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How do you handle data skewness in Spark?

Spark/Big Datamedium0.7 min readPremium
Frequency
Low
Asked at 2 companies
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
AccentureBitwise
Key Concepts Tested
joinpartitionsparksql
Expert AnswerPremium
146 wordsInterview-ready
Skew occurs when a few keys hold disproportionate data, causing hotspot tasks and stragglers. **Why it matters**: One task taking 10x longer blocks the entire stage; cluster utilization drops. **Strategies with trade-offs**: (1) **Salting**: Add random suffix to skewed keys; distributes load but requires two-phase aggregation (first with salt, then collapse). Cost: 2x shuffle....
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