一尘不染

Elasticsearch-聚合脚本字段

elasticsearch

我正在尝试创建一个脚本字段,该脚本字段将计算两个时间戳之间的时间差,然后avg在该脚本字段上聚合一个。

我首先尝试:

{
   "query": {
      "filtered": {
         "query": {
            "match_all": {}
         },
         "filter": {
            "and": [
               {
                  "exists": {
                     "field": "time.new_time"
                  }
               },
               {
                  "exists": {
                     "field": "time.first_alert_time"
                  }
               }
            ]
         }
      }
   },
   "script_fields": {
      "timedifference": {
         "script": "doc['time.new_time'].value - doc['time.first_alert_time'].value"
      }
   },
   "aggs": {
      "avg_timedifference": {
         "avg": {
            "field" : "timedifference"
         }
      }
   }
}

null在合计平均值下产生价值avg_timedifference

然后我尝试了:

{
   "query": {
      "filtered": {
         "query": {
            "match_all": {}
         },
         "filter": {
            "and": [
               {
                  "exists": {
                     "field": "time.new_time"
                  }
               },
               {
                  "exists": {
                     "field": "time.first_alert_time"
                  }
               }
            ]
         }
      }
   },
   "script_fields": {
      "timedifference": {
         "script": "doc['time.new_time'].value - doc['time.first_alert_time'].value"
      }
   },
   "aggs": {
      "avg_timedifference": {
         "avg": {
            "script" : "doc['timedifference'].value"
         }
      }
   }
}

生成了一条错误消息,内容为:“在映射中找不到[timedifference]的字段”


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2020-06-22

共1个答案

一尘不染

简单地将脚本移到聚合上怎么样?

{
   "query": {
      "filtered": {
         "query": {
            "match_all": {}
         },
         "filter": {
            "and": [
               {
                  "exists": {
                     "field": "time.new_time"
                  }
               },
               {
                  "exists": {
                     "field": "time.first_alert_time"
                  }
               }
            ]
         }
      }
   },
   "aggs": {
      "avg_timedifference": {
         "avg": {
            "script" : "Math.ceil(doc['time.new_time'].value - doc['time.first_alert_time'].value)"
         }
      }
   }
}
2020-06-22