Embedded documents (nested objects) in MongoDB - Mini Project: Build & Apply

Create and Query Embedded Documents in MongoDB

📖 Scenario: You are building a small database for a bookstore. Each book has details like title, author, and price. Additionally, each book has an embedded document for the publisher information, which includes the publisher's name and address.

🎯 Goal: Create a MongoDB collection with embedded documents for publisher details. Then, write a query to find all books published by a specific publisher.

📋 What You'll Learn

Create a collection called books with documents containing title, author, price, and an embedded document publisher with name and address fields.

Add a variable targetPublisher to store the publisher name to search for.

Write a query to find all books where the embedded publisher.name matches targetPublisher.

Complete the query by projecting only the title and author fields in the output.

💡 Why This Matters

🌍 Real World

Many real-world databases store related information inside embedded documents to keep data organized and easy to access, like storing publisher details inside book records.

💼 Career

Understanding embedded documents and querying nested fields is essential for working with MongoDB and other NoSQL databases, a common skill in backend development and data engineering.

1

Create the books collection with embedded publisher documents

Create a variable called books and assign it an array with these two documents exactly:
1. { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10.99, publisher: { name: "Scribner", address: "New York" } }
2. { title: "1984", author: "George Orwell", price: 8.99, publisher: { name: "Secker & Warburg", address: "London" } }

MongoDB

# Create the books array with embedded publisher documents
# Your code here

Hint

Use an array of objects. Each book object has a publisher object inside it.

2

Add a variable to hold the target publisher name

Create a variable called targetPublisher and set it to the string "Scribner".

MongoDB

const books = [
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10.99, publisher: { name: "Scribner", address: "New York" } },
  { title: "1984", author: "George Orwell", price: 8.99, publisher: { name: "Secker & Warburg", address: "London" } }
];

// Create targetPublisher variable
# Your code here

Hint

Use const targetPublisher = "Scribner"; to store the publisher name.

3

Write a query to find books by the target publisher

Write a variable called query that uses books.filter() to find all books where book.publisher.name equals targetPublisher.

MongoDB

const books = [
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10.99, publisher: { name: "Scribner", address: "New York" } },
  { title: "1984", author: "George Orwell", price: 8.99, publisher: { name: "Secker & Warburg", address: "London" } }
];

const targetPublisher = "Scribner";

// Filter books by publisher name
# Your code here

Hint

Use filter with a function checking book.publisher.name === targetPublisher.

4

Project only the title and author fields in the query result

Create a variable called result that maps over query to return objects with only title and author fields.

MongoDB

const books = [
  { title: "The Great Gatsby", author: "F. Scott Fitzgerald", price: 10.99, publisher: { name: "Scribner", address: "New York" } },
  { title: "1984", author: "George Orwell", price: 8.99, publisher: { name: "Secker & Warburg", address: "London" } }
];

const targetPublisher = "Scribner";

const query = books.filter(book => book.publisher.name === targetPublisher);

// Map query to only title and author
# Your code here

Hint

Use map to create new objects with only title and author.

Practice

1. What is an embedded document in MongoDB?

easy

A. A document stored inside another document as a nested object

B. A separate collection linked by an ID

C. A document stored in a different database

D. A document stored as a file on disk

Solution

1. Step 1: Understand MongoDB document structure

   MongoDB stores data in documents, which can contain nested objects called embedded documents.

2. Step 2: Identify embedded document meaning

   An embedded document is a document inside another document, not a separate collection or file.

3. Final Answer:

   A document stored inside another document as a nested object -> Option A

4. Quick Check:

   Embedded document = nested object inside document [OK]

Hint: Think of a box inside another box holding related info [OK]

Common Mistakes:

• Confusing embedded documents with references
• Thinking embedded documents are separate collections
• Assuming embedded documents are stored outside the database

2. Which of the following is the correct way to insert an embedded document in MongoDB?

easy

A. db.collection.insertOne([{name: 'Alice'}, {address: {city: 'NY', zip: 10001}}])

B. db.collection.insertOne({name: 'Alice'}, {address: {city: 'NY', zip: 10001}})

C. db.collection.insertOne(name: 'Alice', address: {city: 'NY', zip: 10001})

D. db.collection.insertOne({name: 'Alice', address: {city: 'NY', zip: 10001}})

Solution

1. Step 1: Review MongoDB insertOne syntax

   insertOne takes a single document object with fields and values, including nested objects.

