聚合数据分析histogram按价格区间统计电视销量和销售额

histogram: 类似与terms,也是进行bucket分组操作,接收一个field,按照这个field的值的各个范围区间,进行bucket分组操作

"histogram":{ 
  "field": "price",
  "interval": 2000
}

interval: 2000,划分范围: 0-2000,2000-4000,4000-6000,6000-8000,8000-10000
去根据price的值,比如2500,看落在哪个区间内,比如2000-4000,此时就会将这条数据放入2000-4000对应的哪个bucket中
bucket划分的方法,terms,将field值相同的数据划分到一个bucket中
bucket有了之后,一样的,去对每个bucket执行avg,count,sum,max,min,等个中metric操作,聚合分析

GET /tvs/sales/_search
{
  "size": 0,
  "aggs": {
    "group_by_price": {
      "histogram": {
        "field": "price",
        "interval": 2000
      },
      "aggs": {
        "sum_price": {
          "sum": {
            "field": "price"
          }
        }
      }
    }
  }
}

{
  "took": 14,
  "timed_out": false,
  "_shards": {
    "total": 3,
    "successful": 3,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 8,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_price": {
      "buckets": [
        {
          "key": 0,
          "doc_count": 3,
          "sum_price": {
            "value": 3700
          }
        },
        {
          "key": 2000,
          "doc_count": 4,
          "sum_price": {
            "value": 9500
          }
        },
        {
          "key": 4000,
          "doc_count": 0,
          "sum_price": {
            "value": 0
          }
        },
        {
          "key": 6000,
          "doc_count": 0,
          "sum_price": {
            "value": 0
          }
        },
        {
          "key": 8000,
          "doc_count": 1,
          "sum_price": {
            "value": 8000
          }
        }
      ]
    }
  }
}