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Cloudera CDP Data Engineer - Certification Sample Questions:

1. 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 partitioned table contains a small number of partitions
C) When querying data using the exact partition key in the WHERE clause
D) When the table is partitioned on a column frequently used in query filters

2. Your team is deploying a Spark application on a Kubernetes cluster. To ensure high availability, you need to decide how many executor instances to configure. Which of the following configurations in your PySpark application would correctly set the number of executor instances?

A)

B)

C)

D)

3. You're deploying your Airflow DAGs to a production environment. What are some best practices to ensure reliability and maintainability?

A) Schedule DAGs to run as frequently as possible to ensure real-time data processing.
B) Use the same Airflow environment for development, testing, and production deployments.
C) Implement version control for your DAG code and configuration files to track changes and facilitate rollbacks.
D) Grant full access to the Airflow web UI to everyone for monitoring and troubleshooting purposes.

4. Discuss the trade-offs between using wide tables (many columns) and narrow tables (few columns) in Spark and the implications for data processing efficiency.

A) Wide tables require more storage and may lead to performance overhead due to data serialization.
B) Wide tables offer better performance for filtering operations, while narrow tables excel in aggregations.
C) Both A and C.
D) Spark can optimize data access patterns for both wide and narrow tables equally.

5. You're deploying your Airflow DAGs to a production environment. What are some key considerations for ensuring security and reliability?

A) Schedule DAG runs as frequently as possible to ensure real-time data processing.
B) Configure Airflow to run with high resource limits to handle unexpected spikes in workload.
C) Implement role-based access control (RBAC. to restrict access to sensitive DAGs and resources.
D) Disable task logging to improve DAG execution performance.

Solutions: