**Why DAG Scheduler matters**: Translates logical plan to execution; stage boundaries drive optimization. **Role**: Takes RDD DAG; splits into stages at shuffle boundaries; schedules tasks on executors. Handles locality, failures. Part of SparkContext. **Scalability trade-offs**: Stage count affects scheduling overhead; optimize shuffle boundaries. **Cost implications**: Understanding stages = identify bottleneck....
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