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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. What is a potential downside of overly granular partitioning in Hive tables?

A) Simplified data management
B) Reduced query performance due to metadata overhead
C) Increased data security
D) Automatic data deduplication

2. 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)

3. In the context of improving join performance in Spark, what does "salting" involve?

A) Encrypting the data before performing a join
B) Adding a random prefix to keys to distribute skewed data more evenly
C) Seasoning the data with random noise for privacy
D) Physically co-locating related data on the same node

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

5. You're working with a Hive table containing sensitive dat
a. How can you ensure data security while allowing authorized Spark applications to access the data?
A Store the data in plain text format and restrict access to the HDFS directory

A) Implement custom encryption/decryption logic within your Spark application
B) Use separate clusters for Spark and Hive with stricter security controls
C) Leverage Cloudera Sentry for role-based access control and data masking

Solutions: