Java High Level REST Client

ES java api.jpg

基本查询

请求

  1. GET /person/_search
  2. {
  3.  "query": {
  4.   "term": {
  5.    "name.keyword": {
  6.     "value": "张无忌",
  7.     "boost": 1.0
  8.    }
  9.   }
  10.  }
  11. }

响应

  1. {
  2.   "took" : 0,
  3.   "timed_out" : false,
  4.   "_shards" : { // 分片信息
  5.     "total" : 1, // 总计分片数
  6.     "successful" : 1, // 查询成功的分片数
  7.     "skipped" : 0, // 跳过查询的分片数
  8.     "failed" : 0  // 查询失败的分片数
  9.   },
  10.   "hits" : { // 命中结果
  11.     "total" : {
  12.       "value" : 1, // 数量
  13.       "relation" : "eq"  // 关系：等于
  14.     },
  15.     "max_score" : 2.8526313,  // 最高分数
  16.     "hits" : [
  17.       {
  18.         "_index" : "person", // 索引
  19.         "_type" : "_doc", // 类型
  20.         "_id" : "1",
  21.         "_score" : 2.8526313,
  22.         "_source" : {
  23.           "address" : "光明顶",
  24.           "modifyTime" : "2021-06-29 16:48:56",
  25.           "createTime" : "2021-05-14 16:50:33",
  26.           "sect" : "明教",
  27.           "sex" : "男",
  28.           "skill" : "九阳神功",
  29.           "name" : "张无忌",
  30.           "id" : 1,
  31.           "power" : 99,
  32.           "age" : 18
  33.         }
  34.       }
  35.     ]
  36.   }
  37. }

Term查询

基本

  1. /**
  2.  * term精确查询
  3.  *
  4.  * @throws IOException
  5.  */
  7. @Autowired
  8. private RestHighLevelClient client;
  10. @Test
  11. public void queryTerm() throws IOException {
  12.  // 根据索引创建查询请求
  13.     SearchRequest searchRequest = new SearchRequest("person");
  14.     SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  15.     // 构建查询语句
  16.     searchSourceBuilder.query(QueryBuilders.termQuery("name.keyword", "张无忌"));
  17.     System.out.println("searchSourceBuilder=====================" + searchSourceBuilder);
  18.     searchRequest.source(searchSourceBuilder);
  19.     SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);
  20.     System.out.println(JSONObject.toJSON(response));
  21. }

优化

  • 查询结果中会带有_score这一项，ES会根据结果匹配程度进行评分。打分是会耗费性能的，如果确认自己的查询不需要评分，就设置查询语句关闭评分
  • 可以通过Constant Score将查询转换为Filtering，避免算分，并利用缓存，提高性能 ```json

GET /person/_search { “query”: { “constant_score”: { “filter”: { “term”: { “sect.keyword”: { “value”: “张无忌”, “boost”: 1.0 } } }, “boost”: 1.0 } } }

SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 这样构造的查询条件，将不进行score计算，从而提高查询效率 searchSourceBuilder.query(QueryBuilders .constantScoreQuery(QueryBuilders .termQuery(“sect.keyword”, “明教”)));

  1. <a name="ZTfNr"></a>
  2. ### 多值查询
  3. ```json
  4. GET /person/_search
  5. {
  6.  "query": {
  7.   "terms": {
  8.    "sect.keyword": [
  9.     "明教",
  10.     "武当派"
  11.    ],
  12.    "boost": 1.0
  13.   }
  14.  }
  15. }

java实现

  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders
  4.                           .termsQuery("sect.keyword", 
  5.                                       Arrays.asList("明教", "武当派")));

范围查询

  1. GET /person/_search
  2. {
  3.     "query":{
  4.         "range":{
  5.             "age":{
  6.                 "from":10,
  7.                 "to":20,
  8.                 "include_lower":true,
  9.                 "include_upper":true,
  10.                 "boost":1
  11.             }
  12.         }
  13.     }
  14. }

Java实现

  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders.rangeQuery("age").gte(10).lte(30));

前缀查询

  1. {
  2.  "query": {
  3.   "prefix": {
  4.    "sect.keyword": {
  5.     "value": "武当",
  6.     "boost": 1.0
  7.    }
  8.   }
  9.  }
  10. }

Java实现

  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders.prefixQuery("sect.keyword","武当"));

通配符查询

  1. {
  2.  "query": {
  3.   "wildcard": {
  4.    "sect.keyword": {
  5.     "wildcard": "张*忌",
  6.     "boost": 1.0
  7.    }
  8.   }
  9.  }
  10. }

Java实现

  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders.wildcardQuery("sect.keyword","张*忌"));

