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What causes data skewness in Spark, and how can it be resolved?

Spark/Big Datamedium0.5 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
PWC
Key Concepts Tested
joinpartitionspark
Expert AnswerPremium
94 wordsInterview-ready
**Causes**: Uneven key distribution. Null, default, or popular keys (e.g., tenant_id=0, country=US) dominate. **Solutions**: (1) **Salting**—add random suffix; distribute; merge. (2) **Two-phase aggregate**—partial agg, then final. (3) **AQE skew join**—Spark 3.x splits large partitions. (4) **Filter skewed keys**—process separately; union. (5) **Increase shuffle partitions**—marginal; doesn't fix severe skew. **Why It Matters**: One task runs 10x longer; stage waits for straggler....
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