Explain aggregation in MongoDB with an example.

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Aggregation in MongoDB is a process used to process and transform data from multiple documents in a collection and return computed results. It is similar to SQL’s GROUP BY and JOIN operations but much more powerful for complex data processing. Aggregation pipelines allow data to flow through multiple stages, each performing an operation like filtering, grouping, projecting, sorting, or computing values.

Key Points:

• Aggregation works on collections of documents.

• The most common way to perform aggregation is using the aggregation pipeline, represented as an array of stages.

• Each stage transforms the documents and passes the result to the next stage.

Example Scenario:
Imagine a sales collection storing sales transactions:

{ "_id": 1, "product": "Laptop", "quantity": 5, "price": 1000 }
{ "_id": 2, "product": "Phone", "quantity": 10, "price": 500 }
{ "_id": 3, "product": "Laptop", "quantity": 3, "price": 1000 }

You want to calculate the total quantity sold per product. Aggregation can do this using:

1. $group stage to group documents by product.

2. $sum operator to calculate total quantity.

The result would be:

{ "_id": "Laptop", "totalQuantity": 8 }
{ "_id": "Phone", "totalQuantity": 10 }

Other Common Aggregation Stages:

• $match → Filters documents (like WHERE in SQL)

• $project → Shapes the output fields

• $sort → Orders the results

• $limit / $skip → Pagination

• $lookup → Performs joins with other collections

Aggregation in MongoDB is very flexible and allows complex analytics without moving data to another system.

Read More :

What are indexes in MongoDB, and why are they important?

What is the difference between findOne() and find() in MongoDB?

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