Using Aggregations in MongoDB

 Using aggregations in MongoDB allows you to process and transform data from your collections through a pipeline of operations. Aggregation is commonly used for tasks such as grouping, filtering, calculating averages/sums, or transforming documents.

Here’s a breakdown of how to use aggregation pipelines in MongoDB.

🔧 Basic Syntax

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db.collection.aggregate([

  { stage1 },

  { stage2 },

  ...

])

Each stage in the array performs a transformation on the data.

📘 Common Aggregation Stages

Stage Description

$match Filters documents (like a find query)

$group Groups documents by a field and performs aggregations (e.g., sum, avg)

$project Includes, excludes, or reshapes document fields

$sort Sorts documents

$limit Limits the number of documents

$skip Skips a specified number of documents

$lookup Performs a left outer join with another collection

$unwind Deconstructs an array field to output multiple documents

$addFields Adds new fields or modifies existing ones

🧮 Example Aggregation: Group by Category and Count

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db.products.aggregate([

  { $group: {

      _id: "$category",

      total: { $sum: 1 }

  }}

])

This groups documents in the products collection by the category field and counts how many products are in each category.

📊 Example: Average Price by Category

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db.products.aggregate([

  { $group: {

      _id: "$category",

      avgPrice: { $avg: "$price" }

  }}

])

🔗 Example with $match and $group

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db.orders.aggregate([

  { $match: { status: "shipped" } },

  { $group: {

      _id: "$customerId",

      totalSpent: { $sum: "$amount" }

  }}

])

This filters orders with status: "shipped" and then groups them by customerId, summing the amount each customer spent.

🪄 Example with $lookup (Join)

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db.orders.aggregate([

  {

    $lookup: {

      from: "customers",

      localField: "customerId",

      foreignField: "_id",

      as: "customerInfo"

    }

  }

])

This joins orders with customers based on the customerId field.

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