Free MongoDB C100DEV Exam Questions

Question 1

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 2

Suppose you insert the following documents into a companies collection:

db.companies.insertMany([

{"name": "Facebook"},

{"name": "X"}

])

Select all true statements about this command. (Select three)

A : This command will insert one document into the collection.

B : The command will only insert the first document and skip the second because the _id field is not explicitly provided.

C : This command will insert two documents into the collection.

D : MongoDB will automatically create an _id field for each document and it will be unique.

E : The _id field is not specified in any of these documents.

Answer: C,D,E

Question 3

Suppose you're designing a MongoDB database for an online ticket booking system where millions of users can concurrently book tickets for various events. To maintain data consistency, you need to ensure that only one user can book a specific seat for an event at a time. Which MongoDB feature would you use to ensure data consistency in this high-concurrency situation?

A : Multi-document transactions

B : Change Streams

C : Capped Collections

D : Sharding

Answer: A

Question 4

Consider a collection named orders with the following documents:

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e1"),

"order_id" : 101,

"customer_name" : "John Doe",

"order_date" : ISODate("2022-01-01T00:00:00.000Z"),

"items" : [

{

"product_name" : "Apple",

"quantity" : 2,

"price" : 0.99

},

{

"product_name" : "Banana",

"quantity" : 5,

"price" : 0.5

}

]

}

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e2"),

"order_id" : 102,

"customer_name" : "Jane Doe",

"order_date" : ISODate("2022-01-02T00:00:00.000Z"),

"items" : [

{

"product_name" : "Orange",

"quantity" : 3,

"price" : 0.79

},

{

"product_name" : "Mango",

"quantity" : 2,

"price" : 1.99

}

]

}

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e3"),

"order_id" : 103,

"customer_name" : "Bob Smith",

"order_date" : ISODate("2022-01-03T00:00:00.000Z"),

"items" : [

{

"product_name" : "Peach",

"quantity" : 4,

"price" : 1.49

},

{

"product_name" : "Pear",

"quantity" : 1,

"price" : 2.99

}

]

}

What is the query to retrieve the total sales for each customer in the orders collection?

A : db.orders.aggregate([ { $group: { _id: "$customer_name", total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } } } }])

B : db.orders.aggregate([ { $unwind: "$items" }, { $group: { _id: "$customer_name", total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } } } }])

C : db.orders.aggregate([ { $unwind: "$items" }, { $group: { total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } } } }])

D : db.orders.aggregate([ { $unwind: "$items" }, { $group: { _id: "$customer_name", total_sales: { $sum: { $multiply: ["quantity", "price"] } } } }])

Answer: B

Question 5

What is the difference between a sparse index and a non-sparse index in MongoDB?

A : A sparse index only indexes documents that contain the indexed field, while a non-sparse index indexes all documents in the collection, including those that do not contain the indexed field.

B : A sparse index indexes all documents in the collection, including those that contain the indexed field, while a non-sparse index only indexes documents that do not contain the indexed field.

C : A sparse index only indexes documents that do not contain the indexed field, while a non-sparse index indexes all documents in the collection, including those that contain the indexed field.

D : A sparse index indexes all documents in the collection, including those that do not contain the indexed field, while a non-sparse index only indexes documents that contain the indexed field.

Answer: A