ElasticSearch 聚合 - 小写或不小写

Question

请注意以下情况：

定义映射

PUT /my_index
{
  "mappings": {
    "my_type": {
      "properties": {
        "city": {
          "type": "string",
          "fields": {
            "raw": { 
              "type":  "string",
              "index": "not_analyzed"
            }
          }
        }
      }
    }
  }
}

添加数据

PUT /my_index/my_type/1
{
  "city": "New York"
}

PUT /my_index/my_type/2
{
  "city": "York"
}

PUT /my_index/my_type/3
{
  "city": "york"
}

查询构面

GET /my_index/_search
{
  "size": 0, 
  "aggs": {
    "Cities": {
      "terms": {
        "field": "city.raw" 
      }
    }
  }
}

结果

{
...
  "aggregations": {
    "Cities": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "New York",
          "doc_count": 1
        },
        {
          "key": "York",
          "doc_count": 1
        },
        {
          "key": "york",
          "doc_count": 1
        }
      ]
    }
  }
}

两难境地

我想要两件事：

1. “York”和“york”应该组合起来，而不是每个 1 次命中的 3 个存储桶，我会使用 2 个存储桶，一个用于“New York (1)”，一个用于“York (2)”
2. 必须保留城市的大小写 - 我不希望构面值全部小写

梦想结果

{
    ...
      "aggregations": {
        "Cities": {
          "doc_count_error_upper_bound": 0,
          "sum_other_doc_count": 0,
          "buckets": [
            {
              "key": "New York",
              "doc_count": 1
            },
            {
              "key": "York",
              "doc_count": 2
            }
          ]
        }
      }
    }

Answer 1

这会使您的客户端代码稍微复杂一些，但您总是可以这样做。

使用仅小写的附加子字段设置索引（不拆分空白）：

PUT /my_index
{
   "settings": {
      "analysis": {
         "analyzer": {
            "lowercase_analyzer": {
               "type": "custom",
               "tokenizer": "keyword",
               "filter": [
                  "lowercase"
               ]
            }
         }
      }
   },
   "mappings": {
      "my_type": {
         "properties": {
            "city": {
               "type": "string",
               "fields": {
                  "lowercase": {
                     "type": "string",
                     "analyzer": "lowercase_analyzer"
                  },
                  "raw": {
                     "type": "string",
                     "index": "not_analyzed"
                  }
               }
            }
         }
      }
   }
}

PUT /my_index/my_type/_bulk
{"index":{"_id":1}}
{"city":"New York"}
{"index":{"_id":2}}
{"city":"York"}
{"index":{"_id":3}}
{"city":"york"}

然后使用像这样的两级聚合，其中第二个按字母升序排列（因此大写术语将排在第一位）并且只返回每个小写术语的顶部原始术语：

GET /my_index/_search
{
   "size": 0,
   "aggs": {
      "city_lowercase": {
         "terms": {
            "field": "city.lowercase"
         },
         "aggs": {
            "city_terms": {
               "terms": {
                  "field": "city.raw",
                  "order" : { "_term" : "asc" },
                  "size": 1
               }
            }
         }
      }
   }
}

返回：

{
   "took": 5,
   "timed_out": false,
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "hits": {
      "total": 3,
      "max_score": 0,
      "hits": []
   },
   "aggregations": {
      "city_lowercase": {
         "doc_count_error_upper_bound": 0,
         "sum_other_doc_count": 0,
         "buckets": [
            {
               "key": "york",
               "doc_count": 2,
               "city_terms": {
                  "doc_count_error_upper_bound": 0,
                  "sum_other_doc_count": 1,
                  "buckets": [
                     {
                        "key": "York",
                        "doc_count": 1
                     }
                  ]
               }
            },
            {
               "key": "new york",
               "doc_count": 1,
               "city_terms": {
                  "doc_count_error_upper_bound": 0,
                  "sum_other_doc_count": 0,
                  "buckets": [
                     {
                        "key": "New York",
                        "doc_count": 1
                     }
                  ]
               }
            }
         ]
      }
   }
}

这是我使用的代码（还有一些文档示例）：

http://sense.qbox.io/gist/f3781d58fbaadcc1585c30ebb087108d2752dfff