**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams.
Debug failing Spark job on Dataproc: (1) Check YARN/Spark logs in Cloud Console (Dataproc > Job > View Logs). (2) Spark driver logs—look for stack traces, OOM, serialization errors. (3) Executor logs—task failures, shuffle errors. (4) Enable `spark.eventLog.enabled` and review in History Server. (5) Reproduce locally with small data....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Aarete. The answer also includes follow-up discussion points that interviewers commonly explore.
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