Why the paradigm shift matters in MongoDB - See It in Action

Why the paradigm shift matters

📖 Scenario: You are helping a small bookstore switch from a traditional paper catalog to a modern database system using MongoDB. This will help the store manage books and sales more easily and quickly.

🎯 Goal: Build a simple MongoDB collection to store book information, add a configuration for filtering books by price, query the collection to find affordable books, and finalize the setup for easy future updates.

📋 What You'll Learn

Create a MongoDB collection named books with exactly three book documents

Add a variable maxPrice to set the maximum price for affordable books

Write a query to find all books with a price less than or equal to maxPrice

Add an index on the price field to optimize queries

💡 Why This Matters

🌍 Real World

Bookstores and many businesses use databases like MongoDB to store and quickly find information about products, customers, and sales.

💼 Career

Knowing how to create collections, query data, and optimize with indexes is essential for database administrators and developers working with NoSQL databases.

1

DATA SETUP: Create the books collection with three books

Create a MongoDB collection called books and insert exactly these three documents: { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10 }, { title: "1984", author: "George Orwell", price: 15 }, and { title: "To Kill a Mockingbird", author: "Harper Lee", price: 12 }.

MongoDB

// Insert the three book documents into the books collection
// Your code here

Need a hint?

Use db.books.insertMany([...]) with the exact book documents inside the array.

2

CONFIGURATION: Define maxPrice to filter affordable books

Create a variable called maxPrice and set it to 12 to represent the maximum price for affordable books.

MongoDB

db.books.insertMany([
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10 },
  { title: "1984", author: "George Orwell", price: 15 },
  { title: "To Kill a Mockingbird", author: "Harper Lee", price: 12 }
])

// Define maxPrice variable
// Your code here

Need a hint?

Use const maxPrice = 12 to create the variable.

3

CORE LOGIC: Query books with price less than or equal to maxPrice

Write a MongoDB query using db.books.find() to find all books where the price is less than or equal to the variable maxPrice.

MongoDB

db.books.insertMany([
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10 },
  { title: "1984", author: "George Orwell", price: 15 },
  { title: "To Kill a Mockingbird", author: "Harper Lee", price: 12 }
])

const maxPrice = 12;

// Query books with price <= maxPrice
// Your code here

Need a hint?

Use db.books.find({ price: { $lte: maxPrice } }) to get books priced at or below maxPrice.

4

COMPLETION: Add an index on the price field

Create an index on the price field in the books collection using db.books.createIndex() to speed up price queries.

MongoDB

db.books.insertMany([
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10 },
  { title: "1984", author: "George Orwell", price: 15 },
  { title: "To Kill a Mockingbird", author: "Harper Lee", price: 12 }
])

const maxPrice = 12;

const affordableBooks = db.books.find({ price: { $lte: maxPrice } })

// Create an index on price field
// Your code here

Need a hint?

Use db.books.createIndex({ price: 1 }) to create an ascending index on the price field.