$facet for multiple pipelines in MongoDB - Mini Project: Build & Apply

Using $facet for Multiple Pipelines in MongoDB Aggregation

📖 Scenario: You work at a bookstore that keeps its sales data in a MongoDB collection called sales. Each document records a book sale with fields like title, genre, price, and copies_sold.The manager wants to see two things at once: the total revenue per genre and the top 3 best-selling books overall.

🎯 Goal: Build a MongoDB aggregation query using $facet to run two pipelines simultaneously:One pipeline calculates total revenue per genre.The other pipeline finds the top 3 best-selling books overall.

📋 What You'll Learn

Create a sales collection with exact documents provided.

Add a variable minCopies set to 5 to filter popular books.

Write an aggregation query using $facet with two pipelines: revenueByGenre and topBooks.

In revenueByGenre, group by genre and sum total revenue (price * copies_sold).

In topBooks, filter books with copies_sold >= minCopies, sort by copies_sold descending, and limit to 3.

Complete the aggregation query with the db.sales.aggregate() call.

💡 Why This Matters

🌍 Real World

Bookstores and retail businesses often need to analyze sales data in multiple ways simultaneously, such as revenue by category and best sellers.

💼 Career

Understanding $facet helps database developers and analysts write efficient queries that return multiple summaries in one request, saving time and resources.

1

Create the sales collection with sample data

Create a variable called sales and assign it an array of these exact documents: {"title": "Book A", "genre": "Fiction", "price": 10, "copies_sold": 4}, {"title": "Book B", "genre": "Fiction", "price": 15, "copies_sold": 7}, {"title": "Book C", "genre": "Non-Fiction", "price": 20, "copies_sold": 5}, {"title": "Book D", "genre": "Non-Fiction", "price": 25, "copies_sold": 3}, {"title": "Book E", "genre": "Fiction", "price": 8, "copies_sold": 10}

MongoDB

sales = [
    # Your code here
]

Need a hint?

Create a list named sales with the exact book documents as shown.

2

Add a variable minCopies to filter popular books

Create a variable called minCopies and set it to 5.

MongoDB

sales = [
    {"title": "Book A", "genre": "Fiction", "price": 10, "copies_sold": 4},
    {"title": "Book B", "genre": "Fiction", "price": 15, "copies_sold": 7},
    {"title": "Book C", "genre": "Non-Fiction", "price": 20, "copies_sold": 5},
    {"title": "Book D", "genre": "Non-Fiction", "price": 25, "copies_sold": 3},
    {"title": "Book E", "genre": "Fiction", "price": 8, "copies_sold": 10}
]

# Your code here

Need a hint?

Just create a variable named minCopies and assign 5 to it.

3

Write the aggregation query using $facet with two pipelines

Create a variable called aggregationQuery and assign it the MongoDB aggregation pipeline array that uses $facet with two pipelines: revenueByGenre and topBooks. In revenueByGenre, group by genre and sum total revenue as totalRevenue (calculate price * copies_sold). In topBooks, filter documents where copies_sold is greater than or equal to minCopies, sort by copies_sold descending, and limit to 3.

MongoDB

sales = [
    {"title": "Book A", "genre": "Fiction", "price": 10, "copies_sold": 4},
    {"title": "Book B", "genre": "Fiction", "price": 15, "copies_sold": 7},
    {"title": "Book C", "genre": "Non-Fiction", "price": 20, "copies_sold": 5},
    {"title": "Book D", "genre": "Non-Fiction", "price": 25, "copies_sold": 3},
    {"title": "Book E", "genre": "Fiction", "price": 8, "copies_sold": 10}
]

minCopies = 5

# Your code here

Need a hint?

Use $facet with two pipelines named revenueByGenre and topBooks as described.

4

Complete the aggregation call with db.sales.aggregate()

Write a line of code that assigns to a variable called result the call to db.sales.aggregate() passing the aggregationQuery variable.

MongoDB

sales = [
    {"title": "Book A", "genre": "Fiction", "price": 10, "copies_sold": 4},
    {"title": "Book B", "genre": "Fiction", "price": 15, "copies_sold": 7},
    {"title": "Book C", "genre": "Non-Fiction", "price": 20, "copies_sold": 5},
    {"title": "Book D", "genre": "Non-Fiction", "price": 25, "copies_sold": 3},
    {"title": "Book E", "genre": "Fiction", "price": 8, "copies_sold": 10}
]

minCopies = 5

aggregationQuery = [
    {
        "$facet": {
            "revenueByGenre": [
                {
                    "$group": {
                        "_id": "$genre",
                        "totalRevenue": { "$sum": { "$multiply": ["$price", "$copies_sold"] } }
                    }
                }
            ],
            "topBooks": [
                { "$match": { "copies_sold": { "$gte": minCopies } } },
                { "$sort": { "copies_sold": -1 } },
                { "$limit": 3 }
            ]
        }
    }
]

# Your code here

Need a hint?

Call db.sales.aggregate() with aggregationQuery and assign to result.