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进一步过滤聚合

elasticsearch-aggregation elasticsearch

David Ambler · 技术社区 · 7 年前

{
  "_index": "products",
  "_type": "product",
  "_id": "ID-12345",
  "_score": 1,
  "_source": {
    "created_at": "2017-08-04T17:56:44.592Z",
    "updated_at": "2017-08-04T17:56:44.592Z",
    "product_information": {
      "sku": "12345",
      "name": "Product Name",
      "price": 25,
      "brand": "Brand Name",
      "url": "URL"
    },
    "product_detail": {
      "description": "Product description text here.",
      "string_facets": [
        {
          "facet_name": "Colour",
          "facet_value": "Grey"
        },
        {
          "facet_name": "Category",
          "facet_value": "Linen"
        },
        {
          "facet_name": "Category",
          "facet_value": "Throws & Blanket"
        },
        {
          "facet_name": "Keyword",
          "facet_value": "Contemporary"
        },
        {
          "facet_name": "Keyword",
          "facet_value": "Sophisticated"
        }
      ]
    }
  }
}

product_detail.string_facets product_detail.string_facets.facet_name .

这是我目前的查询,它正在返回数据,但并不像我预期的那样。首先是查询(这只是为了尝试获取颜色):

{
  "from": 0,
  "size": 12,
  "query": {
    "bool": {
      "should": [
        {
          "multi_match": {
            "query": "Rug",
            "fields": ["product_information.name", "product_detail.string_facets.facet_value"]
          }
        },
        {
          "multi_match": {
            "query": "Blue",
            "fields": ["product_information.name", "product_detail.string_facets.facet_name"]
          }
        }
      ],
      "minimum_should_match": "100%"
    }
  },
  "aggs": {
    "suggestions": {
      "filter": { "term": { "product_detail.string_facets.facet_name.keyword": "Colour" }},
      "aggs": {
        "colours": {
          "terms": {
            "field": "product_detail.string_facets.facet_value.keyword",
            "size": 10
          }
        }
      }
    }
  }
}

"aggregations": {
    "suggestions": {
      "doc_count": 21,
      "colours": {
        "doc_count_error_upper_bound": 0,
        "sum_other_doc_count": 23,
        "buckets": [
          {
            "key": "Rug",
            "doc_count": 21
          },
          {
            "key": "Blue",
            "doc_count": 18
          },
          {
            "key": "Bold",
            "doc_count": 7
          },
          {
            "key": "Modern",
            "doc_count": 6
          },
          {
            "key": "Multi-Coloured",
            "doc_count": 5
          },
          {
            "key": "Contemporary",
            "doc_count": 4
          },
          {
            "key": "Traditional",
            "doc_count": 4
          },
          {
            "key": "White",
            "doc_count": 4
          },
          {
            "key": "Luxurious",
            "doc_count": 3
          },
          {
            "key": "Minimal",
            "doc_count": 3
          }
        ]
      }
    }
  }

它给了我所有的结果 facet_name facet_type 颜色和我想象的一样。

1 回复 | 直到 7 年前

Joanna 7 年前

你没有展示地图的样子,但我想 product_detail.string_facets

{
  "product_detail.string_facets.facet_name": ["Colour", "Category", "Keyword"],
  "product_detail.string_facets.facet_value": ["Grey", "Linen", "Throws & Blanket", "Contemporary", "Sophisticated"]
}

如您所见,基于这种结构,Elasticsearch不知道如何聚合数据。

让它工作 product\u detail.string\u镶嵌面 nested .映射 string_facets 应与此类似(注 "type": "nested" ):

"string_facets": {
    "type": "nested",
    "properties": {
        "facet_name": {
            "type": "text",
            "fields": {
                "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                }
            }
        },
        "facet_value": {
            "type": "text",
            "fields": {
                "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                }
            }
        }
    }
}

{
    "created_at": "2017-08-04T17:56:44.592Z",
    "updated_at": "2017-08-04T17:56:44.592Z",
    "product_information": {
      "sku": "12345",
      "name": "Rug",
      "price": 25,
      "brand": "Brand Name",
      "url": "URL"
    },
    "product_detail": {
      "description": "Product description text here.",
      "string_facets": [
        {
          "facet_name": "Colour",
          "facet_value": "Blue"
        },
        {
          "facet_name": "Colour",
          "facet_value": "Red"
        },
        {
          "facet_name": "Category",
          "facet_value": "Throws & Blanket"
        },
        {
          "facet_name": "Keyword",
          "facet_value": "Contemporary"
        }
      ]
    }
}

现在,为了将颜色建议聚合为单独的桶,您可以尝试这个查询(我简化了 bool query

{
  "from": 0,
  "size": 12,
  "query": {
    "bool": {
      "should": [
        {
          "multi_match": {
            "query": "Rug",
            "fields": ["product_information.name", "product_detail.string_facets.facet_value"]
          }
        }
      ]
    }
  },
  "aggs": {
    "facets": {
        "nested" : {
            "path" : "product_detail.string_facets"
        },
        "aggs": {
            "suggestions": {
              "filter": { "term": { "product_detail.string_facets.facet_name.keyword": "Colour" }},
              "aggs": {
                "colours": {
                  "terms": {
                    "field": "product_detail.string_facets.facet_value.keyword",
                    "size": 10
                  }
                }
              }
            }
        }
      }
    }
}

结果:

{
    ...,
    "hits": {
    ...
    },
    "aggregations": {
        "facets": {
            "doc_count": 5,
            "suggestions": {
                "doc_count": 2,
                "colours": {
                    "doc_count_error_upper_bound": 0,
                    "sum_other_doc_count": 0,
                    "buckets": [
                        {
                            "key": "Blue",
                            "doc_count": 1
                        },
                        {
                            "key": "Red",
                            "doc_count": 1
                        }
                    ]
                }
            }
        }
    }
}