Your question is Spark Performance Bottlenecks. 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).
What are the common performance bottlenecks in Spark or distributed processing environments?
Discuss how you would identify bottlenecks using Spark UI, event logs, and infrastructure metrics. Cover data skew, excessive shuffles, poor partition sizing, inefficient joins, serialization overhead, disk spilling, insufficient resources, and slow input or output systems. Explain practical mitigations and the trade-offs between approaches. Include how you would validate an optimization without changing result correctness.
