Free MongoDB Associate-Data-Modeler Exam Questions

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?

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 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?

A data modeler is tasked with designing a database for a movie streaming service. The database needs to efficiently store and retrieve information about movies, including the movie's title, director, genre(s), release year, and average viewer rating. How should the data modeler structure the Movie entity?

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?