Free MongoDB C100DEV Exam Questions

Question 1

Which of the following constraints might impact your data model for MongoDB? (Select three)

A : Operating System

B : RAM

C : Network

D : File System Type

E : Security & Compliance

Answer: B,C,E

Question 2

You have a MongoDB collection named employees that contains documents with fields name, department, and salary. You want to update the salary of all employees in the "Marketing" department to $75,000. The original collection looks like this:

[

{ "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 },

{ "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 },

{ "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 },

{ "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }

]

You run the following MongoDB update operation:

db.employees.updateMany(

{ "department": "Marketing" },

{ $set: { "salary": 75000 } }

)

What will the collection look like after this update operation?

A : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

B : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 62000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

C : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 75000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

D : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 75000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

Answer: C

Question 3

As a MongoDB Developer, you are tasked with optimizing a MongoDB database. Your collection has documents with the following structure:

{

"_id": ObjectId(),

"user_id": Number,

"user_data": {

"name": String,

"email": String,

"phone": String,

"address": {

"city": String,

"state": String,

"country": String

}

},

"transactions": [

{

"transaction_id": Number,

"amount": Number,

"date": Date

}

]

}

The application frequently queries for the total transaction amount for users based on the city. Which index should you create to optimize the performance of these queries?

A : db.collection.createIndex({"user_data.address.city": 1})

B : db.collection.createIndex({"user_data.address.city": 1, "transactions.amount": 1})

C : db.collection.createIndex({"user_id": 1})

D : db.collection.createIndex({"transactions.amount": 1})

E : db.collection.createIndex({"transactions": 1})

Answer: B

Question 4

You are designing a MongoDB schema for an e-commerce platform. The platform has three main collections: Products, Orders, and Users.Products Collection: Contains information about each product, such as its name, price, and description.Orders Collection: Contains details about each order, including the userId (referencing the Users collection), an array of productIds (referencing the Products collection), and the total order amount.Users Collection: Contains user details, such as name, email, and address.Which of the following data modeling approaches represents an anti-pattern in MongoDB?

A : Referencing Orders within the Users collection by storing an array of orderIds.

B : Creating a separate ProductDetails collection and storing all product details there, referencing it from the Products collection.

C : Referencing productIds in the Orders collection instead of embedding full product details.

D : Embedding user details directly in the Orders collection.

Answer: B

Question 5

Which of the following statements are true regarding the MongoDB Aggregation Framework and pipelines? (Select two)

A : Aggregation pipelines can include stages like $match, $group, $project, and $sort.

B : Aggregation pipelines allow you to modify the structure of the original collection.

C : Aggregation pipelines support SQL-like joins between multiple collections.

D : The $limit stage is used to skip a specified number of documents in the aggregation pipeline.

E : The $unwind stage is used to deconstruct an array field from the input documents, creating a new document for each element of the array.

Answer: A,E