Question 1

In designing a catalog application, a developer is dealing with Product entities that have multiple Review entities. The application frequently displays products along with the top three reviews based on ratings. How should the developer model this data to optimize for performance?

Options :

A : Use a separate collection to maintain a list of product IDs and their associated top three review IDs.

B : Embed the top three Review documents within each Product document.

C : Store each Review in a separate document, linking them to their respective Product via a product ID.

D : Embed all Review documents within their respective Product document.

Answer: B

Question 2

In the context of a MongoDB database application for an online news platform, the data modeler is tasked with optimizing the storage and retrieval of news articles that are frequently accessed by readers. The articles undergo occasional updates by the editorial team and include metadata such as publication date, author, and a set of tags. The application has a high read-to-write ratio, with the need for efficient retrieval of articles based on tags and publication dates. What data modeling strategy should be adopted to maximize query performance for retrieving articles based on metadata?

Options :

A : Adopt the Bucket Pattern, grouping articles into buckets by publication month or year.

B : Apply the Reference Pattern, creating separate collections for articles and metadata, with references between them.

C : Employ the Indexing Pattern, creating indexes on tags and publication dates within the articles collection.

D : Implement the Embedded Documents Pattern, embedding metadata within each article document.

Answer: C

Question 3

To improve the performance of queries on a logEntries collection, a MongoDB developer needs to find and analyze slow queries that have been executed. Which command should be used to identify and provide details on slow operations for analysis?

Options :

A : db.adminCommand({ "getLog": "global" })

B : db.setProfilingLevel(2, { "slowms": 100 })

C : db.logEntries.find({ "slowQuery": { $exists: true } })

D : db.logEntries.aggregate([ { $currentOp: { "slowOp": true } } ])

Answer: A

Question 4

In the process of optimizing a MongoDB schema for a social media application that features user profiles, posts, and interactions (likes, comments), a data modeler is evaluating the use of embedded documents versus referencing. Considering the application experiences frequent reads and writes on user interactions, and the volume of interactions is high: What is the primary advantage of embedding user interactions directly within user documents instead of referencing them in separate collections?

Options :

A : Embedding interactions allows for more complex transactions across documents.

B : Embedding interactions facilitates more efficient reads by reducing the need for join operations.

C : Embedding interactions improves write efficiency by reducing the number of write operations.

D : Embedding interactions ensures that data cardinality remains low, improving indexing efficiency.

Answer: B

Question 5

A MongoDB data modeler is designing a schema for a content management system (CMS) that stores articles, each with multiple tags and categories. The CMS will feature frequent searches by tags and categories, with more read operations than writes. The schema must optimize for query performance and scalability. What schema design pattern is most appropriate for this use case?

Options :

A : Use a separate collection for tags and categories, with references in the article documents.

B : Implement a Bucket Pattern, grouping articles by tags and categories in the same document.

C : Utilize the Polymorphic Pattern, allowing tags and categories to adapt to different types of articles.

D : Embed tags and categories directly within each article document.

Answer: D

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