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: Dec 18, 2025

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Question 1

Consider a MongoDB database managing e-commerce product data. The database has a collection named products with documents containing the fields product_id, category, price, and reviews. Each reviews field is an array of subdocuments with fields user_id, rating, and comment. You are tasked with optimizing a query that retrieves all products within a specific category that have an average rating higher than 4. The query is frequently used, and performance is critical. Which indexing strategy would best optimize this query?

A : Create a compound index on category and reviews.rating, with a partial filter expression that only includes documents where the average rating in reviews.rating is greater than 4.

B : Create a multi-key index on reviews.rating.

C : Create a compound index on category and reviews.rating.

D : Create a single index on the category field.

E : Create a compound index on category, reviews.rating, and price.

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

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 4

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 5

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

A :

B :

C :

D :

Answer: D

Page: 1 / 83

Total 411 Questions | Updated On: Dec 18, 2025

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