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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. If a Spark Driver pod in Kubernetes is reaching its CPU limit and experiencing performance issues, what is the most appropriate first action?

A) Increase the CPU requests in the pod's YAML configuration.
B) Restart the Kubernetes cluster.
C) Decrease the memory limits in the pod's YAML configuration.
D) Increase the CPU limits in the pod's YAML configuration.

2. When optimizing join operations in a distributed data processing environment, why is it important to co-locate join keys?

A) To enhance data encryption methods for secure joins
B) To ensure data integrity by preventing data loss during network transmission
C) To minimize data shuffle by ensuring related data is on the same node
D) To increase the storage capacity required for join operations

3. When deploying a Spark application in Kubernetes, what is the purpose of specifying the '-conf spark.kubernetes.driver.pod.name=spark-driver-pod' in the 'spark-submit' command?

A) To name the Executor pods.
B) To define the Docker image for the Driver pod.
C) To specify the name of the Spark Driver pod.
D) To assign a specific node for the Driver pod.

4. How does Spark handle data shuffling during distributed processing?

A) By transferring only required data between executors
B) Spark doesn't perform data shuffling
C) By broadcasting all data to each executor
D) By storing all data on a single node

5. In Apache Airflow, which strategy allows for the dynamic generation of tasks within a DAG based on external data sources, such as a list of database tables?

A) Utilizing the @dag decorator with dynamic input parameters
B) Employing the TaskFlow API with dynamic task mapping
C) Using the Variable class to store and retrieve the list of tables
D) Implementing a PythonOperator that generates other tasks at runtime

Solutions: