elasticsearch学习之字段统计

elasticsearch中保存了多个文档，而每个文档中包含多个字段，如果需要对某个字段的文档进行统计归类，可以使用聚合查询的方法

 

1、对某个字段进行聚合统计

​
curl -X GET "elasticsearch.in.netwa.cn:9200/my_index/_search" -H 'Content-Type: application/json' -d'
{
  "aggs": {
    "all_interests": {
      "terms": { "field": "first_tag" }
    }
  }
}
'

​

 结果如下：

{"took":1,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":123,"max_score":1.0,"hits":[...]},"aggregations":{"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":1,"buckets":[{"key":"自然","doc_count":36},{"key":"地理","doc_count":32},{"key":"人文","doc_count":55}]}}}

hits中的total显示了所有统计的文档数量：123

aggregations展示了聚合统计的结果

buckets包含了多个统计结果，first_tag字段统计的结果分别是：

自然：36

地理：32

人文：55

 

2、将查询结果在进行聚合统计

首先查询字段first_tag，得到的结果再对second_tag字段进行聚合统计

curl -X GET "elasticsearch.in.netwa.cn:9200/my_index/_search" -H 'Content-Type: application/json' -d'
{
  "query": {
		"term": {
			"first_tag": "自然"
		}
	},
  "aggs": {
    "all_interests": {
      "terms": { "field": "second_tag" }
    }
  }
}
'

 结果如下：

​
{"took":1,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":36,"max_score":2.2581334,"hits":[...]},"aggregations":{"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":"生物","doc_count":12},{"key":"常识","doc_count":10},{"key":"天文","doc_count":14}]}}}

​

hits中的total显示了所有统计的文档数量36

buckets包含了多个统计结果，first_tag字段统计的结果分别是：

生物：12

常识：10

天文：14

 

3、对多个字段同时进行聚合统计

同时对first_tag和second_tag字段进行聚合统计

curl -X GET "elasticsearch.in.netwa.cn:9200/my_index/_search" -H 'Content-Type: application/json' -d'
{
  "aggs": {
    "all_interests": {
      "terms": { "field": "first_tag" },
	  "aggs": {
		"all_interests": {
			"terms": { "field": "second_tag" }
		}
	  }
    }
  }
}
'

结果如下：

{"took":3,"timed_out":false,"_shards":{"total":5,"successful":5,"skipped":0,"failed":0},"hits":{"total":123,"max_score":1.0,"hits":[...]},"aggregations":{"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":1,"buckets":[{"key":"人文","doc_count":55,"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":"文学","doc_count":20},{"key":"艺术","doc_count":35}]}},{"key":"自然","doc_count":36,"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":"生物","doc_count":12},{"key":"常识","doc_count":10},{"key":"天文","doc_count":14}]}},{"key":"地理","doc_count":32,"all_interests":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":"人文地理","doc_count":11},{"key":"自然地理","doc_count":21}]}}]}}}

hits中的total显示了所有统计的文档数量123

buckets包含了多个统计结果，first_tag及包含的second_tag字段统计的结果分别是：

人文：55，{文学：20，艺术：35}

自然：36 ，{生物：12，常识：10，天文：14}

地理：32 ，{人文地理：11，自然地理：21}

 

 

参考网址：

https://www.elastic.co/guide/en/elasticsearch/reference/2.4/search-aggregations-metrics-avg-aggregation.html

https://blog.csdn.net/xialei199023/article/details/48298635

https://blog.csdn.net/lpp_dd/article/details/73136059