Question 1

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 2

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 3

In MongoDB, how should the analysis of query and analytics patterns influence the decision on indexing strategies, particularly with respect to the operational context of queries being part of a transaction?

Options :

A : Indexes should be avoided in transactional queries to reduce the complexity of transactions and improve write performance.

B : For queries within transactions, prioritize the creation of indexes on fields involved in the read operations of the transaction to minimize locking and improve concurrency.

C : Ensure that every transactional query operation utilizes a hashed index to guarantee performance efficiency across all transaction phases.

D : Use single field indexes for all fields involved in transactional queries to maximize the flexibility of query optimization.

Answer: B

Question 4

A MongoDB data modeler needs to optimize a collection named orders to efficiently query documents based on the status field, which can have values like 'pending', 'completed', and 'canceled'. The collection has millions of documents, and the queries should return results quickly even under heavy load. Which of the following approaches best achieves this requirement while maintaining the collection's scalability and performance?

Options :

A : Create a separate collection for each status value and distribute the documents accordingly, querying the relevant collection based on the status.

B : Index the status field using a single field index, ensuring queries filtering by 'status' are more efficient.

C : Convert the status field into an array and use a multi-key index, ensuring multiple status values can be queried simultaneously.

D : Use a hashed index on the status field to evenly distribute the documents across the collection.

Answer: B

Question 5

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

Free Associate-Data-Modeler Mock Exam – Practice Online Confidently

Buying Options: