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Spark Executor Management: 10 workers, 100GB RAM, 25 cores - number of executors, size, OOM in Driver

Spark/Big Datahard0.4 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
Meesho
Key Concepts Tested
optimizationpartitionspark
Expert AnswerPremium
82 wordsInterview-ready
**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. 10 workers, 100GB RAM, 25 cores: ~10 executors (1 per worker), 4 cores each, 8-10GB each. Leave 1 core + 1-2GB for OS. Driver: 4-8GB. Avoid OOM: increase partitions; reduce memory per executor; check for collect()....
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 Meesho. The answer also includes follow-up discussion points that interviewers commonly explore.

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