How MongoDB stores data as documents - Practice Exercises

Challenge - 5 Problems

❓ query_result

intermediate

What does this MongoDB document look like after insertion?

Consider the following MongoDB insert operation:

db.users.insertOne({ name: "Alice", age: 30, hobbies: ["reading", "hiking"] })

What will the stored document look like when retrieved?

MongoDB

db.users.findOne({ name: "Alice" })

A { "name": "Alice", "age": "30", "hobbies": "reading, hiking" }

B { "_id": ObjectId(...), "name": "Alice", "age": 30, "hobbies": ["reading", "hiking"] }

C { "_id": ObjectId(...), "name": "Alice", "age": "30", "hobbies": ["reading", "hiking"] }

D { "name": "Alice", "age": 30, "hobbies": ["reading", "hiking"] }

💡 Hint

Remember MongoDB automatically adds an _id field and preserves data types.

MongoDB stores documents with an automatic _id field of type ObjectId unless specified. The age remains a number, and hobbies is stored as an array.

🧠 Conceptual

intermediate

How does MongoDB store nested data?

Which of the following best describes how MongoDB stores nested data inside documents?

A As embedded documents within the main document using key-value pairs.

B As flat JSON strings inside a single field.

C As separate tables linked by foreign keys.

D As separate files on disk referenced by the document.

💡 Hint

Think about how JSON objects can contain other objects.

MongoDB stores nested data as embedded documents inside the main document, allowing hierarchical data representation.

📝 Syntax

advanced

Which MongoDB query correctly updates a nested field?

Given a document structure:

{ name: "Bob", address: { city: "NY", zip: 10001 } }

Which query correctly updates the city to "LA"?

A db.collection.updateOne({ name: "Bob" }, { $set: { address: { city: "LA" } } })

B db.collection.updateOne({ name: "Bob" }, { city: "LA" })

C db.collection.updateOne({ name: "Bob" }, { $set: { "address.city": "LA" } })

D db.collection.updateOne({ name: "Bob" }, { $update: { "address.city": "LA" } })

💡 Hint

Use dot notation with $set to update nested fields.

Option C uses the correct $set operator with dot notation to update the nested city field without overwriting the entire address.

❓ optimization

advanced

How to optimize queries on nested document fields?

You have a collection with documents containing nested fields like:

{ user: { name: "Eve", age: 25 }, status: "active" }

Which approach best improves query performance filtering by user name?

A Use a text index on the entire document.

B Create an index on the status field only.

C Flatten the document to remove nesting.

D Create an index on the nested field user.name.

💡 Hint

Indexes on fields used in queries speed up searches.

Creating an index on user.name allows MongoDB to quickly find documents by that nested field without scanning all documents.

🔧 Debug

expert

Why does this MongoDB query return no results?

Given documents:

{ name: "Sam", details: { age: 40, city: "Boston" } }

Which query will NOT return this document?

Options:
A) db.collection.find({ "details.age": 40 })
B) db.collection.find({ details: { age: 40, city: "Boston" } })
C) db.collection.find({ details: { city: "Boston", age: 40 } })
D) db.collection.find({ "details.city": "Boston" })

A Returns no documents because field order in embedded document matters.

B Returns the document because it matches the nested city field.

C Returns the document because exact object match requires field order.

D Returns the document because it matches the nested age field.

💡 Hint

Exact matches on embedded documents require the same field order.

MongoDB matches embedded documents exactly including field order. Option A has different order and returns no results. Option A matches the document and returns the document. Therefore, option A is correct as NOT returning results.

Practice

1. What is the basic unit of data storage in MongoDB?

easy

A. A document

B. A table

C. A row

D. A column

Solution

1. Step 1: Understand MongoDB data structure

   MongoDB stores data as documents, not tables or rows like traditional databases.

2. Step 2: Identify the correct data unit

   The document is the flexible data unit that holds fields and values in MongoDB.

3. Final Answer:

   A document -> Option A

4. Quick Check:

   MongoDB data unit = document [OK]

Hint: Remember: MongoDB uses documents, not tables or rows [OK]

Common Mistakes:

• Confusing documents with tables from SQL
• Thinking rows or columns are used in MongoDB
• Assuming collections are the basic unit

2. Which of the following is the correct way to represent a MongoDB document with a field name and value Alice?

easy

A. [ 'name': 'Alice' ]

B. { 'name' = 'Alice' }

C. { name: 'Alice' }

D. ( name: 'Alice' )

Solution

1. Step 1: Recall MongoDB document syntax

   MongoDB documents use JSON-like syntax with curly braces and colon to assign values.

