bucket 术语聚合 Elasticsearch

Question

elasticsearch版本

{
  "name" : "abc-Inspiron-5521",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "2vLvphpURJOtfAZSGDDX5w",
  "version" : {
    "number" : "7.10.2",
    "build_flavor" : "default",
    "build_type" : "deb",
    "build_hash" : "747e1cc71def077253878a59143c1f785afa92b9",
    "build_date" : "2021-01-13T00:42:12.435326Z",
    "build_snapshot" : false,
    "lucene_version" : "8.7.0",
    "minimum_wire_compatibility_version" : "6.8.0",
    "minimum_index_compatibility_version" : "6.0.0-beta1"
  },
  "tagline" : "You Know, for Search"
}

文档映射

"user_data" : {
    "aliases" : { },
    "mappings" : {
      "properties" : {
         "experience" : {
          "properties" : {
            "brand" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "brand_segment" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "company" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "duration" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "property_type" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "real_estate_type" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        }
      }
    }

文档结构正确，括号不符请相应修改。

文件样本

{
        "_index" : "user_data",
        "_type" : "_doc",
        "_id" : "dONuEXgBU9vYaZRqY8Jo",
        "_score" : 1.0,
        "_source" : {
          "experience" : [
            {
              "brand" : "Hilton",
              "company" : "Hilton LLC",
              "brand_segment" : "Luxury",
              "property_type" : "All-Inclusive",
              "duration" : "2 years",
              "real_estate_type" : "Institutional"
            },
            {
              "brand" : "Mantis",
              "company" : "Accor LLC",
              "brand_segment" : "Upper-Upscale",
              "property_type" : "Condo",
              "duration" : "2 years",
              "real_estate_type" : "Family Office"
            },
            {
              "brand" : "Marriott",
              "company" : "Marriott LLC",
              "brand_segment" : "Independent",
              "property_type" : "Convention",
              "duration" : "2 years",
              "real_estate_type" : "Family Office"
            }
          ]
        }
}

我在 brand_segment

上的术语聚合查询

GET user_data/_search
{
  "aggs": {
    
      "experience": {
        "terms": { "field": "experience.brand_segment" }
      }
    }
}

现在我在进行术语聚合时遇到了两个问题

在 'brand_segment' 上执行术语聚合时，值 'Upper-Upscale' 应该被视为单个单位并根据其进行计数，但目前我将其作为:
第二个问题是，如果我想计算 brand_segment 值是 'Luxury' 或任何值的次数，但目前从上面的查询中我正在计算文档数量Luxury 出现的位置，而不是 Luxury 在所有文档中出现的次数。（截至目前，对于 1 个文档，多次出现被计为一次）。

错误结果

"aggregations" : {
    "experience" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "independent",
          "doc_count" : 15
        },
        {
          "key" : "luxury",
          "doc_count" : 15
        },
        {
          "key" : "upper",
          "doc_count" : 14
        },
        {
          "key" : "upscale",
          "doc_count" : 14
        }
      ]
    }
  }

期望的输出应该有 Upper-Upscale 作为一个值。我已经获取了多个示例文档，因此得到了这个结果。

请随意使用此作为创建索引的示例文档

{
  "id": 1,
  "name": "abcs",
  "source": "csv_status",
  "profile_complition": "70%",
  "creation_date": "2020-04-02",
  "current_position": [
    {
      "position": "Financial Reporting",
      "position_category": "Finance",
      "position_level": 2
    }
  ],
  "seeking_position": [
    {
      "position": "Financial Planning and Analysis",
      "position_category": "Finance",
      "position_level": 3
    }
  ],
  "last_updation_date": "2021-02-02",
  "experience": [
    {
      "brand": "Hilton",
      "company": "Hilton LLC",
      "brand_segment": "Luxury",
      "property_type": "All-Inclusive",
      "duration": "2 years",
      "real_estate_type": "Institutional"
    },
    {
      "brand": "Accor",
      "company": "Accor LLC",
      "brand_segment": "Luxury",
      "property_type": "Condo",
      "duration": "2 years",
      "real_estate_type": "Family Office"
    },
    {
      "brand": "Marriott",
      "company": "Marriott LLC",
      "brand_segment": "Independent",
      "property_type": "Convention",
      "duration": "2 years",
      "real_estate_type": "Family Office"
    }
  ]
}

brand_segment 中的其他事件 = ['Economy'、'Upscale'、'Midscale'、'Upper-Upscale'、'Luxury'、'Independent' , 'Extended Stay']

PS：所有 brand_segment 都希望被视为单个实体（'Upper-Upscale' 不希望 'Upper'、'Upscale'。与 'Extended Stay')

如果需要进一步说明，请告诉我。

Answer 1

对于第一期，您需要在 keyword 子字段上进行聚合：

GET user_data/_search
{
  "aggs": {
    
      "experience": {
        "terms": { "field": "experience.brand_segment.keyword" }
      }
    }
}

要解决第二个问题，您需要将 experience 字段设置为 nested，这意味着您的映射需要如下所示：

"user_data" : {
    "aliases" : { },
    "mappings" : {
      "properties" : {
         "experience" : {
          "type": "nested",                 <--- add this
          "properties" : {
            "brand" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },

bucket 术语聚合 Elasticsearch

bucket Terms aggregation Elasticsearch

elasticsearch

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elasticsearch-aggregation