Question

聚合中PARTY_ID的计数应相同。在一种情况下它是3000而另一种情况它是所有值的总和（2675 + 244 + 41 + 6 + 2 = 2950），它们不相等。可能是什么原因？

GET /test/data/_search
{
   "size": 0,
   "aggs": {
      "ASSET_CLASS": {
         "terms": {
            "field": "ASSET_CLASS_WORST"
         },
         "aggs": {
            "ASSET_CLASS": {
               "cardinality": {
                  "field": "PARTY_ID"
               }
            }
         }
      },
      "Total count": {
         "cardinality": {
            "field": "PARTY_ID"
         }
      }
   }
}

结果：

{
   "took": 9,
   "timed_out": false,
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "hits": {
      "total": 51891,
      "max_score": 0,
      "hits": []
   },
   "aggregations": {
      "Total count": {
         "value": 3000
      },
      "ASSET_CLASS": {
         "doc_count_error_upper_bound": 0,
         "sum_other_doc_count": 0,
         "buckets": [
            {
               "key": "NPA",
               "doc_count": 49252,
               "ASSET_CLASS": {
                  "value": 2675
               }
            },
            {
               "key": "RESTRUCTURED",
               "doc_count": 2275,
               "ASSET_CLASS": {
                  "value": 244
               }
            },
            {
               "key": "SMA2",
               "doc_count": 308,
               "ASSET_CLASS": {
                  "value": 41
               }
            },
            {
               "key": "SMA1",
               "doc_count": 42,
               "ASSET_CLASS": {
                  "value": 6
               }
            },
            {
               "key": "SMA0",
               "doc_count": 14,
               "ASSET_CLASS": {
                  "value": 2
               }
            }
         ]
      }
   }
}

Answer 1

documentation for cardinality aggregation的第一行是：

计算近似值的单值指标汇总不同价值的数量。

（强调我的）

3000分中的10分误差远低于1％，所以这只是预料之中。

基数聚合使用enhanced版本的HyperLogLog演算，其中包含常量内存复杂度和O（N）时间复杂度等有趣特性。

如果您需要更精确的结果，请尝试更高的precision_threshold参数设置。

GET /test/data/_search
{
   "size": 0,
   "aggs": {
      "ASSET_CLASS": {
         "terms": {
            "field": "ASSET_CLASS_WORST"
         },
         "aggs": {
            "ASSET_CLASS": {
               "cardinality": {
                  "field": "PARTY_ID",
                  "precision_threshold": 10000
               }
            }
         }
      },
      "Total count": {
         "cardinality": {
            "field": "PARTY_ID",
            "precision_threshold": 10000
         }
      }
   }
}

Elasticsearch Cardinality Aggregation导致错误结果

1 个答案: