elasticsearch-dsl聚合-1

接续上篇，本篇介绍elasticsearch聚合查询，使用python库elasticsearch-dsl进行聚合查询操作。

7.3、聚合查询

高阶概念

Buckets(桶/集合):满足特定条件的文档的集合

Metrics(指标):对桶内的文档进行统计计算(例如最小值,求和,最大值等)

新建一张测试表

 PUT cars

 {

   "mappings": {

     "transactions":{

       "properties": {

         "price":{

           "type": "integer"

         },

         "color":{

           "type": "text",

           "fielddata": true

         },

         "make":{

           "type": "text",

           "fielddata": true

         },

         "sold":{

           "type": "date",

           "format": "yyyy-MM-dd"

         }

       }

     }

   }

 }

插入数据

 POST /cars/transactions/_bulk

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "red", "make" : "honda", "sold" : "2014-10-28" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "red", "make" : "honda", "sold" : "2014-11-05" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "green", "make" : "ford", "sold" : "2014-05-18" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "blue", "make" : "toyota", "sold" : "2014-07-02" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "green", "make" : "toyota", "sold" : "2014-08-19" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "red", "make" : "honda", "sold" : "2014-11-05" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "red", "make" : "bmw", "sold" : "2014-01-01" }

 { "index": {"_index": "cars", "_type": "transactions"}}

 { "price" : , "color" : "blue", "make" : "ford", "sold" : "2014-02-12" }

查询哪个颜色的汽车销量最好（按颜色分类）

 GET cars/transactions/_search

 {

   "size": ,

   "aggs": {

     "popular_colors": {

       "terms": {

         "field": "color"

       }

     }

   }

 }

 s = Search(index='cars')

 a = A("terms", field="color")

 s.aggs.bucket("popular_color", a)

 response = s.execute()

或者

 s.aggs.bucket("popular_color", "terms", field="color")

查询每种颜色车的平均价格

 GET cars/transactions/_search

 {

   "size": ,

   "aggs": {

     "colors": {

       "terms": {

         "field": "color"

       },

       "aggs": {

         "avg_price": {

           "avg": {

             "field": "price"

           }

         }

       }

     }

   }

 }

 s = Search(index='cars')

 a1 = A("terms", field="color")

 a2 = A("avg", field="price")

 s.aggs.bucket("colors", a1).metric("avg_price", a2)

 response = s.execute()

或者

 s = Search(index='cars')

 s.aggs.bucket("colors", "terms", field="color").metric("avg_price", "avg", field="price")

 response = s.execute()

先按颜色分，再按品牌分，再求每种品牌的均价

 GET cars/transactions/_search

 {

   "size": ,

   "aggs": {

     "colors": {

       "terms": {

         "field": "color"

       },

       "aggs": {

         "make": {

           "terms": {

             "field": "make"

           },

           "aggs": {

             "avg_price": {

               "avg": {

                 "field": "price"

               }

             }

           }

         }

       }

     }

   }

 }

 s = Search(index='cars')

 s.aggs.bucket("colors", "terms", field="color")

 s.aggs["colors"].bucket("make", "terms", field="make")

 s.aggs["colors"].aggs["make"].metric("avg_price", "avg", field="price")

 response = s.execute()

先按颜色分，再按品牌分，再求每种品牌的最高和最低价

 GET cars/transactions/_search

 {

   "size": ,

   "aggs": {

     "colors": {

       "terms": {

         "field": "color"

       },

       "aggs": {

         "make": {

           "terms": {

             "field": "make"

           },

           "aggs": {

             "min_price": {

               "min": {

                 "field": "price"

               }

             },

             "max_price": {

               "max": {

                 "field": "price"

               }

             }

           }

         }

       }

     }

   }

 }

 s = Search(index='cars')

 s.aggs.bucket("colors", "terms", field="color")

 s.aggs["colors"].bucket("make", "terms", field="make")

 s.aggs["colors"].aggs["make"].metric("min_price", "min", field="price")

 s.aggs["colors"].aggs["make"].metric("max_price", "max", field="price")

 response = s.execute()

未完待续...

巴特西

elasticsearch-dsl聚合-1

7.3、聚合查询

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