stackoverflow.com - questions -59947644

# Based on the query pusblished in the question, I added the following documents to the index.

[
  {
    "@timestamp" : "2020-01-15",
    "condition" : "B",
    "value" : 10,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-15",
    "condition" : "B",
    "value" : 50,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-15",
    "condition" : "A",
    "value" : 50,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-18",
    "condition" : "B",
    "value" : 50,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-18",
    "condition" : "B",
    "value" : 150,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-19",
    "condition" : "B",
    "value" : 10,
    "conditionType" : "ABCD"
  },
  {
    "@timestamp" : "2020-01-19",
    "condition" : "A",
    "value" : 20,
    "conditionType" : "ABCD"
  }
]

# Here is the query. The differences w.r.t. the one in the question are that (1) I dropped the range 
# query on the @timestamp because not relevant; (2) the term filter is on the `condition.keyword` subfield
# (because term-level filters operate only on non-analysed datatypes) and the value is capitalized (because
# the term-level query is case sensitive); (3) I added the `group_by_values` as in my posted solution.

{
  "size": 0,
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "conditionType": "ABCD"
          }
        }
      ]
    }
  },
  "_source": "userData",
  "aggs": {
    "student_data": {
      "date_histogram": {
        "field": "@timestamp",
        "calendar_interval": "day"
      },
      "aggs": {
        "condition_B": {
          "filter": {
            "term": {
              "condition.keyword": "B"
            }
          },
          "aggs": {
            "group_by_values": {
              "terms": {
                "field": "value",
                "size": 100
              }
            },
            "user_avg": {
              "avg": {
                "field": "value"
              }
            }
          }
        }
      }
    }
  }
}

# This is the result, which is as expected.

"aggregations" : {
  "student_data" : {
    "buckets" : [
      {
        "key_as_string" : "2020-01-15T00:00:00.000Z",
        "key" : 1579046400000,
        "doc_count" : 3,
        "condition_B" : {
          "doc_count" : 2,
          "group_by_values" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : 10,
                "doc_count" : 1
              },
              {
                "key" : 50,
                "doc_count" : 1
              }
            ]
          },
          "user_avg" : {
            "value" : 30.0
          }
        }
      },
      {
        "key_as_string" : "2020-01-16T00:00:00.000Z",
        "key" : 1579132800000,
        "doc_count" : 0,
        "condition_B" : {
          "doc_count" : 0,
          "group_by_values" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [ ]
          },
          "user_avg" : {
            "value" : null
          }
        }
      },
      {
        "key_as_string" : "2020-01-17T00:00:00.000Z",
        "key" : 1579219200000,
        "doc_count" : 0,
        "condition_B" : {
          "doc_count" : 0,
          "group_by_values" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [ ]
          },
          "user_avg" : {
            "value" : null
          }
        }
      },
      {
        "key_as_string" : "2020-01-18T00:00:00.000Z",
        "key" : 1579305600000,
        "doc_count" : 2,
        "condition_B" : {
          "doc_count" : 2,
          "group_by_values" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : 50,
                "doc_count" : 1
              },
              {
                "key" : 150,
                "doc_count" : 1
              }
            ]
          },
          "user_avg" : {
            "value" : 100.0
          }
        }
      },
      {
        "key_as_string" : "2020-01-19T00:00:00.000Z",
        "key" : 1579392000000,
        "doc_count" : 2,
        "condition_B" : {
          "doc_count" : 1,
          "group_by_values" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : 10,
                "doc_count" : 1
              }
            ]
          },
          "user_avg" : {
            "value" : 10.0
          }
        }
      }
    ]
  }
}