Aggregation Concepts

MongoDB aggregation framework provides a way to process and transform data that is stored in our MongoDB collections. It allows you to perform calculations and return the calculated results using various data aggregation tools such as aggregation pipelines, map-reduce functions, or single-purpose aggregation methods.

Here are some of the most important concepts of MongoDB Aggregation:

• Pipeline: A pipeline is a series of stages that are executed in order to process the data. Each stage transforms the data in some way and passes it to the next stage. The output of the last stage is the final result of the pipeline.
• Stage: A stage is a single operation that is applied to the data. It can be a simple transformation or a complex aggregation. Each stage has a specific purpose and is responsible for a single task.
• Operator: An operator is a special symbol that is used to perform a specific operation on the data. It can be a mathematical operator, a logical operator, or a comparison operator.

Example of a simple aggregation pipeline:

db.collection.aggregate([
  { $match: { status: 'A' } },
  { $group: { _id: '$cust_id', total: { $sum: '$amount' } } },
  { $sort: { total: -1 } },
]);

Each item in the pipeline is a stage. The first stage is a $match stage that filters the documents in the collection. The second stage is a $group stage that groups the documents by the cust_id field and calculates the sum of the amount field. The third stage is a $sort stage that sorts the documents by the total field in descending order.