2. Step 2: Check each option's syntax

   db.collection.insertOne({name: 'Alice', address: {city: 'NY', zip: 10001}}) correctly nests the address object inside the main document. Others have syntax errors or wrong structure.

3. Final Answer:

   db.collection.insertOne({name: 'Alice', address: {city: 'NY', zip: 10001}}) -> Option D

4. Quick Check:

   Nested object inside one document = correct insert [OK]

Hint: Use one object with nested braces for embedded docs [OK]

Common Mistakes:

• Passing multiple objects instead of one
• Missing curly braces around nested document
• Using array instead of object for embedded document

3. Given the document { name: 'Bob', contact: { email: '[e-mail]', phone: '1234' } }, what will the query db.users.find({ 'contact.email': '[e-mail]' }) return?

medium

A. No documents, because nested fields can't be queried

B. All documents where contact.email equals '[e-mail]'

C. Documents where name equals '[e-mail]'

D. Documents where contact is exactly '[e-mail]'

Solution

1. Step 1: Understand dot notation in queries

   MongoDB uses dot notation to query fields inside embedded documents.

2. Step 2: Analyze the query

   The query looks for documents where the embedded field contact.email matches the given value.

3. Final Answer:

   All documents where contact.email equals '[e-mail]' -> Option B

4. Quick Check:

   Dot notation queries embedded fields correctly [OK]

Hint: Use dot notation to access nested fields in queries [OK]

Common Mistakes:

• Trying to match entire embedded document instead of field
• Using wrong field name without dot notation
• Assuming nested fields can't be queried

4. What is wrong with this update query to change the city in an embedded address document?
db.users.updateOne({name: 'Eve'}, {address.city: 'LA'})

medium

A. The field name should not use dot notation

B. The query filter is incorrect

C. The update document is missing the $set operator

D. updateOne cannot update embedded documents

Solution

1. Step 1: Recall updateOne syntax

   updateOne requires an update operator like $set to specify fields to change.

2. Step 2: Identify missing $set operator

   The query tries to update address.city directly without $set, which is invalid syntax.

3. Final Answer:

   The update document is missing the $set operator -> Option C

4. Quick Check:

   Updates need $set for field changes [OK]

Hint: Always use $set to update fields, including nested ones [OK]

Common Mistakes:

• Forgetting $set in update document
• Using dot notation incorrectly in filter
• Thinking updateOne can't change nested fields

5. You want to store multiple phone numbers inside a user's document using embedded documents. Which schema design is best?

hard

A. { name: 'Sam', phones: [{ type: 'home', number: '111' }, { type: 'work', number: '222' }] }

B. { name: 'Sam', phone1: '111', phone2: '222' }

C. { name: 'Sam', phones: { home: '111', work: '222' } }

D. { name: 'Sam', phones: '111,222' }

Solution

1. Step 1: Understand storing multiple embedded documents

   To store multiple related items, use an array of embedded documents for flexibility and clarity.

2. Step 2: Compare options

   { name: 'Sam', phones: [{ type: 'home', number: '111' }, { type: 'work', number: '222' }] } uses an array of objects with type and number, which is clear and scalable. Others are less flexible or harder to query.

3. Final Answer:

   { name: 'Sam', phones: [{ type: 'home', number: '111' }, { type: 'work', number: '222' }] } -> Option A

4. Quick Check:

   Array of embedded docs best for multiple related items [OK]

Hint: Use arrays of objects for multiple related embedded documents [OK]

Common Mistakes:

• Storing multiple values as comma-separated string
• Using separate fields for each phone number
• Using a single object without array for multiple items