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Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're tasked with optimizing the performance of your ETL pipeline in Airflow. What are some potential strategies to consider?

A) Increase the number of worker processes in Airflow to parallelize task execution.
B) Utilize efficient data structures and algorithms within your custom Python operators for data transformation.
C) Leverage partitioning and bucketing techniques in the data warehouse to improve query performance.
D) All of the above

2. In a Kubernetes environment, how does Kubernetes ensure fault tolerance when a pod running a Spark task fails?

A) Through Pod Replication with ReplicaSets
B) By checkpointing RDDs
C) Using a load balancer for master components
D) By using a Standby Master setup

3. Your Iceberg table has a hidden partition by month(event_timestamp). You frequently query with filters on the event_timestamp column. What potential problem might you encounter, and how would you address it?

A) No problems; hidden partitioning is designed for this use case.
B) Compatibility issues with older Spark versions; ensure you're using a version supporting hidden partitioning
C) Errors due to incorrect partition discovery; you'll need to manually update Iceberg table metadata.
D) Performance issues due to unnecessary file scanning; consider adding event_timestamp as an explicit partition.

4. You need to design a DAG that can be easily monitored and visualized for performance insights. How can you achieve this?

A) Implement custom logic within each task to send detailed performance metrics to external monitoring tools.
B) Implement alerts and notifications within the DAG to trigger upon specific events or performance thresholds.
C) Utilize Airflow's built-in metrics and monitoring features like the Airflow web UI to track DAG execution and task performance.
D) All of the above

5. Considering Hive's optimization mechanisms, under which scenario might partition pruning fail to improve query performance?

A) When querying data using a non-partition column as a filter
B) When the table is partitioned on a column frequently used in query filters
C) When the partitioned table contains a small number of partitions
D) When querying data using the exact partition key in the WHERE clause

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