elasticsearch 如何向elasticsearch查询添加用户定义的字段和值

目标：我想要一个添加鉴别器字段的查询，以区分模糊结果和非模糊结果

考虑这些文件：

curl -X POST "localhost:9200/_bulk" -H 'Content-Type: application/json' -d'
{
    "index": {
        "_index": "dishes",
        "_type": "dish",
        "_id": "1"
    }
}
{
    "name": "butter chicken"
}
{
    "index": {
        "_index": "dishes",
        "_type": "dish",
        "_id": "2"
    }
}
{
    "name": "chicken burger"
}

'

考虑以下查询：

curl -X POST "localhost:9200/dishes/_search?pretty" -H 'Content-Type: application/json' -d'
{
    "query": {
        "bool": {
            "should": [
                {
                    "term": {
                        "name": "burger"
                    }
                },
                {
                    "fuzzy": {
                        "name": {
                            "value": "burger"
                        }
                    }
                }
            ],
            "minimum_should_match": 1,
            "boost": 1.0
        }
    }
}
'

我可以在查询过程中创建一个带有附加标记的结果（它不在文档中），该标记可用于区分模糊结果和非模糊结果

...

"hits" : [
    {
      "_index" : "dishes",
      "_type" : "dish",
      "_id" : "2",
      "_score" : 1.3862942,
      "_source" : {
        "name" : "chicken burger"
      },

"is_fuzzy": false

    },
    {
      "_index" : "dishes",
      "_type" : "dish",
      "_id" : "1",
      "_score" : 0.46209806,
      "_source" : {
        "name" : "butter chicken"
      },

"is_fuzzy": true

    }
  ]

还有一个选择是使用

术语

过滤器，但需要稍微修改：

GET dishes/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "name": {
              "value": "burger",
              "_name": "not_fuzzy"
            }
          }
        },
        {
          "fuzzy": {
            "name": {
              "value": "burger",
              "_name": "fuzzy"
            }
          }
        }
      ],
      "minimum_should_match": 1,
      "boost": 1
    }
  }
}

屈服

[
  {
    "_index":"dishes",
    "_type":"dish",
    "_id":"2",
    "_score":1.3862944,
    "_source":{
      "name":"chicken burger"
    },
    "matched_queries":[         <---
      "fuzzy",
      "not_fuzzy"
    ]
  },
  {
    "_index":"dishes",
    "_type":"dish",
    "_id":"1",
    "_score":0.46209806,
    "_source":{
      "name":"butter chicken"
    },
    "matched_queries":[         <---
      "fuzzy"
    ]
  }
]

[
{
“_索引”：“菜品”，
“_type”：“dish”，
“_id”：“2”，
“_分数”：1.3862944，
“_来源”：{
“名称”：“鸡肉汉堡”
},
“匹配的_查询”：[还有一个选项需要使用，但您的
术语
过滤器需要稍微修改：

GET dishes/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "name": {
              "value": "burger",
              "_name": "not_fuzzy"
            }
          }
        },
        {
          "fuzzy": {
            "name": {
              "value": "burger",
              "_name": "fuzzy"
            }
          }
        }
      ],
      "minimum_should_match": 1,
      "boost": 1
    }
  }
}

屈服

[
  {
    "_index":"dishes",
    "_type":"dish",
    "_id":"2",
    "_score":1.3862944,
    "_source":{
      "name":"chicken burger"
    },
    "matched_queries":[         <---
      "fuzzy",
      "not_fuzzy"
    ]
  },
  {
    "_index":"dishes",
    "_type":"dish",
    "_id":"1",
    "_score":0.46209806,
    "_source":{
      "name":"butter chicken"
    },
    "matched_queries":[         <---
      "fuzzy"
    ]
  }
]

[
{
“_索引”：“菜品”，
“_type”：“dish”，
“_id”：“2”，
“_分数”：1.3862944，
“_来源”：{
“名称”：“鸡肉汉堡”
},
“匹配的查询”：[这不一定是你所要求的，但是你是否考虑过仅仅给精确匹配一个显著的提升，以便它们总是领先于模糊匹配？这不一定是你所要求的，但是你是否考虑过仅仅给精确匹配一个显著的提升，以便它们总是领先于模糊匹配？