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Cloudera CDP Data Engineer - Certification Sample Questions:

1. What is the impact of query vectorization in Cloudera's Optimization Framework?

A) It slows down query execution by adding complexity
B) It encrypts query results for security
C) It enables the execution of SQL commands
D) It improves query performance by processing batches of rows together

2. A PySpark application is facing performance issues due to uneven distribution of data across the nodes. Which approach would best help in resolving this issue?

A) Convert the DataFrame to an RDD and then back to a DataFrame.
B) Employ to redistribute data based on a key.
C) Use 'df.collect()'.
D) Apply 'df.coalesce(Y to reduce the number of partitions.

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

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

4. In a PySpark application running on Kubernetes, if one of the Executors fails to execute a task due to a node failure, what action does the Spark Driver take?

A) It immediately shuts down the entire application.
B) It requests Kubernetes to allocate more resources to the failed Executor.
C) It pauses the application until the failed Executor is back online.
D) It reschedules the task on a different Executor.

5. What impact does the Spark configuration parameter spark.network.timeout have on Spark streaming applications?

A) It determines the timeout for connections between executors and the Spark driver, impacting task retries and executor loss detection.
B) It controls the maximum time a Spark streaming application will wait for data before timing out.
C) It sets the timeout for Akka-based network operations, crucial for Spark streaming's stability.
D) It specifies the timeout for network operations such as data shuffle and broadcast.

Solutions: