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Describe the role of a DAG Scheduler in PySpark

Spark/Big Datahard0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
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1,863
across 7 categories
Asked at these companies
Nielsen
Key Concepts Tested
optimizationspark
Expert AnswerPremium
64 wordsInterview-ready
**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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