python - Elasticsearch请求

Question

我想对Elasticsearch-dsl或Elasticsearch做以下请求。

Select all users with the same name but different ages

示例:
索引数据:

 {  "name": "name1","age": 20  }
 {  "name": "name2","age": 23  } 
 {  "name": "name3","age": 20  }
 {  "name": "name1","age": 22  }
 {  "name": "name4","age": 18  }
 {  "name": "name2","age": 23  }
 {  "name": "name4","age": 18  }
 {  "name": "name4","age": 14  }

我想要这样的 结果
结果:

 {  "name": "name4","age": 18 ,"age": 14  }
 {  "name": "name1","age": 22 ,"age": 20  }

Answer 1

您需要应用nested aggregations。由于您来自python，因此请遵循python脚本:

from elasticsearch import Elasticsearch

# Connect to the elastic cluster
es=Elasticsearch([{'host':'localhost','port':9200}])

your_data = [
     {  "name": "name1","age": 20  },
     {  "name": "name2","age": 23  },
     {  "name": "name3","age": 20  },
     {  "name": "name1","age": 22  },
     {  "name": "name4","age": 18  },
     {  "name": "name2","age": 23  },
     {  "name": "name4","age": 18  },
     {  "name": "name4","age": 14  }
]

your_index_name = "test_index"

# indexing your exemple data
for doc in your_data:
    es.index(index=your_index_name, body=doc)

首先，您需要为每个名称创建文档存储桶，我将其称为“buckets_for_name”，然后在buckets_for_name内部将嵌套的术语聚合应用于年龄:

# the nested aggregation query 
query = {
  "aggs": {
    "buckets_for_name": {
      "terms": { "field": "name.keyword" },
       "aggs": {
          "age_terms": {
            "terms": {
              "field": "age"
            }
          }
        }
    }
  }
}

res = es.search(index=your_index_name, body=query)

# the results are here
res["aggregations"]["buckets_for_name"]["buckets"]

结果并不理想:

[{'key': 'name4',
  'doc_count': 3,
  'age_terms': {'doc_count_error_upper_bound': 0,
   'sum_other_doc_count': 0,
   'buckets': [{'key': 18, 'doc_count': 2}, {'key': 14, 'doc_count': 1}]}},
 {'key': 'name1',
  'doc_count': 2,
  'age_terms': {'doc_count_error_upper_bound': 0,
   'sum_other_doc_count': 0,
   'buckets': [{'key': 20, 'doc_count': 1}, {'key': 22, 'doc_count': 1}]}},
 {'key': 'name2',
  'doc_count': 2,
  'age_terms': {'doc_count_error_upper_bound': 0,
   'sum_other_doc_count': 0,
   'buckets': [{'key': 23, 'doc_count': 2}]}},
 {'key': 'name3',
  'doc_count': 1,
  'age_terms': {'doc_count_error_upper_bound': 0,
   'sum_other_doc_count': 0,
   'buckets': [{'key': 20, 'doc_count': 1}]}}]

好干净这里有个建议:

pretty_results = []
for result in res["aggregations"]["buckets_for_name"]["buckets"]:
    d = dict()
    d["name"] = result["key"]
    d["ages"] = []
    for age in result["age_terms"]["buckets"]:
        d["ages"].append(age["key"])
    pretty_results.append(d)

漂亮的输出:

[{'name': 'name4', 'ages': [18, 14]},
 {'name': 'name1', 'ages': [20, 22]},
 {'name': 'name2', 'ages': [23]},
 {'name': 'name3', 'ages': [20]}]