Free MongoDB C100DEV Exam Questions

Become MongoDB Certified with updated C100DEV exam questions and correct answers

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Total 411 Questions | Updated On: Apr 02, 2026

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Question 1

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 2

In MongoDB, the $out operator is commonly used within an aggregation pipeline. Which of the following statements accurately describes the functionality and usage of the $out operator?

A : $out operator is used to output the results to a specified collection.

B : $out operator can be used to output the results to a collection in a different MongoDB database.

C : $out operator is used to export data directly to a file.

D : $out operator is used to read data from multiple collections in a single command.

Answer: A

Question 3

Given a movies collection where each document has the following structure:

{

_id: ObjectId('573a1390f29313caabcd60e4'),

genres: [ 'Short', 'Comedy', 'Drama' ],

title: 'The Immigrant',

year: 1917,

imdb: { rating: 7.8, votes: 4680, id: 8133 },

countries: [ 'USA' ]

}

Which of the following queries will find all the movies that have more votes than the year in which they were released?

A : db.movies.find({ $expr: { $gt: ["imdb.votes", "year"] } } )

B : db.movies.find({ $expr: { $lt: ["$imdb.votes", "$year"] } } )

C : db.movies.find({ $gt: ["$imdb.votes", "$year"] } )

D : db.movies.find({ $expr: { $gt: ["$imdb.votes", "$year"] } } )

Answer: D

Question 4

When sharding a MongoDB collection, what is the main factor that determines the distribution of data across shards?

A : The location of the client issuing the query

B : The number of documents in the collection

C : The size of each document

D : The value of a shard key

Answer: D

Question 5

We have a movies collection with the following document structure:

{

_id: ObjectId("573a1390f29313caabcd6223"),

genres: [ 'Comedy', 'Drama', 'Family' ],

title: 'The Poor Little Rich Girl',

released: ISODate("1917-03-05T00:00:00.000Z"),

year: 1917,

imdb: { rating: 6.9, votes: 884, id: 8443 }

{

_id: ObjectId("573a13e3f29313caabdc08a4"),

genres: [ 'Horror', 'Thriller' ],

title: 'Mary Loss of Soul',

year: 2014,

imdb: { rating: '', votes: '', id: 2904798 }

}

We need to use Aggregation Framework to calculate the following aggregates:

average imdb rating

minimum imdb rating

maximum imdb rating

Expected output:

[

{

_id: null,

avg_rating: 6.6934040649367255,

min_rating: 1.6,

max_rating: 9.6

}

]

Please note that some documents have "" (empty string) for the field "imdb.rating". Exclude these documents before aggregation.

Which pipeline should you use?

A : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { $avg: "imdb.rating" }, min_rating: { $min: "imdb.rating" }, max_rating: { $max: "imdb.rating" } }}]

B : [{ $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } }}]

C : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } }}]

D : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { avg: "$imdb.rating" }, min_rating: { min: "$imdb.rating" }, max_rating: { max: "$imdb.rating" } }}]

Answer: C

Page: 1 / 83

Total 411 Questions | Updated On: Apr 02, 2026

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