_doc_count field

Bucket aggregations always return a field named doc_count showing the number of documents that were aggregated and partitioned in each bucket. Computation of the value of doc_count is very simple. doc_count is incremented by 1 for every document collected in each bucket.

While this simple approach is effective when computing aggregations over individual documents, it fails to accurately represent documents that store pre-aggregated data (such as histogram or aggregate_metric_double fields), because one summary field may represent multiple documents.

To allow for correct computation of the number of documents when working with pre-aggregated data, we have introduced a metadata field type named _doc_count. _doc_count must always be a positive integer representing the number of documents aggregated in a single summary field.

When field _doc_count is added to a document, all bucket aggregations will respect its value and increment the bucket doc_count by the value of the field. If a document does not contain any _doc_count field, _doc_count = 1 is implied by default.

The following create index API request creates a new index with the following field mappings:

• my_histogram, a histogram field used to store percentile data
• my_text, a keyword field used to store a title for the histogram

PUT my_index
{
  "mappings" : {
    "properties" : {
      "my_histogram" : {
        "type" : "histogram"
      },
      "my_text" : {
        "type" : "keyword"
      }
    }
  }
}

The following index API requests store pre-aggregated data for two histograms: histogram_1 and histogram_2.

PUT my_index/_doc/1
{
  "my_text" : "histogram_1",
  "my_histogram" : {
      "values" : [0.1, 0.2, 0.3, 0.4, 0.5],
      "counts" : [3, 7, 23, 12, 6]
   },
  "_doc_count": 45
}
PUT my_index/_doc/2
{
  "my_text" : "histogram_2",
  "my_histogram" : {
      "values" : [0.1, 0.25, 0.35, 0.4, 0.45, 0.5],
      "counts" : [8, 17, 8, 7, 6, 2]
   },
  "_doc_count": 62
}

1. Field _doc_count must be a positive integer storing the number of documents aggregated to produce each histogram.

If we run the following terms aggregation on my_index:

GET /_search
{
    "aggs" : {
        "histogram_titles" : {
            "terms" : { "field" : "my_text" }
        }
    }
}

We will get the following response:

{
    ...
    "aggregations" : {
        "histogram_titles" : {
            "doc_count_error_upper_bound": 0,
            "sum_other_doc_count": 0,
            "buckets" : [
                {
                    "key" : "histogram_2",
                    "doc_count" : 62
                },
                {
                    "key" : "histogram_1",
                    "doc_count" : 45
                }
            ]
        }
    }
}