elasticsearch Elasticsearch子字段查询

数据：

{
  "name": "John",
  "surname": "Brown",
  "email": "johnbrown@gmail.com",
  "address": [
    {
      "id": "1",
      "city": "London"
    }
  ]
}

此查询正在运行

GET db
{
  "query": {
    "bool": {
      "must": [
        {
          "query_string": {
            "query": "*Brown* OR *@gmail.com*",
            "fields": [
              "surname",
              "email",
              "address.city"
            ]
          }
        }
      ],
      "filter": [
        {
          "bool": {
            "filter": [
              {
                "regexp": {
                  "name": {
                    "value": ".*John.*"
                  }
                }
              }
            ]
          }
        }
      ]
    }
  }
}

"query_string": {
  "query": "*Brown*",
  "fields": [
    "surname",
    "email",
    "address.city"
  ]
}

但是，当我像这样更改查询字符串时，它不起作用。（不起作用的意思是返回0个结果。）

这个查询也可以运行

GET db
{
  "query": {
    "bool": {
      "must": [
        {
          "query_string": {
            "query": "*Brown* OR *@gmail.com*",
            "fields": [
              "surname",
              "email",
              "address.city"
            ]
          }
        }
      ],
      "filter": [
        {
          "bool": {
            "filter": [
              {
                "regexp": {
                  "name": {
                    "value": ".*John.*"
                  }
                }
              }
            ]
          }
        }
      ]
    }
  }
}

"query_string": {
  "query": "*Brown*",
  "fields": [
    "surname",
    "email",
    "address.city"
  ]
}

---

据我所知，它无法在

address.city

中找到值。但是为什么呢？

根据下面的评论，OP创建了

地址

为

嵌套

类型的索引

添加带有索引映射、搜索查询和搜索结果的工作示例

索引映射：

{
  "mappings": {
    "properties": {
      "address": {
        "type": "nested"
      }
    }
  }
}

    {
  "query": {
    "bool": {
      "should": [
        {
          "query_string": {
            "query": "*London*",
            "fields": [
              "surname",
              "email"
            ]
          }
        },
        {
          "nested": {
            "path": "address",
            "query": {
              "query_string": {
                "query": "*London*",
                "fields": [
                  "address.city"
                ]
              }
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  }
}

"hits": [
      {
        "_index": "64908538",
        "_type": "_doc",
        "_id": "1",
        "_score": 1.0,
        "_source": {
          "name": "John",
          "surname": "Brown",
          "email": "johnbrown@gmail.com",
          "address": [
            {
              "id": "1",
              "city": "London"
            }
          ]
        }
      }
    ]

搜索查询：

{
  "mappings": {
    "properties": {
      "address": {
        "type": "nested"
      }
    }
  }
}

    {
  "query": {
    "bool": {
      "should": [
        {
          "query_string": {
            "query": "*London*",
            "fields": [
              "surname",
              "email"
            ]
          }
        },
        {
          "nested": {
            "path": "address",
            "query": {
              "query_string": {
                "query": "*London*",
                "fields": [
                  "address.city"
                ]
              }
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  }
}

"hits": [
      {
        "_index": "64908538",
        "_type": "_doc",
        "_id": "1",
        "_score": 1.0,
        "_source": {
          "name": "John",
          "surname": "Brown",
          "email": "johnbrown@gmail.com",
          "address": [
            {
              "id": "1",
              "city": "London"
            }
          ]
        }
      }
    ]

搜索结果：

{
  "mappings": {
    "properties": {
      "address": {
        "type": "nested"
      }
    }
  }
}

    {
  "query": {
    "bool": {
      "should": [
        {
          "query_string": {
            "query": "*London*",
            "fields": [
              "surname",
              "email"
            ]
          }
        },
        {
          "nested": {
            "path": "address",
            "query": {
              "query_string": {
                "query": "*London*",
                "fields": [
                  "address.city"
                ]
              }
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  }
}

"hits": [
      {
        "_index": "64908538",
        "_type": "_doc",
        "_id": "1",
        "_score": 1.0,
        "_source": {
          "name": "John",
          "surname": "Brown",
          "email": "johnbrown@gmail.com",
          "address": [
            {
              "id": "1",
              "city": "London"
            }
          ]
        }
      }
    ]

---

我应该为“地址”数据建立索引吗？你做过这样的交易吗@Bhavya@MuhammetCanTONBUL在为文档编制索引之前是否创建了索引映射？是的，它是嵌套索引的。我的索引：

“地址”：{“类型”：“嵌套”，“属性”：{

，kibana电子商务示例索引：

“产品”：{“属性”：{

。这里的类型

嵌套
错误吗@Bhavya@MuhammetCanTONBUL请查看我的更新答案，并让我知道这是否解决了您的问题？如果
地址
为
嵌套
类型，则您需要使用嵌套查询