Elasticsearch - 聚合

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聚合框架收集搜尋查詢選擇的所有資料，幷包含許多構建塊，這些構建塊有助於構建資料的複雜摘要。聚合的基本結構如下所示：

"aggregations" : {
   "" : {
      "" : {

      }
 
      [,"meta" : { [] } ]?
      [,"aggregations" : { []+ } ]?
   }
   [,"" : { ... } ]*
}

聚合有不同型別，每種型別都有其自身的用途。本章將詳細討論它們。

指標聚合

這些聚合有助於從聚合文件的欄位值計算矩陣，有時一些值可以從指令碼生成。

數值矩陣可以是單值的，如平均聚合，也可以是多值的，如統計聚合。

Avg 聚合

此聚合用於獲取聚合文件中任何數值欄位的平均值。例如，

POST /schools/_search
{
   "aggs":{
      "avg_fees":{"avg":{"field":"fees"}}
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 41,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : 1.0,
      "hits" : [
         {
            "_index" : "schools",
            "_type" : "school",
            "_id" : "5",
            "_score" : 1.0,
            "_source" : {
               "name" : "Central School",
               "description" : "CBSE Affiliation",
               "street" : "Nagan",
               "city" : "paprola",
               "state" : "HP",
               "zip" : "176115",
               "location" : [
                  31.8955385,
                  76.8380405
               ],
            "fees" : 2200,
            "tags" : [
               "Senior Secondary",
               "beautiful campus"
            ],
            "rating" : "3.3"
         }
      },
      {
         "_index" : "schools",
         "_type" : "school",
         "_id" : "4",
         "_score" : 1.0,
         "_source" : {
            "name" : "City Best School",
            "description" : "ICSE",
            "street" : "West End",
            "city" : "Meerut",
            "state" : "UP",
            "zip" : "250002",
            "location" : [
               28.9926174,
               77.692485
            ],
            "fees" : 3500,
            "tags" : [
               "fully computerized"
            ],
            "rating" : "4.5"
         }
      }
   ]
 },
   "aggregations" : {
      "avg_fees" : {
         "value" : 2850.0
      }
   }
}

Cardinality 聚合

此聚合給出特定欄位的不同值的計數。

POST /schools/_search?size=0
{
   "aggs":{
      "distinct_name_count":{"cardinality":{"field":"fees"}}
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 2,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "distinct_name_count" : {
         "value" : 2
      }
   }
}

注意 - 基數值為 2，因為 fees 中有兩個不同的值。

擴充套件統計聚合

此聚合生成關於聚合文件中特定數值欄位的所有統計資訊。

POST /schools/_search?size=0
{
   "aggs" : {
      "fees_stats" : { "extended_stats" : { "field" : "fees" } }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 8,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "fees_stats" : {
         "count" : 2,
         "min" : 2200.0,
         "max" : 3500.0,
         "avg" : 2850.0,
         "sum" : 5700.0,
         "sum_of_squares" : 1.709E7,
         "variance" : 422500.0,
         "std_deviation" : 650.0,
         "std_deviation_bounds" : {
            "upper" : 4150.0,
            "lower" : 1550.0
         }
      }
   }
}

Max 聚合

此聚合查詢聚合文件中特定數值欄位的最大值。

POST /schools/_search?size=0
{
   "aggs" : {
   "max_fees" : { "max" : { "field" : "fees" } }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 16,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
  "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "max_fees" : {
         "value" : 3500.0
      }
   }
}

Min 聚合

此聚合查詢聚合文件中特定數值欄位的最小值。

POST /schools/_search?size=0
{
   "aggs" : {
      "min_fees" : { "min" : { "field" : "fees" } }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 2,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
  "aggregations" : {
      "min_fees" : {
         "value" : 2200.0
      }
   }
}

Sum 聚合

此聚合計算聚合文件中特定數值欄位的總和。

POST /schools/_search?size=0
{
   "aggs" : {
      "total_fees" : { "sum" : { "field" : "fees" } }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 8,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "total_fees" : {
         "value" : 5700.0
      }
   }
}

還有一些其他指標聚合用於特殊情況，例如用於地理位置的地理邊界聚合和地理中心聚合。

統計聚合

一種多值指標聚合，用於計算從聚合文件中提取的數值的統計資料。

POST /schools/_search?size=0
{
   "aggs" : {
      "grades_stats" : { "stats" : { "field" : "fees" } }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 2,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "grades_stats" : {
         "count" : 2,
         "min" : 2200.0,
         "max" : 3500.0,
         "avg" : 2850.0,
         "sum" : 5700.0
      }
   }
}

聚合元資料

您可以在請求時使用 meta 標籤新增一些關於聚合的資料，並可以在響應中獲取這些資料。

POST /schools/_search?size=0
{
   "aggs" : {
      "avg_fees" : { "avg" : { "field" : "fees" } ,
         "meta" :{
            "dsc" :"Lowest Fees This Year"
         }
      }
   }
}

執行以上程式碼後，我們得到以下結果：

{
   "took" : 0,
   "timed_out" : false,
   "_shards" : {
      "total" : 1,
      "successful" : 1,
      "skipped" : 0,
      "failed" : 0
   },
   "hits" : {
      "total" : {
         "value" : 2,
         "relation" : "eq"
      },
      "max_score" : null,
      "hits" : [ ]
   },
   "aggregations" : {
      "avg_fees" : {
         "meta" : {
            "dsc" : "Lowest Fees This Year"
         },
         "value" : 2850.0
      }
   }
}
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