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Persistence Storage Levels: When to use MEMORY_ONLY, MEMORY_AND_DISK, etc.

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
Daniel Wellington
Key Concepts Tested
optimizationpartition
Expert AnswerPremium
72 wordsInterview-ready
**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. Storage levels: MEMORY_ONLY—fast, no spill; use when fits. MEMORY_AND_DISK—spill excess to disk. MEMORY_ONLY_SER—serialized, less memory. MEMORY_AND_DISK_SER—serialized + spill. DISK_ONLY—large, rarely reused....
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 Daniel Wellington. The answer also includes follow-up discussion points that interviewers commonly explore.

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