Why the paradigm shift matters 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() to get data.

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'

AupdateOne

BinsertOne

CdeleteOne

Dfind

Attempts:

3 left

💡 Hint

Common Mistakes

Using find() to add data instead of insertOne().

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: 'Alice' }, { [1]: { age: 31 } })

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

A$set

B$get

C$add

D$remove

Attempts:

3 left

💡 Hint

Common Mistakes

Using $get or $add which are not valid update operators.

The $set operator updates the value of a field in a document.

4fill in blank

hard

Fill both blanks to find 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

B$lt

C25

D30

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lt (less than) instead of $gt (greater than).

The $gt operator means 'greater than'. We want ages greater than 25.

5fill in blank

hard

Fill all three blanks to delete documents where status is 'inactive' and age is less than 20.

MongoDB

db.collection.deleteMany({ status: [1], age: { [2]: [3] } })

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

A'inactive'

B$lt

C20

D'active'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'active' instead of 'inactive' for status.

We delete documents where status is 'inactive' and age is less than 20 using $lt.

Practice

1. What is the main reason MongoDB represents a paradigm shift compared to traditional databases?

easy

A. It only works with small datasets

B. It uses SQL queries for data retrieval

C. It requires strict schemas for all data

D. It stores data as flexible documents instead of fixed tables

Solution

1. Step 1: Understand traditional database storage

   Traditional databases store data in tables with fixed columns and rows.

2. Step 2: Compare MongoDB storage model

   MongoDB stores data as flexible JSON-like documents, allowing varied fields and structures.

3. Final Answer:

   It stores data as flexible documents instead of fixed tables -> Option D

4. Quick Check:

   Document storage = Paradigm shift [OK]

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

Common Mistakes:

• Thinking MongoDB uses SQL queries
• Assuming MongoDB requires fixed schemas
• Believing MongoDB is only for small data

2. Which of the following is the correct way to insert a document into a MongoDB collection named users?

easy

A. INSERT INTO users VALUES ('Alice', 30)

B. db.users.add({name: 'Alice', age: 30})

C. db.users.insertOne({name: 'Alice', age: 30})

D. insert document into users {name: 'Alice', age: 30}

Solution

1. Step 1: Recall MongoDB insert syntax

   MongoDB uses insertOne() or insertMany() methods on collections.

2. Step 2: Identify correct syntax

   db.users.insertOne({name: 'Alice', age: 30}) correctly inserts one document.

3. Final Answer:

   db.users.insertOne({name: 'Alice', age: 30}) -> Option C

4. Quick Check:

   insertOne() = Correct insert method [OK]

Hint: Use insertOne() to add a single document [OK]

Common Mistakes:

• Using SQL INSERT syntax in MongoDB
• Using non-existent methods like add()
• Writing commands in plain English

3. Given the collection products with documents like {name: 'Pen', price: 1.5}, what will this query return?

db.products.find({price: {$gt: 1}})

medium

A. All products with price greater than 1

B. Syntax error in query

C. All products with price equal to 1

D. All products with price less than 1

Solution

1. Step 1: Understand the query filter

   The filter {price: {$gt: 1}} means price greater than 1.

2. Step 2: Interpret the query result

   The query returns all documents where the price field is more than 1.

3. Final Answer:

   All products with price greater than 1 -> Option A

4. Quick Check:

   $gt means greater than [OK]

Hint: Remember $gt means greater than in MongoDB queries [OK]

Common Mistakes:

• Confusing $gt with $lt
• Thinking it returns price equal to 1
• Assuming syntax error due to $gt

4. Identify the error in this MongoDB query:

db.orders.find({status: 'shipped'}

medium

A. Missing closing parenthesis for find()

B. Incorrect field name 'status'

C. Using single quotes instead of double quotes

D. No error, query is correct

Solution

1. Step 1: Check query syntax

   The query is missing a closing parenthesis after the filter object.

2. Step 2: Confirm correct syntax

   Proper syntax is db.orders.find({status: 'shipped'}) with closing parenthesis.

3. Final Answer:

   Missing closing parenthesis for find() -> Option A

4. Quick Check:

   Parentheses must be balanced [OK]

Hint: Count parentheses to avoid syntax errors [OK]

Common Mistakes:

• Ignoring missing parentheses
• Thinking quotes cause error
• Assuming field name is wrong without checking

5. Why does MongoDB's document model make scaling easier compared to relational databases?

hard

A. Because it only supports vertical scaling

B. Because documents can store nested data, reducing the need for complex joins

C. Because it enforces strict schemas for all data

D. Because it uses SQL for faster queries

Solution

1. Step 1: Understand document model benefits

   MongoDB stores data in nested documents, allowing related data to be stored together.

2. Step 2: Compare with relational joins

   Relational databases require joins across tables, which can slow queries and complicate scaling.

3. Step 3: Connect to scaling

   Storing nested data reduces joins, making horizontal scaling and distributed data easier.

4. Final Answer:

   Because documents can store nested data, reducing the need for complex joins -> Option B

5. Quick Check:

   Nested documents = easier scaling [OK]

Hint: Nested documents reduce joins, aiding scaling [OK]

Common Mistakes:

• Thinking MongoDB enforces strict schemas
• Believing it only supports vertical scaling
• Assuming MongoDB uses SQL