Your Spark application on Kubernetes requires a secure connection to a database. You've stored the database password in Kubernetes Secrets. How would you typically access this secret in your PySpark application?
You need to filter data from a Hive table based on a specific date range. Which approach would be most efficient and maintainable?
Which security feature offered by the Cloudera Data Engineering service allows granular access control to data pipelines and resources?
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?
Your Airflow DAG involves sending notifications upon successful completion of the entire pipeline. How can you achieve this functionality?
