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Databricks Certified Data Engineer Associate Exam Sample Questions (Q68-Q73):

NEW QUESTION # 68
A global retail company sells products across multiple categories (e.g.. Electronics, Clothing) and regions (e.
g.. North. South, East. West). The sales team has provided the data engineer with a PySpark dataframe named sales_df as below and the team wants the data engineer to analyze the sales data to help them make strategic decisions.

A. Category_sales = sales_df.sum( " 3ales_amount " ). g-1- upBy( " categcryn).alias( " toLal_sales_amount))
B. Category_sales = sales_df.groupBy( " reqion " ). agq(sum( " sales_amountn).alias(ntotal_sales_amount
' ' ))
C. Category_sale: .es df -agg (sum ( " sales amount " ) .-;r*i:rRy ( " category " ) .alias ( " total sa.en amount " ))
D. Category_sales = sales df.groupBy( " category " ).agg(sum( " sales amount " ) .alias ( " total sales amount " ))

Answer: D

NEW QUESTION # 69
A data engineer is configuring Unity Catalog in Databricks and needs to assign a role to a user who should have the ability to grant and revoke privileges on various data objects within a specific schema but should not have read/write access over the schema or its objects.
Which role should the data engineer assign to this user?

A. Table Owner
B. Catalog Owner
C. USE CATALOG / USE SCHEMA privilege on the schema
D. Schema Owner

Answer: D

Explanation:
This question's options do not include the most precise Unity Catalog answer, which would normally be the MANAGE privilege on the schema, because Databricks documents that MANAGE allows a principal to grant and revoke privileges on an object without automatically granting all data-access privileges on that object. However, since MANAGE is not one of the answer choices, the best available answer is D, Schema Owner. Databricks states that schema owners can grant and revoke permissions on the schema, and schema-level administration is a documented responsibility of the schema owner. Option A is incorrect because USE CATALOG and USE SCHEMA only allow object access/navigation and do not confer privilege-management rights. Option B is too broad because a catalog owner governs the entire catalog scope, not just one schema. Option C is too narrow because a table owner controls only one table, not various objects across a schema. So, among the choices provided, Schema Owner is the closest Databricks-aligned answer, though the cleanest real-world implementation would be MANAGE on the schema.
=========

NEW QUESTION # 70
Which languages are supported by Serverless compute clusters? (Choose two.)

A. Python
B. R
C. Scala
D. SQL
E. Java

Answer: A,D

Explanation:
Serverless compute clusters in Databricks support SQL (via Serverless SQL Warehouses) and Python (for interactive and job-based execution). Other languages like R, Scala, and Java require regular clusters.

NEW QUESTION # 71
Which of the following is hosted completely in the control plane of the classic Databricks architecture?

A. JDBC data source
B. Worker node
C. Databricks Filesystem
D. Databricks web application
E. Driver node

Answer: D

Explanation:
The control plane in the classic Databricks architecture is responsible for managing the Databricks workspace, user and group management, and cluster management, among other things. The Databricks web application is a part of the control plane that enables users to interact with the workspace, create and manage clusters, and work with notebooks, jobs, and data.
Worker nodes and driver nodes are part of the data plane, which is responsible for executing data processing tasks. JDBC data sources and the Databricks Filesystem are services that are used by both the control plane and the data plane.

NEW QUESTION # 72
A data engineer is configuring a cluster in Databricks and wants to ensure that multiple Spark executors can run tasks concurrently across worker nodes. Which cluster component is responsible for executing tasks?

A. Job scheduler
B. Driver
C. Executor
D. Notebook

Answer: C

NEW QUESTION # 73
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