44深入聚合数据分析_bucket filter：统计牌品最近一个月的平均价格

在聚合中进行过滤

查询品牌是长虹的电视，并且过滤售卖日期在150天内，然后统计平均价格，再过滤售卖日期在140天内，然后统计平均价格，再过滤售卖日期在130天内，然后统计平均价格.

GET /tvs/sales/_search 
{
  "size": 0,
  "query": {
    "term": {
      "brand": {
        "value": "长虹"
      }
    }
  },
  "aggs": {
    "recent_150d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "now-150d"
          }
        }
      },
      "aggs": {
        "recent_150d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    },
    "recent_140d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "2017-03-19-140d"
          }
        }
      },
      "aggs": {
        "recent_140d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    },
    "recent_130d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "now-130d"
          }
        }
      },
      "aggs": {
        "recent_130d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    }
  }
}

aggs.filter，针对的是聚合去做的

如果放query里面的filter，是全局的，会对所有的数据都有影响

但是比如说，你要统计，长虹电视，最近1个月的平均值; 最近3个月的平均值; 最近6个月的平均值

bucket filter：是对不同的bucket下的aggs，进行filter

GET tvs/sales/_search

响应结果

{
  "took": 0,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 8,
    "max_score": 1,
    "hits": [
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYI",
        "_score": 1,
        "_source": {
          "price": 1200,
          "color": "绿色",
          "brand": "TCL",
          "sold_date": "2016-08-19"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYK",
        "_score": 1,
        "_source": {
          "price": 8000,
          "color": "红色",
          "brand": "三星",
          "sold_date": "2017-01-01"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYE",
        "_score": 1,
        "_source": {
          "price": 1000,
          "color": "红色",
          "brand": "长虹",
          "sold_date": "2016-10-28"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYF",
        "_score": 1,
        "_source": {
          "price": 2000,
          "color": "红色",
          "brand": "长虹",
          "sold_date": "2016-11-05"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYG",
        "_score": 1,
        "_source": {
          "price": 3000,
          "color": "绿色",
          "brand": "小米",
          "sold_date": "2016-05-18"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYJ",
        "_score": 1,
        "_source": {
          "price": 2000,
          "color": "红色",
          "brand": "长虹",
          "sold_date": "2016-11-05"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYH",
        "_score": 1,
        "_source": {
          "price": 1500,
          "color": "蓝色",
          "brand": "TCL",
          "sold_date": "2016-07-02"
        }
      },
      {
        "_index": "tvs",
        "_type": "sales",
        "_id": "AX1PKYdDl-iNu-QvdWYL",
        "_score": 1,
        "_source": {
          "price": 2500,
          "color": "蓝色",
          "brand": "小米",
          "sold_date": "2017-02-12"
        }
      }
    ]
  }
}

由于之前的数据都是2017年的数据，这里可以改为过滤售卖日期在指定日期的N天内

GET /tvs/sales/_search 
{
  "size": 0,
  "query": {
    "term": {
      "brand": {
        "value": "长虹"
      }
    }
  },
  "aggs": {
    "recent_150d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "2017-03-19||-150d"
          }
        }
      },
      "aggs": {
        "recent_150d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    },
    "recent_140d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "2017-03-19||-140d"
          }
        }
      },
      "aggs": {
        "recent_140d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    },
    "recent_130d": {
      "filter": {
        "range": {
          "sold_date": {
            "gte": "2017-03-19||-130d"
          }
        }
      },
      "aggs": {
        "recent_130d_avg_price": {
          "avg": {
            "field": "price"
          }
        }
      }
    }
  }
}

响应结果

{
  "took": 1,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "recent_130d": {
      "doc_count": 0,
      "recent_130d_avg_price": {
        "value": null
      }
    },
    "recent_140d": {
      "doc_count": 2,
      "recent_140d_avg_price": {
        "value": 2000
      }
    },
    "recent_150d": {
      "doc_count": 3,
      "recent_150d_avg_price": {
        "value": 1666.6666666666667
      }
    }
  }
}