Why modeling decisions matter in MongoDB - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find all documents in the collection.

MongoDB

db.collection.[1]()

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

Afind

Binsert

Cupdate

Ddelete

Attempts:

3 left

💡 Hint

Common Mistakes

Using insert instead of find will add data, not retrieve it.

Using update or delete will modify or remove data, not retrieve.

The find() method retrieves all documents from a MongoDB collection.

2fill in blank

medium

Complete the code to insert a new document into the collection.

MongoDB

db.collection.[1]({ name: 'Alice', age: 30 })

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

AdeleteOne

Bfind

CinsertOne

DupdateOne

Attempts:

3 left

💡 Hint

Common Mistakes

Using find will not add data.

Using deleteOne or updateOne will remove or change data, not add.

The insertOne() method adds a single new document to the collection.

3fill in blank

hard

Fix the error in the query to update a document's age.

MongoDB

db.collection.updateOne({ name: 'Bob' }, { [1]: { age: 35 } })

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

Aupdate

Bset

C$update

D$set

Attempts:

3 left

💡 Hint

Common Mistakes

Missing the dollar sign causes the update to fail.

Using 'set' without $ is not recognized by MongoDB.

The $set operator updates specific fields in a document.

4fill in blank

hard

Fill both blanks to create a query that finds documents where age is greater than 25.

MongoDB

db.collection.find({ age: { [1]: [2] } })

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

A$gt

B25

C$lt

D30

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lt finds ages less than the number, not greater.

Using 30 instead of 25 changes the filter condition.

The $gt operator means 'greater than'. So this finds documents with age > 25.

5fill in blank

hard

Fill all three blanks to create a query that finds documents with name 'Eve' and age less than 40.

MongoDB

db.collection.find({ name: [1], age: { [2]: [3] } })

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

A'Eve'

B$lt

C40

D'Alice'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong name string changes the filter.

Using $gt instead of $lt reverses the age condition.

This query finds documents where name is 'Eve' and age is less than 40 using $lt.

Practice

1. Why is choosing the right data model important in MongoDB?

easy

A. It decides the font used in the database shell

B. It changes the color of the database interface

C. It affects how fast and easy your app can access data

D. It controls the network speed of your internet

Solution

1. Step 1: Understand data model impact

   The data model determines how data is stored and accessed, affecting speed and ease of use.

2. Step 2: Eliminate unrelated options

   Options about colors, fonts, or internet speed do not relate to data modeling.

3. Final Answer:

   It affects how fast and easy your app can access data -> Option C

4. Quick Check:

   Data model affects app speed and ease [OK]

Hint: Data model = app speed and ease [OK]

Common Mistakes:

• Confusing UI features with data modeling
• Thinking data model affects internet speed
• Ignoring performance impact of modeling

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

easy

A. { name: 'Alice', address: { city: 'NY', zip: '10001' } }

B. { name: 'Alice', address: ['NY', '10001'] }

C. { name: 'Alice', address: 'NY, 10001' }

D. { name: 'Alice', address: ObjectId('abc123') }

Solution

1. Step 1: Identify embedding format

   Embedding means placing a sub-document inside the main document as a nested object.

2. Step 2: Check options for nested object

   { name: 'Alice', address: { city: 'NY', zip: '10001' } } uses a nested object for address, which is correct embedding syntax.

3. Final Answer:

   { name: 'Alice', address: { city: 'NY', zip: '10001' } } -> Option A

4. Quick Check:

   Embedding uses nested objects [OK]

Hint: Embed with nested objects, not arrays or strings [OK]

Common Mistakes:

• Using array instead of object for embedding
• Storing address as a plain string
• Referencing with ObjectId instead of embedding

3. Given the following MongoDB documents, what will be the result of querying for users with embedded orders having product 'Book'?

{ _id: 1, name: 'John', orders: [{ product: 'Book', qty: 2 }, { product: 'Pen', qty: 5 }] }

{ _id: 2, name: 'Jane', orders: [{ product: 'Notebook', qty: 1 }] }

db.users.find({ 'orders.product': 'Book' })

medium

A. [{ _id: 1, name: 'John', orders: [...] }]

B. [{ _id: 2, name: 'Jane', orders: [...] }]

C. []

D. Error: Invalid query

Solution

1. Step 1: Understand query condition

   The query looks for documents where any order's product is 'Book'.

2. Step 2: Match documents with 'Book' product

   Only John has an order with product 'Book', so only his document matches.

3. Final Answer:

   [{ _id: 1, name: 'John', orders: [...] }] -> Option A

4. Quick Check:

   Query matches embedded product 'Book' [OK]

Hint: Query embedded fields with dot notation [OK]

Common Mistakes:

• Assuming query matches documents without 'Book'
• Expecting syntax error from dot notation
• Confusing array matching with string matching

4. You have a user document with an embedded array of comments. You try to update a comment's text but the update does not work. Which is the likely error?

db.users.updateOne(
  { _id: 1, comments.id: 5 },
  { $set: { 'comments.text': 'Updated' } }
)

medium

A. Using updateOne instead of updateMany

B. Syntax error in query filter

C. Incorrect collection name

D. Missing $ positional operator to target the correct array element

Solution

1. Step 1: Analyze update query

   The filter matches the comment with id 5, but the update sets 'comments.text' without specifying which array element.

2. Step 2: Identify missing positional operator

   To update a specific array element, the $ positional operator is needed in the update path: 'comments.$.text'.

3. Final Answer:

   Missing $ positional operator to target the correct array element -> Option D

4. Quick Check:

   Use $ to update matched array element [OK]

Hint: Use $ to update specific array item [OK]

Common Mistakes:

• Forgetting $ in update path for arrays
• Changing updateOne to updateMany unnecessarily
• Assuming collection name or filter syntax is wrong

5. You want to model a blog app where each post has many comments. Comments can be very large and users often read posts without comments. Which modeling choice is best and why?

hard

A. Embed comments inside posts to get all data in one query

B. Store comments in a separate collection and reference posts to avoid large post documents

C. Store comments as strings inside posts to save space

D. Duplicate comments in both posts and a separate collection

Solution

1. Step 1: Analyze data size and access pattern

   Comments are large and often not needed when reading posts, so embedding would make posts heavy.

2. Step 2: Choose referencing for efficiency

   Referencing comments separately keeps post documents small and loads comments only when needed.

3. Final Answer:

   Store comments in a separate collection and reference posts to avoid large post documents -> Option B

4. Quick Check:

   Large optional data = use referencing [OK]

Hint: Large optional data? Use referencing [OK]

Common Mistakes:

• Embedding large optional data causing slow reads
• Storing comments as strings losing structure
• Duplicating data causing inconsistency