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 have a reviews collection with the following index:

{ stars: 1, votes: 1 }

Which of the following queries would be a covered query?

A : db.reviews.find( { votes: { $gte: 100 } }, { _id: 0, votes: 1, stars: 1 })

B : db.reviews.find( { votes: { $gte: 100 } }, { _id: 0, votes: 1 })

C : db.reviews.find( { votes: { $gte: 100 }, stars: 4.5 }, { _id: 0 })

D : db.reviews.find( { stars: { $gt: 4.5 } }, { _id: 0, votes: 1 })

Answer: D

Question 3

Consider a collection named orders with the following documents:

{

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

"order_number" : 1001,

"customer_id" : "CUST-001",

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

"total_amount" : 199.99

},

{

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

"order_number" : 1002,

"customer_id" : "CUST-002",

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

"total_amount" : 299.99

},

{

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

"order_number" : 1003,

"customer_id" : "CUST-003",

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

"total_amount" : 399.99

}

What is the query to create a compound index on the "customer_id" (ascending) and "order_date" (descending) fields in the orders collection?

A : db.orders.createIndex({ order_date: -1, customer_id: 1 })

B : db.orders.createIndex({ customer_id: asc, order_date: desc })

C : db.orders.createIndex({ customer_id: 1, order_date: -1 })

D : db.orders.createIndex({ customer_id: -1, order_date: 1 })

Answer: C

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

Consider a collection named students with the following document:

{

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

"name" : "Alice",

"age" : 21,

"courses" : [

{

"name" : "Math",

"grade" : 89

},

{

"name" : "Science",

"grade" : 92

}

]

}

What is the query to update the grade of the "Math" course for the student with "_id" equal to ObjectId("5f0a7e80d8c9c7b5a48c49e1") to 95?

A : db.students.updateOne( { "courses.name": "Math" }, { $set: { "courses.$.grade": 95 } })

B : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1") }, { $set: { "courses.$.grade": 95 } })

C : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1"), "courses.name": "Math" }, { $set: { "courses.$.grade": 95 } })

D : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1"), "courses.name": "Math" }, { $set: { "grade": 95 } })

Answer: C