复合查询

  • must：所有的语句都必须匹配，与 ‘=’ 等价。
  • must_not：所有的语句都不能匹配，与 ‘!=’ 或 not in 等价。
  • should：至少有n个语句要匹配，n由参数控制。
    1. {
    2. "query": {
    3. "bool": {
    4.  "must": [
    5.   {
    6.       "term": {
    7.     "sex": {
    8.      "value": "女",
    9.      "boost": 1.0
    10.     }
    11.    }
    12.   },
    13.   {
    14.    "term": {
    15.     "sect.keywords": {
    16.      "value": "明教",
    17.      "boost": 1.0
    18.     }
    19.    }
    20.   }
    21.  ],
    22.  "adjust_pure_negative": true,
    23.  "boost": 1.0
    24. }
    25. }
    26. }

    Java实现

    ```json 示例1: SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 构建查询语句 searchSourceBuilder.query(QueryBuilders.boolQuery()
    1.   .must(QueryBuilders.termQuery("sex", "女"))
    2.   .must(QueryBuilders.termQuery("sect.keyword", "明教"))
    ); 示例2: SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 构建查询语句 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery()
    1.   .must(QueryBuilders.termQuery("sex", "女"))
    2.   .must(QueryBuilders.rangeQuery("age").gte(30).lte(40))
    3.   .mustNot(QueryBuilders.termQuery("sect.keyword", "明教"))
    4.   .should(QueryBuilders.termQuery("address.keyword", "峨眉山"))
    5.   .should(QueryBuilders.rangeQuery("power.keyword").gte(50).lte(80))
    6.   .minimumShouldMatch(1);  // 设置should至少需要满足几个条件

// 将BoolQueryBuilder构建到SearchSourceBuilder中 searchSourceBuilder.query(boolQueryBuilder);

  1. <a name="SGjop"></a>
  2. ### Filter查询
  4. - query和filter的区别：query查询的时候，会先比较查询条件，然后计算分值，最后返回文档结果；而filter是先判断是否满足查询条件，如果不满足会缓存查询结果（记录该文档不满足结果），满足的话，就直接缓存结果，filter不会对结果进行评分，能够提高查询效率。
  5. ```json
  6. {
  7.     "query":{
  8.         "bool":{
  9.             "filter":[
  10.                 {
  11.                     "term":{
  12.                         "sex":{
  13.                             "value":"男",
  14.                             "boost":1
  15.                         }
  16.                     }
  17.                 }
  18.             ],
  19.             "adjust_pure_negative":true,
  20.             "boost":1
  21.         }
  22.     }
  23. }

Java实现

  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders.boolQuery()
  4.         .filter(QueryBuilders.termQuery("sex", "男"))
  5. );

将must、must_not置于filter下，这种方式是最常用的

  1. {
  2.  "query": {
  3.   "bool": {
  4.    "filter": [
  5.     {
  6.      "bool": {
  7.       "must": [
  8.        {
  9.         "term": {
  10.          "sect.keyword": {
  11.           "value": "明教",
  12.           "boost": 1.0
  13.          }
  14.         }
  15.        },
  16.        {
  17.         "range": {
  18.          "age": {
  19.           "from": 20,
  20.           "to": 35,
  21.           "include_lower": true,
  22.           "include_upper": true,
  23.           "boost": 1.0
  24.          }
  25.         }
  26.        }
  27.       ],
  28.       "must_not": [
  29.        {
  30.         "term": {
  31.          "sex.keyword": {
  32.           "value": "女",
  33.           "boost": 1.0
  34.          }
  35.         }
  36.        }
  37.       ],
  38.       "adjust_pure_negative": true,
  39.       "boost": 1.0
  40.      }
  41.     }
  42.    ],
  43.    "adjust_pure_negative": true,
  44.    "boost": 1.0
  45.   }
  46.  }
  47. }
  1. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  2. // 构建查询语句
  3. searchSourceBuilder.query(QueryBuilders.boolQuery()
  4.         .filter(QueryBuilders.boolQuery()
  5.                 .must(QueryBuilders.termQuery("sect.keyword", "明教"))
  6.                 .must(QueryBuilders.rangeQuery("age").gte(20).lte(35))
  7.                 .mustNot(QueryBuilders.termQuery("sex.keyword", "女")))
  8. );

聚合查询

  1. SearchRequest searchRequest = new SearchRequest("person");
  2. SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
  3. searchSourceBuilder.size(0);
  4. // 按sect分组
  5. AggregationBuilder aggBuilder = AggregationBuilders.terms("sect_count").field("sect.keyword");
  6. searchSourceBuilder.aggregation(aggBuilder);