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Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're working with a complex data pipeline involving both Spark and Hive operations. How can you ensure data consistency and avoid data corruption across different stages?

A) Manually manage data consistency through custom code
B) Rely solely on Spark's checkpointing capabilities
C) Leverage ACID transactions in both Spark and Hive
D) Use separate clusters for Spark and Hive processing

2. What mechanism does Apache Airflow provide to delay the execution of a task until a certain condition is met?
A The delay parameter in task definitions.

A) The execution_timeout attribute, which can be set to postpone task execution.
B) Sensors, which are special operators that wait for a certain condition to be true.
C) The wait_for_downstream setting in the DAG configuration.

3. In the context of packaging a PySpark application, what is the purpose of the 'requirements.txt' file?

A) To list the environment variables needed for the application.
B) To list all the third-party dependencies required by the application.
C) To specify the Python version required for the application.
D) To define the Spark version compatible with the application.

4. You are processing a large dataset using Spark and need to ensure that the results are available for subsequent stages without recomputing. Which approach achieves this efficiently?

A) Leverage Spark's automatic checkpointing mechanism
B) Implement custom logic to save the data to HDFS between stages
C) Use rdd.persist() with the appropriate storage level based on your needs
D) Store the data in a temporary table using Spark SQL

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

Solutions: