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: Feb 09, 2026

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Question 1

How can we present the basic syntax for aggregation in MongoDB?

A :

B :

C :

D :

Answer: D

Question 2

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

{

'_id': ObjectId("572bb8222b288919b68abf6d"),

'trip_duration': 858,

'start_station id': 532,

'end_station_id': 401,

'bike_id': 17057,

'start_station_loc': { type: 'Point', coordinates: [ -73.960876, 40.710451 ] },

'end_station_loc': { type: 'Point', coordinates: [ -73.98997825, 40.72019576 ] },

'start_time': ISODate("2016-01-01T00:09:31.000Z"),

'stop_time': ISODate("2016-01-01T00:23:49.000Z")

}

How can you extract all trips from this collection ended at stations that are to the west of the -73.5 longitude coordinate?

A : db.trips.find( { 'end_station_loc.coordinates.0': { $gt: -73.5 } } )

B : db.trips.find( { 'coordinates': { $lt: -73.5 } } )

C : db.trips.find( { 'end_station_loc.coordinates.0': { $lt: -73.5 } } )

D : db.trips.find( { 'end_station_loc.coordinates.1': { $lt: -73.5 } } )

Answer: C

Question 3

In the context of MongoDB development, you are creating a new service that is expected to handle high load. You've decided to leverage the MongoDB drivers' connection pooling capability. What best describes connection pooling and its advantages?

A : Connection pooling ensures secure data transfer between the client and the server by encrypting all connections in the pool.

B : Connection pooling allows a client to connect to a database only when a data transfer operation occurs, reducing the memory requirements.

C : Connection pooling involves maintaining a "pool" of open database connections, which can be reused for multiple requests, improving performance.

D : Connection pooling refers to the storage of multiple connection strings for redundancy, increasing system reliability.

Answer: C

Question 4

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

Question 5

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

Page: 1 / 83

Total 411 Questions | Updated On: Feb 09, 2026

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