Introducing the aggregation framework
The aggregation functionality is completely different from search and enables you to ask sophisticated questions of the data. The use cases of aggregation vary from building analytical reports to getting real-time analysis of data and taking quick actions.
Also, despite being different in functionality, aggregations can operate along the usual search requests. Therefore, you can search or filter your data, and at the same time, you can also perform aggregation on the same datasets matched by search/filter criteria in a single request. A simple example can be to find the maximum number of hashtags used by users related to tweets that has crime in the text field. Aggregations enable you to calculate and summarize data about the current query on the fly. They can be used for all sorts of tasks such as dynamic counting of result values to building a histogram.
Aggregations come in two flavors: metrics and buckets.
Metrics: Metrics are used to do statistics...