我的思路是按照时间进行分组,
{
  "size":0,
  "aggs":{
    "group_by_date":{
      "date_histogram": {
        "field": "@timestamp",
        "interval": "day"
      }
    }
  }
  
}以下是我完整的dsl:
{
  "size":0,
  "aggs":{
    "group_by_date":{
      "date_histogram": {
        "field": "@timestamp",
        "interval": "day"
      }
    },
    "avg_stately_day" : {
    "avg_bucket": {
      "buckets_path": "group_by_date.doc_count"
    }
  }
  }
}我的返回结果
"aggregations" : {
    "group_by_date" : {
      "buckets" : [
        {
          "key_as_string" : "2020-10-30T00:00:00.000Z",
          "key" : 1604016000000,
          "doc_count" : 809
        },
        {
          "key_as_string" : "2020-10-31T00:00:00.000Z",
          "key" : 1604102400000,
          "doc_count" : 166
        }
      ]
    },
    "avg_stately_day" : {
      "value" : null
    }}
 
	
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pony_maggie - 公众号:犀牛饲养员的技术笔记
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