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Explain Spark Architecture – Driver, Executors, and Tasks.

Spark/Big Datahard3.6 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Datametica
Key Concepts Tested
optimizationpartitionspark
Expert AnswerPremium
724 wordsIncludes code examplesInterview-ready
**Section 1 — The Context (The 'Why')** Spark's driver-executor architecture creates a single point of coordination: the driver builds the DAG and schedules tasks, while executors perform the actual work. Driver OOM from collect() or executor OOM from data skew are common production failures. A naive fix—increasing driver memory for an executor skew problem—wastes cost and does not solve the root cause....
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 Datametica. The answer also includes follow-up discussion points that interviewers commonly explore.

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