Free MongoDB Associate-Data-Modeler Exam Questions

Question 1

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 2

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?

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

Question 3

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 4

In an e-commerce application, the main entity Product includes details such as name, description, and price. Each Product can have multiple Review documents, which include ratings and customer comments. The application frequently displays products along with their reviews. How should the developer optimize the schema for read performance?

A : Embed Review documents within the Product document as an array of subdocuments.

B : Store each Review in a separate collection and use the Product ID to link to each Review.

C : Create a separate Review collection and a ProductReview join collection to manage the many-to-many relationship.

D : Store Review documents in a separate collection without storing a reference to the Product ID.

Answer: A

Question 5

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?

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