Free MongoDB Associate-Data-Modeler Exam Questions

Question 1

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?

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 2

In a blogging application, the main entity Article contains text, a title, and metadata. Each article can have multiple comments made by users. The application frequently retrieves an article along with all its comments for display. How should the developer optimize the schema for read performance?

A : Embed Comment documents directly within an Article document in an array of subdocuments.

B : Store each Comment in a separate collection and reference the Article ID in every Comment.

C : Use a third collection to manage relationships between Article and Comment documents with document references.

D : Duplicate the Article information in each Comment document to avoid joins.

Answer: A

Question 3

In a MongoDB database for an online bookstore, you're designing a data model to handle books, authors, and reviews efficiently, considering a complex scenario involving relationships and potential data skew due to varying numbers of reviews per book. Given the requirements:

Each book can have multiple authors.

Each author can write multiple books.

Books can have a large number of reviews, but most have a few or none, creating potential data skew.

The application frequently queries books with their authors and a sample of reviews to avoid performance issues due to data skew.

How should you model the relationships among books, authors, and reviews to optimize for query performance and data management?

A : Embed authors and a fixed number of top reviews in each book document.

B : Use a separate collection for reviews and link them to books with a book ID. Authors and books are embedded within each other's documents.

C : Reference authors and reviews in the book document with foreign keys.

D : Embed books within author documents, including all reviews for each book.

Answer: A

Question 4

A MongoDB data modeler is optimizing the performance of an application that frequently executes the following query:

db.orders.find(

{ status: "shipped", deliveryDate: { $lte: new Date("2023-12-31") } }

).sort({ deliveryDate: -1 })

The explain method reveals the following key details indicating the query is not efficiently utilizing indexes:

{

"queryPlanner": {

...

"winningPlan": {

"stage": "SORT",

"sortPattern": { "deliveryDate": -1 },

...

"inputStage": {

"stage": "FETCH",

"inputStage": {

"stage": "IXSCAN",

"keyPattern": { "status": 1 },

...

}

},

"executionStats": {

"executionSuccess": true,

"nReturned": 100,

"executionTimeMillis": 120,

"totalKeysExamined": 500,

"totalDocsExamined": 500,

...

},

...

}

What action should the data modeler take to enhance the performance of this query?

A : Create a compound index on status and deliveryDate in descending order to match the sort pattern.

B : Create an index on the deliveryDate field to optimize the sort operation.

C : Create a compound index on status and deliveryDate in ascending order.

D : Remove the sort operation to decrease the complexity of the query.

Answer: A

Question 5

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?

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