What is aggregation in MongoDB?

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Aggregation in MongoDB is a powerful framework used to process and transform large amounts of data within collections. Instead of just fetching documents, aggregation allows you to analyze, filter, group, and reshape data—similar to SQL’s GROUP BY and aggregate functions like COUNT, SUM, AVG, etc.

🔹 What is Aggregation?

• It’s the process of taking input documents and applying operations (called stages) to produce computed results.

• Each stage in the aggregation pipeline transforms the documents and passes them to the next stage.

• This enables complex queries such as filtering, grouping, sorting, and joining data across collections.

🔹 Why is Aggregation Used?

1. Data Summarization:
   Example – Count total orders, calculate average salaries, or find max/min values.

2. Grouping Data:
   Combine documents by a specific field (like grouping sales by region).

3. Data Transformation:
   Reshape documents by adding new computed fields, projecting specific fields, or restructuring arrays.

4. Filtering & Sorting:
   Apply conditions to select subsets of data and order the results.

5. Joining Collections (lookup):
   Perform operations similar to SQL joins by combining data from multiple collections.

🔹 How it Works (Pipeline Concept)

• The aggregation pipeline is a sequence of stages.

• Common stages include:

  • $match → filter documents (like SQL WHERE).

  • $group → group by fields and apply aggregate functions.

  • $project → select or reshape fields.

  • $sort → order results.

  • $lookup → join with another collection.

✅ In short:
Aggregation in MongoDB is a data processing framework that lets you perform advanced operations like filtering, grouping, sorting, and computing values, turning raw documents into meaningful insights—all within the database.

Read More :

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

Explain the difference between a document and a collection in MongoDB.

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