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Data-Related Issues Encountered - handling skewed data

Spark/Big Datamedium0.4 min readPremium
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Asked at 1 company
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questions in Spark/Big Data
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in this category
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1,863
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Asked at these companies
Lumiq
Key Concepts Tested
partitionspark
Expert AnswerPremium
81 wordsInterview-ready
**Why skew matters**: Uneven partition sizes = stragglers; one partition 10x others = 90% resources idle. **Resolutions**: (1) **Salting**—add random suffix to key, redistribute, aggregate, then merge. (2) **Broadcast**—small dimension, avoid shuffle. (3) **Split hot keys**—e.g., user_id 12345 → 12345_0, 12345_1. (4) **AQE**—Spark 3.x can detect skew. **Scalability trade-offs**: Salting adds complexity; broadcast has size limit....
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