Question

无论使用什么其他参数（terms，term等），我都希望查询仅基于匹配进行汇总。更具体地说，我在一家网上商店使用多个滤镜（颜色，大小等）。如果我检查某个字段，例如color：red，则不再合并其他颜色。我正在使用的解决方案是进行2个分离的查询（一个用于应用过滤器的搜索，另一个用于聚合。任何想法如何将2个分离的查询组合在一起？

Answer 1

您可以利用post_filter的优势，该优势将不适用于您的聚合，而只会过滤要返回的hits。例如：

创建商店

PUT online_shop
{
  "mappings": {
    "properties": {
      "color": {
        "type": "keyword"
      },
      "size": {
        "type": "integer"
      },
      "name": {
        "type": "text",
        "fields": {
          "keyword": {
            "type": "keyword"
          }
        }
      }
    }
  }
}

用一些产品填充它

POST online_shop/_doc
{"color":"red","size":35,"name":"Louboutin High heels abc"}

POST online_shop/_doc
{"color":"black","size":34,"name":"Louboutin Boots abc"}

POST online_shop/_doc
{"color":"yellow","size":36,"name":"XYZ abc"}

将共享查询应用于hits和aggregations，然后使用post_filter来对匹配进行以下过滤：

GET online_shop/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "name": "abc"
          }
        }
      ]
    }
  },
  "aggs": {
    "by_color": {
      "terms": {
        "field": "color"
      }
    },
    "by_size": {
      "terms": {
        "field": "size"
      }
    }
  },
  "post_filter": {
    "bool": {
      "must": [
        {
          "term": {
            "color": {
              "value": "red"
            }
          }
        }
      ]
    }
  }
}

预期结果

{
  ...
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.11750763,
    "hits" : [
      {
        "_index" : "online_shop",
        "_type" : "_doc",
        "_id" : "cehma3IBG_KW3EFn1QYa",
        "_score" : 0.11750763,
        "_source" : {
          "color" : "red",
          "size" : 35,
          "name" : "Louboutin High heels abc"
        }
      }
    ]
  },
  "aggregations" : {
    "by_color" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "black",
          "doc_count" : 1
        },
        {
          "key" : "red",
          "doc_count" : 1
        },
        {
          "key" : "yellow",
          "doc_count" : 1
        }
      ]
    },
    "by_size" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : 34,
          "doc_count" : 1
        },
        {
          "key" : 35,
          "doc_count" : 1
        },
        {
          "key" : 36,
          "doc_count" : 1
        }
      ]
    }
  }
}

在同一查询中对不同搜索进行Elasticsearch聚合

1 个答案: