范围内的数组字段上的 Elasticsearch 聚合

Question

我将通过过滤范围内的值来对数组字段执行计数聚合。例如，我有以下 3 个文档，我想找出从 20210101 到 now() 之间的 purchase_date_list 的值计数。预期结果（20210101 - now() 之间的购买计数）将是： customer_id：1，购买次数为：2 customer_id：2，购买次数为：0 customer_id：3，购买次数为：1

有人可以就如何为上述请求编写聚合查询提供一些想法吗？

非常感谢！

{
  customer_id: 1,
  purchase_date_list: [
    20050101,
    20210304,
    20211121
  ]
},
{
  customer_id: 2,
  purchase_date_list: [
    20100301
  ]
},
{
  customer_id: 3,
  purchase_date_list: [
    20210701
  ]
}

Answer 1

根据我的评论，它使用无痛解决了它。 （因为我仍然不确定如何使用聚合来处理它）

这是帮助我解决此问题的文档。 [doc]

设置

PUT /so_agg_test/

POST /so_agg_test/_doc
{
  "customer_id": 1,
  "purchase_date_list": [
    20050101,
    20210304,
    20211121
  ]
}

POST /so_agg_test/_doc
{
  "customer_id": 2,
  "purchase_date_list": [
    20100301
  ]
}

POST /so_agg_test/_doc
{
  "customer_id": 3,
  "purchase_date_list": [
    20210701
  ]
}

GET /so_agg_test/_search

解决方案

此查询将在您的hits 中创建一个名为number_of_sales_interval 的新字段。

GET /so_agg_test/_search
{
  "query": {
    "match_all": {}
  },
  "script_fields": {
    "number_of_sales_interval": {
      "script": {
        "lang": "painless",
        "params": {
          "lower_bound": 20210101
        }, 
        "source": """
        def dates = doc['purchase_date_list'];
        
        def number_of_sales_interval = 0;
        for(date in dates){
          if(date > params.lower_bound){
            number_of_sales_interval += 1;
          }
        }
        
        return number_of_sales_interval;
        """
      }
    }
  }
}

结果

你应该有类似的东西。

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "so_agg_test",
        "_type" : "_doc",
        "_id" : "UOVplX0B0iK523s0yaCu",
        "_score" : 1.0,
        "fields" : {
          "number_of_sales_interval" : [
            2
          ]
        }
      },
      {
        "_index" : "so_agg_test",
        "_type" : "_doc",
        "_id" : "UeVplX0B0iK523s01KC-",
        "_score" : 1.0,
        "fields" : {
          "number_of_sales_interval" : [
            0
          ]
        }
      },
      {
        "_index" : "so_agg_test",
        "_type" : "_doc",
        "_id" : "UuVplX0B0iK523s04KAT",
        "_score" : 1.0,
        "fields" : {
          "number_of_sales_interval" : [
            1
          ]
        }
      }
    ]
  }
}