Aggregations are one of the most powerful and useful features of Elastic Search. Basically, aggregations will make the data stored in Elastic Search more effectively analyzed, summarized and visualized.
There are three main types of aggregations in Elastic Search: metrics, bucket and pipeline. Metric aggregations provide information about numerical values in the data, such as average, sum, or maximum. For example, an average aggregation can be used to determine the average price of a product.
Bucket aggregations, on the other hand, group data into "buckets" based on certain criteria. For example, a term aggregation can be used to group data by the values of a given field, such as product categories in a purchasing catalog.
Finally, pipeline aggregations are used to process the results of other aggregations. For example, a difference aggregation could be used to calculate the difference between the results of two metric aggregations.
Today we talk about aggregations, what they are, what types exist and many practical examples.
Content:
00:03 - What are aggregations in Elastic Search.
00:28 - Types of aggregations in Elastic Search
01:00 - Basic structure of an aggregation
01:40 - Metric type aggregations
04:05 - Aggregations with query in Elastic: avg and sum
05:21 - Bucket aggregations: terms and histogram
07:54 - Example of subaggregations
09:10 - Pipeline type aggregations
13:12 - Which aggregation to use
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