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Cloudera CDP Data Engineer - Certification Sample Questions:

1. In Apache Spark, which of the following is the most effective strategy for minimizing data shuffling across nodes in a cluster?

A) Increasing the number of partitions
B) Using broadcast variables for small data
C) Decreasing the number of partitions
D) Filtering data after a wide transformation

2. Which Airflow operator is best used for executing a Python function as part of a DAG?

A) Dockeroperator
B) SimpleHttpOperator
C) BashOperator
D) PythonOperator

3. You encounter an error message stating "Schema mismatch" when joining two DataFrames in Spark. What could be the potential causes and how can you resolve them?

A) All of the above
B) The DataFrames have the same column names but different data types
C) The join condition references non-existent columns in one of the DataFrames
D) The DataFrames have different column names but the same data types

4. In a meeting about Spark applications deployment on Kubernetes, your team discusses strategies for handling node failures. Which Kubernetes feature should be utilized to maintain high availability in case of node failures?
A Horizontal Pod Autoscaler

A) Resource Quotas
B) ReplicaSets
C) Pod Priority

5. You are developing a PySpark application that processes a large dataset. Your application involves a transformation that requires shuffling data across the Executors. Which of the following responsibilities of the Spark Driver is most directly involved in this process?

A) Managing the shuffling and aggregation of data across Executors.
B) Monitoring the progress and status of tasks on the Executors.
C) Interpreting the user application and creating an execution plan.
D) Managing the lifecycle of Executor pods in Kubernetes.

Solutions: