Elastic Search 如何按日期分组（当嵌套在数组中时）

Question

我的数据库结构如下：

{
    name:"string",
    ....
    arrayData: [ 
        { price:100, date: "yyyy-mm-dd" },
        { price:120, date: "yyyy-mm-dd" } ,
        { price:150, date: "yyyy-mm-dd" } ,
        { price:250, date: "yyyy-mm-dd" } 
    ]
}

如何获得 2015 年 的平均价格？

我目前的方法是使用此过滤器汇总价格：

{
  "range": {
    "arrayData.date": {
      "gte": "2015-01-01",
      "lt": "2016-01-01"
    }
  }
}

测试聚合：

"aggs": {
    "2": {
      "date_histogram": {
        "field": "arrayData.date",
        "interval": "1y",
        "time_zone": "Europe/Helsinki",
        "min_doc_count": 1
      },
      "aggs": {
        "1": {
          "avg": {
            "field": "arrayData.price"
          }
        }
      }
    }
  }

但这也将在 arrayData 中获得具有匹配日期的文档中其他年份的平均值。

这也应该与 Kibana 一起使用，因为最后我必须将它添加到仪表板。

Answer 1

使用术语聚合你会得到你的结果。

       {
            "aggs": {
                 "date": {
                 "terms": {
                 "field": "date"
       },
           "aggs": {
                 "average": {
                 "avg": {
                 "field": "price"
                        }
                         }
                  }
                  }
                  }
                   }

Answer 2

看来我需要将数组中的对象映射为 nested。

根据 Elastic 文档：

Arrays of inner object fields do not work the way you may expect. Lucene has no concept of inner objects, so Elasticsearch flattens object hierarchies into a simple list of field names and values. For instance, the following document:
{
  "user" : [ 
    {
      "first" : "John",
      "last" :  "Smith"
    },
    {
      "first" : "Alice",
      "last" :  "White"
    }
  ]
}
The user field is dynamically added as a field of type object and would be transformed internally into a document that looks more like this:
{
  "user.first" : [ "alice", "john" ],
  "user.last" :  [ "smith", "white" ]
}

Elastic Search 如何按日期分组（当嵌套在数组中时）

Elastic Search how to group by date (when nested in arrays)

elasticsearch

kibana

kibana-4