Is it possible to create a map in runtime mode, which will be filled in passing through all document-CodePudding

For ex: I have 2 documents with this body:

{
  "id": "doc_one",
  "name": "test_name",
  "date_creation": "some_date_cr_1",
  "date_updation": "some_date_up_1"
}

And the second doc:

{
  "id": "doc_two",
  "name": "test_name",
  "date_creation": "some_date_cr_2",
  "date_updation": "some_date_up_2"
}

What I want to do: to create two runtime field or Map('data_creation',count_of_doc_where_field_not_null_AND_the_condition_is_met).

For ex: I've got the 1st doc, there is date_creation IS NOT NULL and the condition startDate<=date_creation<=endDate is met, so, I create some field count = 0 and when I've got this case I do count . When I will get all the docs I will set finally count value from map as result: Map('data_creation',final_count) and the same for another field but in the same map.

I tried to use script, but there is return Map for each doc, for ex:

{
            "_index": "my_index_001",
            "_type": "_doc",
            "_id": "1",
            "_score": 1.0,
            "fields": {
                "my_doubled_field": [
                    {
                        "NEW": 2
                    }
                ]
            }
        },
        {
            "_index": "my_index_001",
            "_type": "_doc",
            "_id": "2",
            "_score": 1.0,
            "fields": {
                "my_doubled_field": [
                    {
                        "NEW": 2
                    }
                ]
            }
        }

CodePudding user response：

I have index below 3 documents to index where one document dont have date_creation field:

POST sample/_doc
{
  "id": "doc_two",
  "name": "test_name",
  "date_updation": "some_date_up_2"
}

POST sample/_doc
{
  "id": "doc_one",
  "name": "test_name",
  "date_creation": "some_date_cr_1",
  "date_updation": "some_date_up_1"
}

POST sample/_doc
{
  "id": "doc_two",
  "name": "test_name",
  "date_creation": "some_date_cr_2",
  "date_updation": "some_date_up_2"
}

Now you can use filter aggregation from elasticsearch as shown below:

{
  "size": 0,
  "aggs": {
    "date_creation": {
      "filter": {
        "range": {
          "date_creation": {
            "gte": "2020-01-09T10:20:10"
          }
        }
      }
    },
    "date_updation": {
      "filter": {
        "range": {
          "date_updation": {
            "gte": "2020-01-09T10:20:10"
          }
        }
      }
    }
  }
}

Response:

"hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "date_updation" : {
      "meta" : { },
      "doc_count" : 3
    },
    "date_creation" : {
      "meta" : { },
      "doc_count" : 2
    }
  }

You can see date_updation field is available in 3 doc so it is showing count as 3 and date_creation field is available in 2 doc so it is showing count as 2.