Metric aggregation
Grasp the concept of metric aggregation and how to consolidate data based on specific criteria.
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Overview
Metrics aggregation is a type of aggregation that calculates metric data such as sum or average. It mainly refers to the mathematical calculations performed across a set of documents, usually based on the values of a numerical field present in the document. There are several types of metrics aggregations available in Elasticsearch, each serving a different purpose, such as:

Sum aggregation: It calculates the sum of a numeric field across all documents matching the query.

Avg aggregation: It computes the average of a numeric field across the matching documents.

Min aggregation: It finds the minimum value of a numeric field among the documents.

Max aggregation: It determines the maximum value of a numeric field among the documents.

Stats aggregation: It provides a collection of basic statistics about a numeric field, including count, sum, average, min, and max.

Extended stats aggregation: It is similar to the stats aggregation, but it includes additional statistical information such as standard deviation and variance.

Percentiles aggregation: It computes one or more percentiles (e.g., 25th, 50th, and 75th) for a numeric field.

Cardinality aggregation: It estimates the distinct count of values in a numeric or keyword field.

Value count aggregation: It counts the number of nonnull values in a numeric or keyword field.

The
top_hits
metric aggregator: It keeps track of the most relevant document being aggregated. This aggregator is intended to be used as a subaggregator so that the top matching documents can be aggregated per bucket.
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