Question 1

In a MongoDB database tracking e-commerce orders, each order document includes fields for customer ID, order date, and a status that changes over time. To automatically purge orders older than two years and efficiently support queries for recent orders by customer ID, which combination of indexes would be most appropriate?

Options :

A : A compound index on customer ID and order date, and a TTL index on the status field.

B : A single-field index on the customer ID and a Time-To-Live (TTL) index on the order date.

C : A text index on the customer ID for efficient search and a TTL index on the order date.

D : A hashed index on customer ID and a TTL index on the order date.

Answer: B

Question 2

A data modeler is tasked with designing a database for a movie streaming service. The database needs to efficiently store and retrieve information about movies, including the movie's title, director, genre(s), release year, and average viewer rating. How should the data modeler structure the Movie entity?

Options :

A : Model Movie as a movie-s title, director, genre(s), release year, and average viewer rating.

B : Model Movie as a movie-s title, director, and genre(s).

C : Model Movie as a movie-s title, director, genre(s), release year, average viewer rating, and the total number of viewers.

D : Model Movie as the movie-s title only.

Answer: A

Question 3

A startup is designing a new MongoDB database to store user information and their respective device data. Each user can have multiple devices, and each device can generate daily usage statistics. The startup's application needs to frequently access a user's profile and their device's latest usage statistics. Considering scalability, efficiency, and security, which data model would best suit the startup's requirements?

Options :

A : Hybrid Model

B : Normalized Data Model

C : Embedded Documents Model

D : Bucketing

Answer: C

Question 4

A team is developing a logistics application using MongoDB to track shipments in real-time. Each shipment record updates frequently with GPS coordinates, and the system requires immediate access to the latest location data for efficient routing and delivery updates. The application also needs to maintain a compact record of each shipment's path without unnecessary data duplication. Which MongoDB feature or design pattern should be used to model the shipment tracking system?

Options :

A : The Bucket Pattern, grouping location updates by day for each shipment.

B : The Preallocation Pattern, by preallocating space for each shipment document to accommodate location updates.

C : The Document Versioning Pattern, where each update creates a new version of the shipment document.

D : A standard collection with an index on the lastUpdated field.

Answer: D

Question 5

In MongoDB schema design, what is a critical implication to consider when adding another piece of data into an array field, especially in the context of document size limitations and performance?

Options :

A : Arrays do not impact document size, allowing for unlimited data addition without performance concerns.

B : Adding elements to an array increases the risk of exceeding the BSON document size limit, potentially leading to failed updates.

C : Adding data to arrays significantly improves query performance by utilizing array-specific indexes.

D : Each addition to an array requires a complete document rewrite, which has no impact on performance or storage.

Answer: B

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