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Executor vs Driver in Spark

Spark/Big Dataeasy0.4 min readPremium

**Why distinction matters**: Driver OOM vs Executor OOM have different causes and fixes. **Driver**: Single process; runs main(); builds DAG; schedules; collects results. Bottleneck for collect(), take(). **Executor**: Workers; run tasks; store cached data. Do the heavy lifting....

🤖 Analyze Your Answer
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
Presidio
Key Concepts Tested
spark

Why This Question Matters

This easy-level Spark/Big Data question appears frequently in data engineering interviews at companies like Presidio. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (spark) will help you answer variations of this question confidently.

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Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
74 words

Why distinction matters: Driver OOM vs Executor OOM have different causes and fixes. Driver: Single process; runs main(); builds DAG; schedules; collects results. Bottleneck for collect(), take(). Executor: Workers; run tasks; store cached data. Do the heavy lifting. Scalability trade-offs: Driver = single point; executors scale. collect() on large = driver OOM. Cost implications: Over-sized driver = waste; undersized = OOM. Best practice: Keep driver small; avoid collect on large; size executors for workload.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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