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?

Options :

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 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 3

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 4

When optimizing a MongoDB collection's schema for a high-traffic application, what factor is crucial for determining the most effective document structure?

Options :

A : Modeling documents to reflect the application-s access patterns, prioritizing query performance and data retrieval efficiency.

B : Designing documents based on the visual appeal of the JSON structure in the database management interface.

C : Ensuring all documents in a collection have a uniform size by adding placeholder data where necessary.

D : Organizing fields in alphabetical order within documents to facilitate easier indexing.

Answer: A

Question 5

A financial trading platform stores transaction data in MongoDB, including trade details, user portfolios, and real-time market data. The platform must efficiently process and display up-to-date portfolio valuations, historical trades, and market trends. Given the critical need for low-latency responses to support real-time decision-making and historical analysis, which MongoDB schema design pattern should be prioritized to optimize the platform's most critical data access patterns?

Options :

A : Outlier Pattern

B : Computed Pattern

C : Versioning Pattern

D : Subset Pattern

Answer: B

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