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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. How does the Cloudera Optimization Framework leverage columnar storage formats for query performance improvement?

A) By encrypting data stored in columnar formats
B) By allowing more efficient data scans and operations on compressed data
C) By reducing network traffic through columnar data replication
D) By enabling more efficient compression and encoding schemes

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

3. In the context of data quality checks with Apache Airflow, what is the primary purpose of using the EmailOperator?

A) To execute quality checks on email data
B) To notify team members of failed data quality checks
C) To retry failed tasks via email commands
D) To collect data from email attachments for quality checks

4. For a dataset that is used multiple times in different transformations but is not large enough to warrant disk storage, which caching level in Apache Spark is most appropriate?

A) MEMORY ONLY SER
B) DISK ONLY
C) MEMORY AND DISK SER
D) MEMORY ONLY

5. You want to write the results of a Spark DataFrame back to a Hive table. How can you achieve this efficiently?

A) Convert the DataFrame to a temporary table and then use HiveQL operations
B) Use the DataFrame.write.saveAsTable("table_name") method
C) Use the hiveContext.sql("lNSERT INTO table_name SELECT FROM df') method
D) Implement a custom function to write individual rows to the Hive table

Solutions: