Elasticsearch-查询（二）match 与 match_phrase 查询

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在Elasticsearch查询中， 经常用到 match 与 match_phrase 查询， 下面我们说下两个查询方式的用法
在我们的索引用，有一个test， 里面存储了部分学生信息， 下面我们用关键字“He is”进行检索

POST /test/_doc/_search

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{
  "query": {
    "match": {
      "description": "He is"
    }
  }

执行查询，得到结果如下， 得到4条数据：

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{
   "took": 3,
   "timed_out": false,
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "hits": {
      "total": 4,
      "max_score": 0.2169777,
      "hits": [
         {
            "_index": "test",
            "_type": "student",
            "_id": "2",
            "_score": 0.2169777,
            "_source": {
               "name": "februus",
               "sex": "male",
               "age": 24,
               "description": "He is passionate.",
               "interests": "reading, programing"
            }
         },
         {
            "_index": "test",
            "_type": "student",
            "_id": "1",
            "_score": 0.16273327,
            "_source": {
               "name": "leotse",
               "sex": "male",
               "age": 25,
               "description": "He is a big data engineer.",
               "interests": "reading, swiming, hiking"
            }
         },
         {
            "_index": "test",
            "_type": "student",
            "_id": "4",
            "_score": 0.01989093,
            "_source": {
               "name": "pascal",
               "sex": "male",
               "age": 25,
               "description": "He works very hard because he wanna go to Canada.",
               "interests": "programing, reading"
            }
         },
         {
            "_index": "test",
            "_type": "student",
            "_id": "3",
            "_score": 0.016878016,
            "_source": {
               "name": "yolovon",
               "sex": "female",
               "age": 24,
               "description": "She is so charming and beautiful.",
               "interests": "reading, shopping"
            }
         }
      ]
   }
}

实用match_phrase 进行检索：
POST /test/_doc/_search

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{
  "query": {
    "match_phrase": {
      "description": "He is"
    }
  }
}

得到如下2条结果：

[C#] 纯文本查看 复制代码

{
   "took": 3,
   "timed_out": false,
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "hits": {
      "total": 2,
      "max_score": 0.30685282,
      "hits": [
         {
            "_index": "test",
            "_type": "student",
            "_id": "2",
            "_score": 0.30685282,
            "_source": {
               "name": "februus",
               "sex": "male",
               "age": 24,
               "description": "He is passionate.",
               "interests": "reading, programing"
            }
         },
         {
            "_index": "test",
            "_type": "student",
            "_id": "1",
            "_score": 0.23013961,
            "_source": {
               "name": "leotse",
               "sex": "male",
               "age": 25,
               "description": "He is a big data engineer.",
               "interests": "reading, swiming, hiking"
            }
         }
      ]
   }
}

通过上面的查询条件， 可以清晰的看到， 两则得到的数据结果是不一样的， 分析得到：
1. 对于match的结果，我们可以可以看到，结果的Document中description这个field可以包含“He is”，“He”或者“is”；
2. match_phrased的结果中的description字段，必须包含“He is”这一个词组；

通过上面分析就可以看到， match查询，会将词进行拆分， 只要包含相关Document， 都会出现在最终的结果集中

那么，如果我们不想将我们的查询条件拆分，应该怎么办呢？这时候我们就可以使用match_phrase：

match_phrase是短语搜索，亦即它会将给定的短语（phrase）当成一个完整的查询条件。当使用match_phrase进行搜索的时候，你的结果集中，所有的Document都必须包含你指定的查询词组，在这里是“He is”。这看起来有点像关系型数据库的like查询操作。