One-to-one embedding pattern in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to embed the address inside the user document.

MongoDB

db.users.insertOne({ name: "Alice", address: [1] })

Drag options to blanks, or click blank then click option'

A{ street: "123 Main St", city: "Springfield" }

B[ "123 Main St", "Springfield" ]

C"123 Main St, Springfield"

DObjectId("507f1f77bcf86cd799439011")

Attempts:

3 left

💡 Hint

Common Mistakes

Using an array instead of an object for the address.

Using a string instead of an embedded document.

Using an ObjectId instead of embedding the address.

The address should be embedded as a subdocument (an object) inside the user document for one-to-one embedding.

2fill in blank

medium

Complete the query to find users living in 'Springfield'.

MongoDB

db.users.find({ "address.[1]": "Springfield" })

Drag options to blanks, or click blank then click option'

Astreet

Bcity

Czipcode

Dstate

Attempts:

3 left

💡 Hint

Common Mistakes

Querying 'address.street' instead of 'address.city'.

Querying 'address.zipcode' when it doesn't exist.

Using 'address' without dot notation.

To query embedded documents, use dot notation. Here, 'address.city' matches the city field inside the embedded address.

3fill in blank

hard

Fix the error in the update to change the street in the embedded address.

MongoDB

db.users.updateOne({ name: "Bob" }, { $set: { "address.[1]": "456 Elm St" } })

Drag options to blanks, or click blank then click option'

Azipcode

Baddress

Cstreet

Dcity

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to update 'address' directly instead of 'address.street'.

Using 'city' or 'zipcode' instead of 'street'.

To update the street inside the embedded address, use the field 'address.street' with dot notation.

4fill in blank

hard

Fill both blanks to create a user document with embedded contact info.

MongoDB

db.users.insertOne({ name: "Carol", contact: { phone: [1], email: [2] } })

Drag options to blanks, or click blank then click option'

A"555-1234"

B"[e-mail]"

C12345

D"notanemail"

Attempts:

3 left

💡 Hint

Common Mistakes

Using numbers without quotes for phone or email.

Using invalid email format.

Phone and email should be strings inside the embedded contact document.

5fill in blank

hard

Fill all three blanks to query users with a specific phone number in embedded contact.

MongoDB

db.users.find({ "contact.[1]": [2], name: [3] })

Drag options to blanks, or click blank then click option'

Aphone

B"555-1234"

C"Carol"

D"555-0000"

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong field name instead of 'phone'.

Not using quotes around string values.

Using a different phone number or name.

Use dot notation to query the phone inside contact. Match the phone number and the user's name as strings.

Practice

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

easy

A. It requires complex joins to retrieve related data.

B. It splits data into multiple collections to reduce document size.

C. It stores related data inside a single document for faster reads.

D. It duplicates data across collections for backup.

Solution

1. Step 1: Understand one-to-one embedding

   One-to-one embedding stores related data inside the same document instead of separate collections.

2. Step 2: Identify the advantage

   This approach simplifies queries and improves read speed by avoiding joins.

3. Final Answer:

   It stores related data inside a single document for faster reads. -> Option C

4. Quick Check:

   Embedding = faster reads [OK]

Hint: Embedding keeps related data together for quick access [OK]

Common Mistakes:

• Thinking embedding splits data into multiple collections
• Assuming embedding requires joins
• Confusing embedding with data duplication

2. Which of the following is the correct way to embed a profile document inside a user document in MongoDB?

easy

A. { _id: 1, name: 'Alice' }, profile: { age: 30, city: 'NY' }

B. { _id: 1, name: 'Alice', profile: { age: 30, city: 'NY' } }

C. { _id: 1, name: 'Alice', profile: [ { age: 30, city: 'NY' } ] }

D. { _id: 1, name: 'Alice', profile: 'age:30, city:NY' }

Solution

1. Step 1: Check embedding syntax

   Embedding means nesting a document inside another document as a field with an object value.

2. Step 2: Identify correct JSON structure

   { _id: 1, name: 'Alice', profile: { age: 30, city: 'NY' } } correctly nests the profile as an object inside user. { _id: 1, name: 'Alice' }, profile: { age: 30, city: 'NY' } separates profile outside user. { _id: 1, name: 'Alice', profile: [ { age: 30, city: 'NY' } ] } uses an array unnecessarily. { _id: 1, name: 'Alice', profile: 'age:30, city:NY' } stores profile as a string, not an object.