2. Step 2: Check each option's syntax

   { name: 'Alice' } uses correct JSON-like syntax: { name: 'Alice' }. Others use invalid symbols or brackets.

3. Final Answer:

   { name: 'Alice' } -> Option C

4. Quick Check:

   Correct MongoDB document = JSON-like with colons [OK]

Hint: Use curly braces and colons for fields in MongoDB documents [OK]

Common Mistakes:

• Using equal signs instead of colons
• Using square or round brackets instead of curly braces
• Putting field names in quotes incorrectly

3. Given the MongoDB document: { name: 'Bob', age: 30, hobbies: ['reading', 'swimming'] }, what is the value of the hobbies field?

medium

A. A string 'reading, swimming'

B. A nested document with keys 'reading' and 'swimming'

C. A number 2

D. An array with 'reading' and 'swimming'

Solution

1. Step 1: Identify the data type of hobbies field

   The hobbies field is shown with square brackets, which means it is an array.

2. Step 2: Understand array contents

   The array contains two string elements: 'reading' and 'swimming'.

3. Final Answer:

   An array with 'reading' and 'swimming' -> Option D

4. Quick Check:

   Square brackets mean array = An array with 'reading' and 'swimming' [OK]

Hint: Square brackets [] mean array in MongoDB documents [OK]

Common Mistakes:

• Thinking it's a string instead of an array
• Confusing arrays with nested documents
• Assuming the value is a count of items

4. Identify the error in this MongoDB document: { 'title': 'Book', pages: 250, author: 'John Doe' }

medium

A. This document is valid and has no error

B. Mixing quoted and unquoted field names is invalid

C. Values must be numbers only

D. Field names must all be unquoted

Solution

1. Step 1: Check field name quoting rules

   MongoDB allows field names to be quoted or unquoted as long as they are valid strings.

2. Step 2: Verify document validity

   Mixing quoted and unquoted field names is allowed; values are correctly typed.

3. Final Answer:

   This document is valid and has no error -> Option A

4. Quick Check:

   Quoted or unquoted field names both valid [OK]

Hint: MongoDB allows mixed quoted/unquoted field names [OK]

Common Mistakes:

• Thinking all field names must be quoted
• Assuming mixing quotes causes error
• Believing values must be only numbers

5. You want to store a user's profile with name, age, and a list of addresses (each with street and city) in MongoDB. Which document structure correctly represents this?

hard

A. { name: 'Eva', age: 28, addresses: '1st Ave, NY; 2nd St, LA' }

B. { name: 'Eva', age: 28, addresses: [{ street: '1st Ave', city: 'NY' }, { street: '2nd St', city: 'LA' }] }

C. { name: 'Eva', age: 28, addresses: { street: '1st Ave', city: 'NY' }, { street: '2nd St', city: 'LA' } }

D. [ name: 'Eva', age: 28, addresses: [{ street: '1st Ave', city: 'NY' }] ]

Solution

1. Step 1: Understand nested documents and arrays

   Addresses is a list (array) of objects (documents), each with street and city fields.

2. Step 2: Check each option's structure

   { name: 'Eva', age: 28, addresses: [{ street: '1st Ave', city: 'NY' }, { street: '2nd St', city: 'LA' }] } correctly uses an array of documents inside the addresses field. Others use strings, invalid syntax, or wrong brackets.

3. Final Answer:

   { name: 'Eva', age: 28, addresses: [{ street: '1st Ave', city: 'NY' }, { street: '2nd St', city: 'LA' }] } -> Option B

4. Quick Check:

   Array of nested documents = { name: 'Eva', age: 28, addresses: [{ street: '1st Ave', city: 'NY' }, { street: '2nd St', city: 'LA' }] } [OK]

Hint: Use array of documents for multiple nested objects [OK]

Common Mistakes:

• Storing nested data as a plain string
• Using invalid JSON syntax with multiple objects outside array
• Using square brackets for entire document instead of curly braces