One-to-many embedding pattern in MongoDB

Introduction

This pattern helps store related data together in one place. It makes reading data faster and simpler.

When you have a main item with many related details, like a blog post with many comments.

When the related data is mostly read together with the main data.

When the number of related items is not too large to slow down the main document.

When you want to keep data organized and easy to access in one document.

Syntax

MongoDB

db.collection.insertOne({
  mainField1: value1,
  mainField2: value2,
  relatedItems: [
    { subField1: valueA, subField2: valueB },
    { subField1: valueC, subField2: valueD }
  ]
})

The related items are stored as an array inside the main document.

This keeps related data together, avoiding separate queries.

Examples

This example stores a blog post with two comments inside the same document.

MongoDB

db.posts.insertOne({
  title: "My First Post",
  author: "Alice",
  comments: [
    { user: "Bob", message: "Nice post!" },
    { user: "Carol", message: "Thanks for sharing." }
  ]
})

This example stores an order with multiple items embedded inside it.

MongoDB

db.orders.insertOne({
  orderId: 12345,
  customer: "John",
  items: [
    { product: "Book", quantity: 2 },
    { product: "Pen", quantity: 5 }
  ]
})

Sample Program

This inserts a library document with a list of books inside it. Then it finds and prints the library with its books.

MongoDB

db.library.insertOne({
  name: "City Library",
  address: "123 Main St",
  books: [
    { title: "1984", author: "George Orwell" },
    { title: "To Kill a Mockingbird", author: "Harper Lee" }
  ]
})

// Query to find the library and its books
const library = db.library.findOne({ name: "City Library" })
printjson(library)

Important Notes

Embedding is good for data that is mostly read together.

If the embedded array grows too large, it can slow down queries and updates.

For very large or growing related data, consider referencing instead of embedding.

Summary

One-to-many embedding stores related data inside a main document.

It makes reading related data faster and simpler.

Best for small to medium related data that is read together.

Practice

1. What is the main advantage of using the one-to-many embedding pattern in MongoDB?

easy

A. It separates related data into different collections for better normalization.

B. It duplicates data across multiple documents to improve write speed.

C. It requires complex joins to retrieve related data.

D. It stores related data inside the main document for faster reads.

Solution

1. Step 1: Understand embedding in MongoDB

   Embedding means storing related data inside the main document instead of separate collections.

2. Step 2: Identify the advantage of embedding

   This approach makes reading related data faster and simpler because all data is in one place.

3. Final Answer:

   It stores related data inside the main document for faster reads. -> Option D

4. Quick Check:

   Embedding = faster reads [OK]

Hint: Embedding means related data inside main document for quick access [OK]

Common Mistakes:

• Confusing embedding with referencing (separate collections)
• Thinking embedding requires joins
• Assuming embedding duplicates data

2. Which of the following is the correct way to embed multiple comments inside a blog post document in MongoDB?

easy

A. { _id: 1, title: 'Post', comments: 'Alice: Nice!, Bob: Great!' }

B. { _id: 1, title: 'Post', comments: { user: 'Alice', text: 'Nice!' }, { user: 'Bob', text: 'Great!' } }

C. { _id: 1, title: 'Post', comments: [{ user: 'Alice', text: 'Nice!' }, { user: 'Bob', text: 'Great!' }] }

D. { _id: 1, title: 'Post', comments: [{ user: 'Alice' }, user: 'Bob', text: 'Great!' ] }

Solution

1. Step 1: Check the structure for embedding multiple comments

   Embedding many comments requires an array of objects inside the main document.

2. Step 2: Identify the correct JSON syntax

   { _id: 1, title: 'Post', comments: [{ user: 'Alice', text: 'Nice!' }, { user: 'Bob', text: 'Great!' }] } correctly uses an array of comment objects inside the comments field.

