Elastic_Terms 内容分类统计

Terms 按字段的值进行分类，并计算出doc_count，

bucket聚合 类似于 group by

常用统计 分类并出现频率高的，并进一步挖出，计算出想要的数据。

参考资料

    https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html    

1.批量插入数据

   curl -XPOST 127.0.0.1:9200/cars/transactions/_bulk --data-binary @cars.json   

{ "index": {}}
{ "price" : 10000, "color" : "red", "make" : "honda", "sold" : "2014-10-28" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 30000, "color" : "green", "make" : "ford", "sold" : "2014-05-18" }
{ "index": {}}
{ "price" : 15000, "color" : "blue", "make" : "toyota", "sold" : "2014-07-02" }
{ "index": {}}
{ "price" : 12000, "color" : "green", "make" : "toyota", "sold" : "2014-08-19" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 80000, "color" : "red", "make" : "bmw", "sold" : "2014-01-01" }
{ "index": {}}
{ "price" : 25000, "color" : "blue", "make" : "ford", "sold" : "2014-02-12" }

2.哪种颜色的车卖的最好
  http://192.168.1.10:9200/cars/
       _search?search_type=count //并不关心搜索结果,只关心统计，使用的search_type是count

{ "aggs": {
    "color": {
      "terms": {             //定义了一个terms类型的桶，它针对color字段聚合,terms桶会动态地为每一个它遇到的不重复的词条创建一个新的桶
        "field": "color",
        "size": 50,                //返回结果大小
        "min_doc_count": 1,         //控制最小计数 大于1才显示
        "order": {"_count": "asc" } //排序方式
      }
    }
  }
}

  //每个桶中的key对应的是在color字段中找到的不重复的词条。它同时也包含了一个doc_count，用来表示包含了该词条的文档数量。
  //响应包含了一个桶列表，每个桶都对应着一个不重复的颜色(比如，红色或者绿色)。每个桶也包含了“掉入”该桶中的文档数量。比如，有4辆红色的车

3.每种颜色汽车的平均价格是多少?

{  "aggs": {
    "color": {
      "terms": {
        "field": "color",
        "size": 50,
        "min_doc_count": 1,
        "order": {  "avg_price": "asc"    }    //按平均价格排序
       },
       "aggs": {           //添加了一个新的aggs层级（聚合层）avg 指标嵌套在terms桶中，每种颜色都计算一个平均值
        "avg_price": {
          "avg": {  "field": "price"  }
        }
      }
    }
  }
}

返回每个颜色汽车的个数及平均价格

4.每种颜色的汽车的制造商分布信息?

{"aggs": {
    "color": {
      "terms": {
        "field": "color",
        "size": 50,
        "min_doc_count": 1,
        "order": {"avg_price": "asc" }
      },
      "aggs": {
        "avg_price": {
          "avg": { "field": "price"      }
        },
        "make": { //添加了新聚合make，它是一个terms类型的桶(嵌套在名为colors的terms桶中)。这意味着会根据数据集创建不重复的(color, make)组合
          "terms": { "field": "make"  }
        }
      }
    }
  }
}

4.再添加 每个制造商 最低和最高价格?

{ "aggs": {
    "color": {
      "terms": {
        "field": "color",
        "size": 50,
        "min_doc_count": 1,
        "order": {
          "avg_price": "asc"
        }
      },
      "aggs": {
        "avg_price": {
          "avg": {
            "field": "price"
          }
        },
        "make": {
          "terms": { "field": "make"},
          "aggs": {
            "min_price": { "min": { "field": "price"       }       },
            "max_price": { "max": {   "field": "price"   }       }
          }
        }
      }
    }
  }
}

5.再添加 每个制造商 价格列表?

{
  "aggs": {
    "color": {
      "terms": {
        "field": "color",
        "size": 50,
        "min_doc_count": 1,
        "order": {
          "avg_price": "asc"
        }
      },
      "aggs": {
        "avg_price": {
          "avg": {
            "field": "price"
          }
        },
        "make": {
          "terms": {
            "field": "make"
          },
          "aggs": {
            "price": {
              "terms": {
                "field": "price"
              }
            },
            "min_price": {
              "min": {
                "field": "price"
              }
            },
            "max_price": {
              "max": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
}