3. Final Answer:

   { _id: 1, name: 'Alice', profile: { age: 30, city: 'NY' } } -> Option B

4. Quick Check:

   Embedded document = nested object [OK]

Hint: Embed as nested object, not separate or string [OK]

Common Mistakes:

• Placing embedded document outside main document
• Using array instead of object for one-to-one
• Storing embedded data as string

3. Given the document { _id: 1, name: 'Bob', address: { street: 'Main St', city: 'LA' } }, what will be the result of the query db.users.findOne({ _id: 1 })?

medium

A. { _id: 1, name: 'Bob' }

B. null

C. { address: { street: 'Main St', city: 'LA' } }

D. { _id: 1, name: 'Bob', address: { street: 'Main St', city: 'LA' } }

Solution

1. Step 1: Understand findOne query

   The query searches for a document with _id equal to 1 and returns the whole document.

2. Step 2: Check document structure

   The document includes embedded address inside user, so the full document is returned.

3. Final Answer:

   { _id: 1, name: 'Bob', address: { street: 'Main St', city: 'LA' } } -> Option D

4. Quick Check:

   findOne returns full document [OK]

Hint: findOne returns entire matching document including embedded [OK]

Common Mistakes:

• Expecting only top-level fields returned
• Thinking embedded fields are separate documents
• Assuming query returns null if embedded exists

4. You have this document: { _id: 2, name: 'Carol', profile: { age: 25, city: 'Chicago' } }. Which update command correctly changes the city to 'Boston' using one-to-one embedding?

medium

A. db.users.updateOne({ _id: 2 }, { $set: { 'profile.city': 'Boston' } })

B. db.users.updateOne({ _id: 2 }, { $set: { profile: 'Boston' } })

C. db.users.updateOne({ _id: 2 }, { $set: { city: 'Boston' } })

D. db.users.updateOne({ _id: 2 }, { $set: { 'profile[city]': 'Boston' } })

Solution

1. Step 1: Identify correct update syntax for embedded field

   To update a nested field, use dot notation like 'profile.city'.

2. Step 2: Check each option

   db.users.updateOne({ _id: 2 }, { $set: { 'profile.city': 'Boston' } }) uses correct dot notation. db.users.updateOne({ _id: 2 }, { $set: { profile: 'Boston' } }) replaces entire profile with string. db.users.updateOne({ _id: 2 }, { $set: { city: 'Boston' } }) tries to set city at top level, which doesn't exist. db.users.updateOne({ _id: 2 }, { $set: { 'profile[city]': 'Boston' } }) uses invalid bracket notation.

3. Final Answer:

   db.users.updateOne({ _id: 2 }, { $set: { 'profile.city': 'Boston' } }) -> Option A

4. Quick Check:

   Use dot notation to update embedded fields [OK]

Hint: Use dot notation to update embedded fields [OK]

Common Mistakes:

• Replacing whole embedded document instead of one field
• Using incorrect field path without dot notation
• Using invalid bracket notation in update

5. You want to design a MongoDB schema for users and their passports using one-to-one embedding. Which design is best and why?

hard

A. Embed passport details inside user document because passports are small and tightly linked.

B. Store passports in a separate collection and reference user IDs to avoid large documents.

C. Duplicate passport data in both user and passport collections for faster writes.

D. Store passport as a string field inside user document to simplify queries.

Solution

1. Step 1: Analyze data relationship and size

   Passports are small and tightly connected to users, perfect for embedding.

2. Step 2: Choose embedding benefits

   Embedding keeps related data together, simplifies queries, and improves read speed.

3. Step 3: Evaluate other options

   Store passports in a separate collection and reference user IDs to avoid large documents adds complexity with references. Duplicate passport data in both user and passport collections for faster writes duplicates data causing inconsistency. Store passport as a string field inside user document to simplify queries stores data as string losing structure.

4. Final Answer:

   Embed passport details inside user document because passports are small and tightly linked. -> Option A

5. Quick Check:

   Small, tightly linked data = embed [OK]

Hint: Embed small, tightly linked data for simplicity and speed [OK]

Common Mistakes:

• Choosing references for small one-to-one data
• Duplicating data causing inconsistency
• Storing structured data as plain string