弹性搜索请求

Question

我想用 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

不特定于Python，这里需要的是关于年龄的术语聚合，其中名称是特定值：

GET /_search
{
  "query" : {
     "bool" : {
        "should" : { "match" : { "name" : "name1"} }
     }
  },
  "aggs": {
    "ages_for_name": {
      "terms": { "field": "age" } 
    }
  }
}

和运行这用于“name1”和“name4”以获取“ages_for_name”存储桶并仅使用键（存储桶名称）并忽略存储桶值。

Answer 2

还有另一种方法可以解决此问题，方法是聚合姓名，然后仅选择具有不同 min/max 年龄的姓名桶：

POST test/_search
{
  "size": 0,
  "aggs": {
    "names": {
      "terms": {
        "field": "name.keyword",
        "size": 10,
        "min_doc_count": 2
      },
      "aggs": {
        "min_age": {
          "min": {
            "field": "age"
          }
        },
        "max_age": {
          "max": {
            "field": "age"
          }
        },
        "all_ages": {
          "terms": {
            "field": "age",
            "size": 10
          }
        },
        "diff_ages": {
          "bucket_selector": {
            "buckets_path": {
              "min": "min_age",
              "max": "max_age"
            },
            "script": "params.min != params.max"
          }
        }
      }
    }
  }
}

响应：您只得到名字 name1 和 name4 因为 name2 有相同的 min/max 年龄。

  "buckets" : [
    {
      "key" : "name4",
      "doc_count" : 3,
      "max_age" : {
        "value" : 18.0
      },
      "all_ages" : {
        "doc_count_error_upper_bound" : 0,
        "sum_other_doc_count" : 0,
        "buckets" : [
          {
            "key" : 18,
            "doc_count" : 2
          },
          {
            "key" : 14,
            "doc_count" : 1
          }
        ]
      },
      "min_age" : {
        "value" : 14.0
      }
    },
    {
      "key" : "name1",
      "doc_count" : 2,
      "max_age" : {
        "value" : 22.0
      },
      "all_ages" : {
        "doc_count_error_upper_bound" : 0,
        "sum_other_doc_count" : 0,
        "buckets" : [
          {
            "key" : 20,
            "doc_count" : 1
          },
          {
            "key" : 22,
            "doc_count" : 1
          }
        ]
      },
      "min_age" : {
        "value" : 20.0
      }
    }
  ]

Answer 3

您需要申请nested aggregations。由于您来自 python，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)

首先你需要为每个名字创建文档桶，我称之为“buckets_for_name”，然后在 buckets_for_name 中应用年龄的嵌套术语聚合：

# 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"]

结果并不如你所愿：

[{'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}]}}]

这么干净。这里有一个建议：

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]}]

弹性搜索请求

Elasticsearch request

python

request

elasticsearch

elasticsearch-dsl