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我必须从时区的不同部分获取数据（例如纽约 -6.00 和罗马 +2.00）。在文档中，我有一个字段“时间戳”定义为“数据”，例如，我创建了一个“日期直方图”，例如从上午 8 点到上午 9 点。如何匹配 USA 8.00-9.00 和 ITA 8.00-9.00 数据以便比较同一时期的两个数据？

这是我的数据有两个不同的保险丝。2 个来自美国，2 个来自 ITA：

 "hits" : [
  {
    "_index" : "test-data-2021-8-4",
    "_type" : "_doc",
    "_id" : "9tS4EHsB4Ke8qtFfYqbg",
    "_score" : 1.0,
    "_source" : {
      "id" : "mtKDIsEfSr3I8AwCDE1Gjw_11",
      "value" : 87.2,
      "timestamp" : "2021-08-04T12:32:04+02:00"
    }
  },
  {
    "_index" : "test-data-2021-8-4",
    "_type" : "_doc",
    "_id" : "99S4EHsB4Ke8qtFfYqbg",
    "_score" : 1.0,
    "_source" : {
      "id" : "mtKDIsEfSr3I8AwCDE1Gjw_5",
      "value" : 31.0025,
      "timestamp" : "2021-08-04T12:32:04+02:00"
    }
  },
  {
    "_index" : "test-data-2021-8-4",
    "_type" : "_doc",
    "_id" : "wdOREHsB4Ke8qtFfuZAf",
    "_score" : 1.0,
    "_source" : {
      "id" : "mtKDIsEfSr3I8AwCDE1Gjw_11",
      "value" : 15.1,
      "timestamp" : "2021-08-04T05:49:50-04:00"
    }
  },
  {
    "_index" : "test-data-2021-8-4",
    "_type" : "_doc",
    "_id" : "wtOREHsB4Ke8qtFfuZAg",
    "_score" : 1.0,
    "_source" : {
      "id" : "mtKDIsEfSr3I8AwCDE1Gjw_5",
      "value" : 27.9457,
      "timestamp" : "2021-08-04T05:49:50-04:00"
    }
  }
]

这是我的 date_histogram 查询：

    GET /test-data-*/_search?size=10000
{
  "aggs": {
    "agg_sum": {
      "date_histogram": {
        "field": "timestamp",
        "fixed_interval": "1h"
      },
      "aggs": {
        "aggregazione": {
          "sum": {
            "field": "value"
          }
        }
      }
    }
  },
  "size": 0,
  "fields": [
    {
      "field": "timestamp",
      "format": "date_time"
    }
  ],
  "stored_fields": [
    "*"
  ],
  "query": {
    "bool": {
      "must": [],
      "filter": [
        {
          "range": {
            "timestamp": {
              "gte": "2021-08-04T08:00:00.000",
              "lte": "2021-08-04T09:00:00.000",
              "format": "strict_date_optional_time"
            }
          }
        }
      ],
      "should": [],
      "must_not": []
    }
  }
}

提前感谢您的回复。

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