
            "fields": {
            "name": {},
            "description":{}
            }
        }
}

JavaClient示例：

/**
     * 高亮
     * @throws IOException
     */
    @Test
    public void testHighlight() throws IOException {
        SearchRequest searchRequest = new SearchRequest("xc_course");
        searchRequest.types("doc");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
//source源字段过虑
        searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"},
                new String[]{});
        searchRequest.source(searchSourceBuilder);
//匹配关键字
        MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("开发","name", "description");
        searchSourceBuilder.query(multiMatchQueryBuilder);
//布尔查询
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        boolQueryBuilder.must(searchSourceBuilder.query());
//过虑
        boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100));
//排序
        searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC));
        searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC));
//高亮设置
        HighlightBuilder highlightBuilder = new HighlightBuilder();
        highlightBuilder.preTags("<tag>");//设置前缀
        highlightBuilder.postTags("</tag>");//设置后缀
// 设置高亮字段
        highlightBuilder.fields().add(new HighlightBuilder.Field("name"));
// highlightBuilder.fields().add(new HighlightBuilder.Field("description"));
        searchSourceBuilder.highlighter(highlightBuilder);
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
        SearchHits hits = searchResponse.getHits();
        SearchHit[] searchHits = hits.getHits();
        for (SearchHit hit : searchHits) {
            Map<String, Object> sourceAsMap = hit.getSourceAsMap();
//名称
            String name = (String) sourceAsMap.get("name");
//取出高亮字段内容
            Map<String, HighlightField> highlightFields = hit.getHighlightFields();
            if(highlightFields!=null){
                HighlightField nameField = highlightFields.get("name");
                if(nameField!=null){
                    Text[] fragments = nameField.getFragments();
                    StringBuffer stringBuffer = new StringBuffer();
                    for (Text str : fragments) {
                        stringBuffer.append(str.string());
                    }
                    name = stringBuffer.toString();
                }
            }
            String index = hit.getIndex();
            String type = hit.getType();
            String id = hit.getId();
            float score = hit.getScore();
            String sourceAsString = hit.getSourceAsString();
            String studymodel = (String) sourceAsMap.get("studymodel");
            String description = (String) sourceAsMap.get("description");
            System.out.println(name);
            System.out.println(studymodel);
            System.out.println(description);
        }
    }
高亮

 

标签：String,searchSourceBuilder,description,DSL,搜索,new,studymodel,ES,name
From： https://www.cnblogs.com/lksses/p/17716635.html

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