**Process**: (1) Driver parses code, builds DAG. (2) DAG sent to cluster manager (YARN/K8s). (3) Manager allocates executors. (4) Driver splits DAG into stages (wide boundaries). (5) Tasks sent to executors. (6) Executors run, report back. (7) Driver collects results for actions. (8) Next stage until done.
**Why Stages**: Wide transformations require shuffle; can't proceed until previous stage completes.
**Scalability Trade-offs**: Driver single point; cluster deploy for resilience....
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 Dunnhumby. The answer also includes follow-up discussion points that interviewers commonly explore.
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