Question 1

Regarding MongoDB schema design and document structure, which two of the following statements are accurate?

Options :

A : All documents within a collection must have the same fields and data types.

B : Embedding documents is recommended for frequently accessed data that is read together.

C : Schema validation rules are enforced by default on all collections upon creation.

D : Denormalization can reduce the need for expensive joins and improve read performance.

Answer: B,D

Question 2

When modeling a content management system in MongoDB, which approach best describes the handling of articles and their corresponding comments to optimize for frequent reads and occasional writes?

Options :

A : Articles and comments should be stored in separate collections, with comments embedding the full article document for efficiency.

B : Each comment should be stored in its own collection with a reference to its parent article ID.

C : Store each article in its own document within a single collection, with comments embedded as an array of subdocuments within each article.

D : A relational database management system must be used, as MongoDB cannot efficiently manage hierarchical data like articles and comments.

Answer: C

Question 3

In the design of a MongoDB database for an application that manages user profiles with varying degrees of completeness and privacy settings, what are the positives and negatives of relying on in-app enforcement versus schema validation to ensure data integrity and compliance with business requirements?

Options :

A : Schema validation ensures that all data writes adhere to the defined schema, reducing the need for additional application logic but lacks flexibility for handling complex conditional validation.

B : In-app enforcement is more performance-efficient because it avoids the overhead of database-level checks but can result in data integrity issues if the application crashes.

C : In-app enforcement allows for more complex logic and conditional validation but may lead to inconsistency if not implemented correctly across all application components.

D : Schema validation simplifies application code by offloading rules to the database but can lead to performance bottlenecks under heavy write loads.

Answer: C

Question 4

A developer is building a project management tool where each Project can have multiple Task entities. The tasks are frequently updated and accessed together with their parent project. What is the most efficient way to model this data relationship in MongoDB to optimize for task read and write operations?

Options :

A : Embed Task documents as an array of subdocuments within each Project.

B : Create a separate collection for tasks and projects, linking them through a shared projectId and taskId in a third collection.

C : Store each Task in a separate collection, with a projectId to reference back to their Project.

Answer: A

Question 5

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

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