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我有如下数据：

{
  "_index": "user_log",
  "_type": "logs",
  "_id": "gdUJpXIBAoADuwvHTK29",
  "_score": 1,
  "_source": {
    "user_id": 105,
    "user_name": "prathameshsalap@gmail.com",
    "working_hours": "2019-10-21 09:00:01",
    "date": "2019-10-21",
    "working_minutes": 540   
}

{
  "_index": "user_log",
  "_type": "logs",
  "_id": "gtUJpXIBAoADuwvHTK29",
  "_version": 1,
  "_score": 0,
  "_source": {
    "user_id": 106,
    "user_name": "vaishusawant143@gmail.com",
    "working_hours": "2019-10-21 09:15:01",
    "date": "2019-10-21",
    "working_minutes": 555
}

在这里，我有多个字段，例如 user_id、user_name、working_hours、date、working_minutes。我只想选择 user_id、user_name 和 avg_hours（在为每个用户计算 avg_working_minutes 之后）。

body = {
    "query" : {"match_all": {}},
     "aggs": {
      "users": {
          "terms": {
              "field": "user_name.keyword",
              "order": {
                 "avg_hours": "desc"
              }
          },
          "aggs": {
              "avg_hours": {
                  "avg": {
                      "field": "working_minutes"
                  }
              }
          }
      }
  }
}

es_obj = Elasticsearch()
response = els_obj.search(index='user_log', body)
# save into csv
with open(path, 'w') as files:
    header_present = False
    for doc in response['hits']['hits']:
        my_dict = doc['_source'] 
        if not header_present:
           w = csv.DictWriter(files, my_dict.keys())
           w.writeheader()
           header_present = True
        w.writerow(my_dict)

它的返回输出如下：

user_id  |  date    |         user_name       |  working_hours,   | working_minutes
---------|----------|-------------------------|-------------------|----------
  105    |2019-10-21|prathameshsalap@gmail.com|2019-10-21 09:00:01|   540
  106    |2019-10-21|vaishusawant143@gmail.com|2019-10-21 09:15:01|   555

这里它返回所有 user_id、user_name、working_hours、date、working_minutes。我不想要所有这些领域。那么，如何在此查询中选择多个字段（user_id、user_name 和 avg_hours）？

预期输出：

user_id  |         user_name       | Avg_hour
---------|-------------------------|----------
  105    |prathameshsalap@gmail.com|   450.55
  106    |vaishusawant143@gmail.com|   350
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