**Partitioning**: repartition by join key before shuffle; coalesce before write. Match partition count to 2–4x cores.
**Broadcast**: Small tables < 100MB; no shuffle.
**Cache**: Reused DFs; unpersist when done.
**Predicate/Column Pruning**: Filter and select early; push to source.
**AQE**: Enable; coalesce, skew join, broadcast switch.
**Salting**: For skewed keys.
**Avoid UDFs**: Built-in or pandas_udf.
**Executor Tuning**: 4–8 cores, 8–16GB; avoid huge executors (GC)....
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 Coforge. The answer also includes follow-up discussion points that interviewers commonly explore.
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