_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 } ] } } }