MongoDB Aggregation Pipeline Stages

The MongoDB aggregation pipeline is a powerful framework for performing data aggregation operations on collections within MongoDB. The pipeline consists of multiple stages, each of which performs a specific operation on the input documents and passes the results to the next stage. Here are some common stages in the MongoDB aggregation pipeline:

1. match: Filters the documents in the collection to include only those that match the specified criteria. This stage is analogous to the WHERE clause in SQL.

2. project: Reshapes the documents by including, excluding, or renaming fields, as well as by creating new computed fields. It's similar to the SELECT clause in SQL.

3. group: Groups documents by a specified key and performs aggregation operations (such as sum, average, count, etc.) on the grouped data. This stage is similar to the GROUP BY clause in SQL.

4. sort: Orders the documents based on one or more fields in ascending or descending order. It's similar to the ORDER BY clause in SQL.

5. limit: Limits the number of documents passed to the next stage in the pipeline. It's similar to the LIMIT clause in SQL.

6. skip: Skips a specified number of documents and passes the remaining documents to the next stage. It's useful for implementing pagination.

7. unwind: Deconstructs an array field from the input documents and outputs a separate document for each element of the array. It's useful for performing operations on array elements.

8. lookup: Performs a left outer join between documents from the input collection and documents from another collection based on a specified condition. It's similar to the JOIN clause in SQL.

9. facet: Allows for the execution of multiple pipelines within a single aggregation stage. Each sub-pipeline generates its own set of results, which are then combined into a single response.

10. addFields: Adds new fields to the documents. Unlike project, addFields adds new fields to all documents, even if they are not explicitly selected.

11. replaceRoot: Replaces the entire document with a new document. It's useful for reshaping documents and promoting nested fields to the top level.

12. redact: Allows for the implementation of data access control policies by selectively hiding or exposing fields in documents based on specified conditions.

These are just some of the most commonly used stages in the MongoDB aggregation pipeline. MongoDB provides a rich set of aggregation operators and stages, allowing for complex data transformation and analysis tasks to be performed directly within the database.