Free MongoDB C100DEV Exam Questions

Question 1

You are designing a MongoDB schema for an e-commerce platform. The system has three collections: Products, Categories, and Reviews.Products Collection: Contains information about each product, including its name, price, and categoryId referencing the Categories collection.Categories Collection: Contains the category name and description.Reviews Collection: Contains user reviews for products, including the productId referencing the Products collection, userId, rating, and reviewText.Which of the following is the best approach to model the relationships between Products, Categories, and Reviews in MongoDB?

A : Reference Categories in the Products collection using categoryId and reference Products in the Reviews collection using productId.

B : Embed Categories directly within the Products collection.

C : Embed Reviews directly within the Products collection.

D : Reference Reviews in both the Products and Categories collections.

Answer: A

Question 2

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 3

In a MongoDB database with referenced relationships, what is the advantage of using a separate collection for each entity over using a single collection for all entities?

A : Improved maintainability and reduced complexity of updates to related entities.

B : Improved query performance and reduced complexity of updates to related entities.

C : Improved maintainability and increased scalability.

D : Improved query performance and increased scalability.

Answer: A

Question 4

Consider a tasks collection that holds task records. The document structure is as follows:

{

"_id": ObjectId("64b64c58ed01c0a5e72dbf5f"),

"task": "Review PR",

"status": "pending",

"assignedTo": "alice"

}

Two operations are performed concurrently:

Operation A:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

remove: true

});

Operation B:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

update: { $set: { status: "completed" } },

new: true

});

Operation B starts slightly after Operation A but before Operation A completes. What will be the final state of the tasks collection after both operations have been executed?

A : The document will be removed from the collection.

B : The document's status will be updated to "completed".

C : A new document with the status "completed" will be inserted.

D : The document's status will remain "pending".

Answer: A

Question 5

We have an accounts collection with the following document structure:

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239d"),

account_id: 864905,

limit: 10000,

products: [ 'Commodity', 'InvestmentStock' ]

},

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239e"),

account_id: 299072,

limit: 10000,

products: [ 'InvestmentFund', 'InvestmentStock' ]

},

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239f"),

account_id: 137994,

limit: 10000,

products: [ 'CurrencyService', 'InvestmentStock' ]

}

We need to use Aggregation Framework to find the distribution of products field. Sort the result set by decreasing total number of products.

Expected output:

[

{ _id: 'InvestmentStock', total: 1746 },

{ _id: 'CurrencyService', total: 742 },

{ _id: 'Brokerage', total: 741 },

{ _id: 'InvestmentFund', total: 728 },

{ _id: 'Commodity', total: 720 },

{ _id: 'Derivatives', total: 706 }

]

Which pipeline should you use?

A : [{ $group: { _id: "$products", total: { $sum: 1 } }}]

B : [{ $unwind: { path: "$products" }}, { $group: { _id: "$products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

C : [{ $unwind: { path: "products" }}, { $group: { _id: "products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

D : [{ $group: { _id: "$products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

Answer: B