3. Final Answer:

   { _id: 1, title: 'Post', comments: [{ user: 'Alice', text: 'Nice!' }, { user: 'Bob', text: 'Great!' }] } -> Option C

4. Quick Check:

   Array of objects = correct embedding [OK]

Hint: Embed many items as an array of objects inside the document [OK]

Common Mistakes:

• Using multiple objects without array brackets
• Storing comments as a string instead of objects
• Incorrect JSON syntax with misplaced commas or braces

3. Given the following document in a posts collection:

{ _id: 1, title: 'Hello', comments: [{ user: 'Alice', text: 'Hi' }, { user: 'Bob', text: 'Hello' }] }

What will be the result of the query db.posts.find({ _id: 1 }, { 'comments.user': 1, _id: 0 })?

medium

A. { comments: [{ user: 'Alice' }, { user: 'Bob' }] }

B. { comments: [{ text: 'Hi' }, { text: 'Hello' }] }

C. { _id: 1, comments: [{ user: 'Alice' }, { user: 'Bob' }] }

D. { comments: ['Alice', 'Bob'] }

Solution

1. Step 1: Understand the projection in the query

   The query projects only the comments.user field and excludes _id.

2. Step 2: Determine the output structure

   It returns the comments array with only the user fields inside each comment object.

3. Final Answer:

   { comments: [{ user: 'Alice' }, { user: 'Bob' }] } -> Option A

4. Quick Check:

   Projection of comments.user = array of user objects [OK]

Hint: Projection with dot notation returns array of objects with that field [OK]

Common Mistakes:

• Expecting full comment objects instead of only user fields
• Including _id when excluded in projection
• Getting array of strings instead of objects

4. You have this document:

{ _id: 1, name: 'Store', products: [{ name: 'Pen', price: 1.5 }, { name: 'Pencil', price: 1.0 }] }

Which update query correctly adds a new product { name: 'Eraser', price: 0.5 } to the products array?

medium

A. db.stores.updateOne({ _id: 1 }, { $push: { products: { name: 'Eraser', price: 0.5 } } })

B. db.stores.updateOne({ _id: 1 }, { $addToSet: { products: 'Eraser' } })

C. db.stores.updateOne({ _id: 1 }, { $set: { products: { name: 'Eraser', price: 0.5 } } })

D. db.stores.updateOne({ _id: 1 }, { $push: { products: ['Eraser', 0.5] } })

Solution

1. Step 1: Identify the correct operator to add an object to an array

   The $push operator adds an element to an array field.

2. Step 2: Check the value being pushed

   db.stores.updateOne({ _id: 1 }, { $push: { products: { name: 'Eraser', price: 0.5 } } }) pushes the correct object { name: 'Eraser', price: 0.5 } into the products array.

3. Final Answer:

   db.stores.updateOne({ _id: 1 }, { $push: { products: { name: 'Eraser', price: 0.5 } } }) -> Option A

4. Quick Check:

   $push with object adds to array [OK]

Hint: Use $push with full object to add to embedded array [OK]

Common Mistakes:

• Using $set replaces whole array instead of adding
• Using $addToSet with a string instead of object
• Pushing array instead of object inside array

5. You want to store a user's orders in a single document using one-to-many embedding. Each order has an orderId, date, and a list of items. Which schema design is best to handle up to 100 orders per user efficiently?

hard

A. Separate orders collection with userId reference for each order

B. { _id: userId, name: 'User', orders: [{ orderId, date, items: [{ productId, qty }] }] }

C. { _id: userId, name: 'User', orderIds: [orderId1, orderId2], orders: [] }

D. { _id: userId, name: 'User', orders: { orderId, date, items: [{ productId, qty }] } }

Solution

1. Step 1: Understand embedding for one-to-many with moderate size

   Embedding up to 100 orders inside a user document is reasonable for fast reads.

2. Step 2: Check schema design for correct embedding

   { _id: userId, name: 'User', orders: [{ orderId, date, items: [{ productId, qty }] }] } embeds an array of order objects, each with its own items array, which fits the one-to-many embedding pattern well.

3. Final Answer:

   { _id: userId, name: 'User', orders: [{ orderId, date, items: [{ productId, qty }] }] } -> Option B

4. Quick Check:

   Embed array of orders with nested items for one-to-many [OK]

Hint: Embed arrays of objects for moderate related data size [OK]

Common Mistakes:

• Using object instead of array for multiple orders
• Separating orders into another collection unnecessarily
• Storing only order IDs without details inside user