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Explain the architecture of Spark, including its components such as driver, executor, and cluster manager.

Spark/Big Datahard2.6 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
Capgemini
Key Concepts Tested
optimizationpartitionspark
Expert AnswerPremium
512 wordsIncludes code examplesInterview-ready
**Section 1 — The Context (The 'Why')** Spark driver schedules; executors execute. Cluster manager allocates. Mis-sizing driver wastes money. Executor OOM from skew differs from driver OOM from collect(). **Section 2 — The Diagram** ``` [Driver] <-> [Cluster Mgr] | v [DAG] --> [Stages] | v [Executors] [Tasks] ``` **Section 3 — Component Logic** **Driver** builds DAG, schedules stages. **Cluster Manager** allocates executors. **Executors** run tasks, cache RDDs....
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 Capgemini. The answer also includes follow-up discussion points that interviewers commonly explore.

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