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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. When analyzing an Explain Plan, what does the presence of a large number of "Nested Loop Joins" indicate about a query's potential performance?

A) It guarantees optimal performance for all dataset sizes
B) It suggests that the query is fully optimized for distributed execution
C) It implies that the data is perfectly partitioned for the query
D) It may indicate potential performance issues for large datasets due to the high computational cost

2. You need to design your Airflow DAG for data quality checks to be scalable and manageable as the number of datasets and checks grows. How can you achieve this?

A) Hardcode all data quality checks and data sources directly within the DAG code.
B) Implement a modular design using sub-DAGs, where each sub-DAG encapsulates the data quality checks for a specific dataset.
C) Utilize Airflow variables to store configuration details like data source paths and check thresholds.
D) Leverage external configuration files (e.g., YAML or JSON) to define data quality checks and associated parameters.

3. A data analyst is performing a join operation in PySpark between a large DataFrame Clarge_df) and a much smaller DataFrame ('small_df). The process is very slow. What can the analyst do to optimize this join operation?

A) Use "key").
B) Utilize the 'broadcast' function in the join operation.
C) Apply before the join.
D) Increase the number of partitions in 'small_df'.

4. What is the role of a Spark driver in a distributed processing job?

A) Stores and processes intermediate data
B) Manages communication between executors and workers
C) Coordinates tasks across the cluster
D) Performs computations on individual data partitions

5. You're working with an Airflow DAG that performs data quality checks on sensitive dat a. How can you ensure data security during the checks?

A) Implement data masking techniques to obfuscate sensitive information during the checks.
B) Utilize environment variables to store sensitive data and access them within the PythonOperator.
C) Store sensitive data like thresholds and comparison values directly within the DAG code.
D) All of the above

Solutions: