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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're building an Airflow ETL pipeline that involves data validation checks. How can you integrate these checks into the pipeline and handle potential failures?

A) Configure the DAG to send email notifications upon validation failures for manual intervention.
B) Implement the validation checks within custom Python operators and raise exceptions upon failure, triggering downstream tasks to handle the error.
C) Leverage XCom to share the validation results with downstream tasks for further processing.
D) Use the FailoverOperator to automatically skip downstream tasks if the validation check fails.

2. You're building an Airflow DAG that involves multiple data processing tasks. How can you handle task dependencies and ensure the tasks execute in the correct order?

A) Use the Airflow UI to visually connect the tasks with arrows, indicating their execution order.
B) Define the tasks directly within the DAG code using Python operators and set their dependencies manually.
C) Leverage XCom to share data between tasks and define dependencies based on the data availability.
D) All of the above

3. Your Airflow DAG encounters an error during the data transformation stage. What information can you access in the Airflow UI to troubleshoot the issue?

A) The Airflow web server logs might contain relevant information about the error.
B) The DAG run details page displays the task logs, providing insights into the specific error encountered.
C) You need to manually inspect the code for potential issues.
D) All of the above

4. You are writing a PySpark application where you need to collect the final results from various Executors and present them to the user. Which aspect of the Spark Driver's role is primarily involved in this process?

A) Constructing the logical plan from the user application.
B) Optimizing resource utilization within the Kubernetes cluster.
C) Collecting final results from Executors and providing the output.
D) Managing Kubernetes API interactions for Executor lifecycle.

5. What is the role of an Operator in an Apache Airflow DAG?
A To schedule DAG runs based on time or external triggers

A) To store metadata and logs for tasks and DAGs
B) To monitor the execution of DAGs and provide notifications
C) To represent a single task or a step within a DAG

Solutions: