A pipeline aggregation in Elasticsearch is a way to perform additional computations on the results of other aggregations. It allows you to apply a series of transformations or calculations to the output of one or more aggregations, and obtain a new set of results that reflects the transformed data.
When you perform a pipeline aggregation, you specify one or more input aggregations that provide the data to be transformed, and one or more pipeline aggregations that perform the transformations. Pipeline aggregations can be chained together to perform a series of transformations in a specific order.
Pipeline aggregations can perform a wide range of transformations, including arithmetic operations, statistical calculations, bucketing, filtering, and more. The output of a pipeline aggregation can be a single value or a new set of buckets, depending on the type of aggregation.
For example, let’s say you have an index of customer orders, and each document has a “product” field that represents the product ordered, and a “price” field that represents the price of the product. You could perform a terms aggregation on the “product” field to group the orders by product, and a sum aggregation on the “price” field to calculate the total revenue for each product. You could then perform a pipeline aggregation to calculate the average revenue per product, by dividing the total revenue by the number of orders for each product.
Pipeline aggregations can be useful for a wide range of applications, such as calculating ratios, detecting anomalies, or generating reports. They allow you to perform complex calculations on your data, while also taking advantage of the powerful aggregation capabilities of Elasticsearch.