Free MongoDB Associate-Data-Modeler Exam Questions

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?

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?

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?

To improve the performance of queries on a logEntries collection, a MongoDB developer needs to find and analyze slow queries that have been executed. Which command should be used to identify and provide details on slow operations for analysis?

In designing a database schema for a MongoDB application that handles user-generated content, such as posts and comments, a data modeler is considering the most efficient way to store comments related to each post to optimize read operations, as the application experiences significantly more reads than writes. The application requires frequent retrieval of posts along with their associated comments. What pattern should the data modeler use to store comments in relation to posts, and why?