Why querying nested data matters in MongoDB - See It in Action

Why querying nested data matters

📖 Scenario: You work at a company that stores customer orders in a MongoDB database. Each order document contains nested information about the customer and the items they purchased. You want to learn how to query this nested data to find specific details.

🎯 Goal: Build a MongoDB query step-by-step to find orders where a specific item was purchased and extract nested customer information.

📋 What You'll Learn

Create a collection called orders with sample nested documents

Add a filter variable to specify the item name to search for

Write a query to find orders containing that item in the nested items array

Project the customer's name and the matching item details in the query result

💡 Why This Matters

🌍 Real World

Many real-world databases store complex nested data like orders with customers and items. Being able to query inside nested arrays is essential to find relevant information quickly.

💼 Career

Database developers and analysts often need to write queries that access nested data structures to generate reports, filter data, or build APIs.

1

DATA SETUP: Create the orders collection with nested documents

Create a variable called orders and assign it an array with these two documents exactly: { _id: 1, customer: { name: "Alice", age: 30 }, items: [ { name: "Pen", qty: 3 }, { name: "Notebook", qty: 1 } ] } and { _id: 2, customer: { name: "Bob", age: 25 }, items: [ { name: "Pencil", qty: 2 }, { name: "Pen", qty: 5 } ] }

MongoDB

# Create the orders array with two nested documents
# Your code here

Need a hint?

Define orders as a list with two dictionaries. Each dictionary has _id, customer (which is another dictionary), and items (which is a list of dictionaries).

2

CONFIGURATION: Define the item name to search for

Create a variable called search_item and set it to the string "Pen".

MongoDB

orders = [
    {"_id": 1, "customer": {"name": "Alice", "age": 30}, "items": [{"name": "Pen", "qty": 3}, {"name": "Notebook", "qty": 1}]},
    {"_id": 2, "customer": {"name": "Bob", "age": 25}, "items": [{"name": "Pencil", "qty": 2}, {"name": "Pen", "qty": 5}]}
]
# Define the search_item variable
# Your code here

Need a hint?

Just create a variable search_item and assign it the string "Pen".

3

CORE LOGIC: Write a MongoDB-style query to find orders with the search item

Create a variable called matching_orders and assign it a list comprehension that filters orders for documents where any item in items has name equal to search_item. Use for order in orders and any(item['name'] == search_item for item in order['items']) in the condition.

MongoDB

orders = [
    {"_id": 1, "customer": {"name": "Alice", "age": 30}, "items": [{"name": "Pen", "qty": 3}, {"name": "Notebook", "qty": 1}]},
    {"_id": 2, "customer": {"name": "Bob", "age": 25}, "items": [{"name": "Pencil", "qty": 2}, {"name": "Pen", "qty": 5}]}
]
search_item = "Pen"
# Filter orders containing the search_item
# Your code here

Need a hint?

Use a list comprehension with any() to check if any item in order['items'] has the name matching search_item.

4

COMPLETION: Project customer name and matching item details

Create a variable called result and assign it a list comprehension that for each order in matching_orders creates a dictionary with keys customer_name set to order['customer']['name'] and items set to a list of items from order['items'] where item['name'] == search_item.

MongoDB

orders = [
    {"_id": 1, "customer": {"name": "Alice", "age": 30}, "items": [{"name": "Pen", "qty": 3}, {"name": "Notebook", "qty": 1}]},
    {"_id": 2, "customer": {"name": "Bob", "age": 25}, "items": [{"name": "Pencil", "qty": 2}, {"name": "Pen", "qty": 5}]}
]
search_item = "Pen"
matching_orders = [order for order in orders if any(item['name'] == search_item for item in order['items'])]
# Create result with customer_name and filtered items
# Your code here

Need a hint?

Use a list comprehension over matching_orders. For each order, create a dictionary with customer_name and a filtered list of items matching search_item.