Your question is Spark Internals and Transformations. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain Spark internals and how transformations and actions work under the hood, including what you would tune to improve performance.
Cover the driver, executors, jobs, stages, tasks, DAG construction, lazy evaluation, narrow and wide transformations, shuffle behavior, and fault recovery. Use a practical example to explain how you would diagnose and improve a slow Spark pipeline, including relevant Spark UI metrics, partitioning, caching, serialization, joins, data skew, and resource configuration.