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Cloudera CDP Data Engineer - Certification Sample Questions:

1. What is the primary purpose of the Cost-Based Optimizer (CBO) in the context of Cloudera's Optimization Framework?

A) To decide the best execution plan based on the cost of operations
B) To choose the data storage format
C) To minimize the amount of data processed
D) To distribute data evenly across the cluster

2. What is the primary purpose of the Airflow Scheduler in Apache Airflow?

A) To distribute tasks across workers for execution
B) To provide a user interface for monitoring and managing DAGs
C) To monitor the state of tasks and trigger them based on their dependencies
D) To execute the code for each task in a DAG

3. You're developing a Spark application with multiple stages, and you want to ensure that later stages only start processing after all data from the previous stage is complete. How can you achieve this dependency management in Spark?

A) Set appropriate configuration for spark.sql.shuffe.partitions
B) Leverage Spark's lineage tracking and stage boundaries
C) Implement custom logic to track completion of each stage
D) Use explicit rdd.persist() calls in each stage

4. As a data engineer, you are working with PySpark to analyze data stored in an HDFS cluster. You need to read a CSV file into a Spark DataFrame. Which of the following code snippets correctly reads the data from HDFS into a DataFrame?

A)

B)

C)

D)

5. You need to design an Airflow DAG that waits for a specific file to become available before proceeding with the downstream tasks. How can you achieve this dependency?

A) Schedule the DAG to run periodically, hoping the file becomes available eventually.
B) Configure the source system to notify Airflow when the file is ready for processing.
C) Implement a custom loop within a Python operator to continuously check for the file until it appears.
D) Use the File sensor operator to check for the file's existence and trigger downstream tasks upon its arrival.

Solutions: