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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. You need to process data stored in AWS S3 using SparkSQL. Which of the following options correctly reads a JSON file stored in S3 into a DataFrame and performs a SQL query on it?

A)

B)

C)

D)

2. You are designing a data pipeline that involves ingesting data from multiple sources, performing data transformations using Spark, and storing the results in a data lake. How would you leverage the Cloudera Data Engineering service to ensure efficient and fault-tolerant execution?

A) Design the pipeline with stages and steps, leveraging Spark operators for transformations and utilizing retries and error handling mechanisms.
B) Implement custom logic within the YAML configuration file to manage data flow and error handling.
C) Develop a single Spark job containing all transformation logic.
D) Utilize separate Spark jobs for each data source and transformation step.

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

4. Due to regulatory requirements, you need to permanently delete specific sensitive records from an Iceberg table. Which of the following techniques would be most appropriate?

A) Issue a standard Iceberg DELETE query, as deleted data will automatically be expunged from the table.
B) Modify the data files directly using low-level tools to overwrite the sensitive data.
C) Use Iceberg's EXPIRE SNAPSHOTS procedure to remove snapshots containing the sensitive data.
D) Implement a custom process, leveraging Iceberg's row-level updates to delete the sensitive records and then using file-level operations to physically remove the data.

5. You're facing slow performance in your Spark application due to frequent shuffles. What are some strategies you can employ to optimize shuffle operations and improve performance?

A) Reduce the number of partitions in your RDDs
B) Use a broadcast variable for small, frequently accessed data
C) Increase the number of executors in your cluster
D) All of the above

Solutions: