Free MongoDB C100DEV Exam Questions

Question 1

Given the following orders collection in MongoDB:

[

{

"_id": 1,

"customer": "John",

"orderDetails": [

{ "productId": "P1", "quantity": 2, "unitPrice": 50 },

{ "productId": "P2", "quantity": 1, "unitPrice": 30 }

]

},

{

"_id": 2,

"customer": "Sara",

"orderDetails": [

{ "productId": "P1", "quantity": 3, "unitPrice": 50 },

{ "productId": "P3", "quantity": 2, "unitPrice": 20 }

]

},

{

"_id": 3,

"customer": "Peter",

"orderDetails": [

{ "productId": "P2", "quantity": 2, "unitPrice": 30 },

{ "productId": "P4", "quantity": 1, "unitPrice": 100 }

]

}

]

Which MongoDB query will find all orders that contain a product with the productId of "P1" and a quantity greater than 1?

A : db.orders.find( { orderDetails: { $elemMatch: { productId: "P1", quantity: { $gt: 1 } } } } )

B : db.orders.find( { "orderDetails.productId": "P1", "orderDetails.quantity": { $gt: 1 } } )

C : db.orders.find( { orderDetails: { $elemMatch: { productId: "P1", quantity: { $gte: 1 } } } } )

D : db.orders.find( { "orderDetails.productId": "P1", "orderDetails.quantity": { $eq: 2 } } )

Answer: A

Question 2

Consider a MongoDB collection named products which has documents in the following format:

{

"_id" : ObjectId("5f5b0d2f3e3dfbcc11c84444"),

"name" : "Smartphone",

"brand" : "Apple",

"category" : "Electronics",

"price" : 1000,

"discount" : 0.1

}

What is the correct syntax to update the "price" field of all documents in the products collection by multiplying it with (1 - discount) using the $set operator and the $multiply operator?

A : db.products.update( {}, { $set: { price: { $multiply: ["$price", { $subtract: [1, "$discount"] }] } } })

B : db.products.updateMany( {}, { $set: { price: { $multiply: ["$price", 1 - $discount] } } })

C : db.products.update( {}, { $set: { price: { $multiply: ["$price", 1 - $discount] } } })

D : db.products.updateMany( {}, { $set: { price: { $multiply: ["$price", { $subtract: [1, "$discount"] }] } } })

Answer: D

Question 3

Suppose you have a restaurants collection with the following document structure:

{

_id: ObjectId("5eb3d668b31de5d588f42931"),

address: {

building: '6409',

coord: [ -74.00528899999999, 40.628886 ],

street: '11 Avenue',

zipcode: '11219'

},

borough: 'Brooklyn',

cuisine: 'American',

grades: [

{

date: ISODate("2014-07-18T00:00:00.000Z"),

grade: 'A',

score: 12

},

{

date: ISODate("2013-07-30T00:00:00.000Z"),

grade: 'A',

score: 12

},

{

date: ISODate("2013-02-13T00:00:00.000Z"),

grade: 'A',

score: 11

},

{ date: ISODate("2012-08-16T00:00:00.000Z"),

grade: 'A',

score: 2 },

{

date: ISODate("2011-08-17T00:00:00.000Z"),

grade: 'A',

score: 11

}

],

name: 'Regina Caterers',

restaurant_id: '40356649'

}

You don't have any indexes so far. What will the query plan look like for the following query?

db.restaurants.find( { "cuisine": "American" } )

A : IXSCAN

B : SORT

C : FETCH

D : COLLSCAN

Answer: D

Question 4

In a MongoDB collection named orders, you are tasked with retrieving a subset of documents that fulfill specific criteria. Each document in this collection contains the following fields: customerId, orderId, orderDate, and orderDetails (an embedded document with fields: product, quantity, unitPrice). You are required to fetch all orders made by the customer with a customerId of 1234 on a specific date 2023-04-12, and only return the orderId, orderDate, and product from orderDetails. Which of the following MongoDB queries would accurately fulfill these requirements?

A :

B :

C :

D :

Answer: A

Question 5

In your database there is a collection named companies with the following document structure:

{

name: 'Wize',

relationships: [

{

is_past: false,

title: 'Head of Product',

person: {

first_name: 'Ethan',

last_name: 'Smith',

permalink: 'ethan-smith'

}

},

{

is_past: true,

title: 'Director, Business Development',

person: {

first_name: 'Stephanie',

last_name: 'Quay',

permalink: 'stephanie-quay'

}

},

{

is_past: true,

title: 'Sr. Engineer',

person: {

first_name: 'Stefan',

last_name: 'Antonowicz',

permalink: 'stefan-antonowicz'

}

]

}

Which of the following queries should you use to extract all companies that have "Co-Founder" title in relationships field (Array)?

A : db.companies.find( { relationships: { $expr: { title: 'Co-Founder' } } } )

B : db.companies.find( { relationships: { $elemMatch: { title: 'Co-Founder' } } } )

C : db.companies.find( { relationships: { $match: { title: 'Co-Founder' } } } )

D : db.companies.find( { relationships: { $eq: { title: 'Co-Founder' } } } )

Answer: B