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What is Shuffle and How to Handle It in Spark

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
Nagarro
Key Concepts Tested
joinpartitionspark
Expert AnswerPremium
101 wordsInterview-ready
**Shuffle**: Redistribution for groupBy, join, distinct. Wide transformation; data moves across network. Expensive—serialization, network, disk. **Handle**: (1) **Reduce data**—select only needed columns before shuffle. (2) **Broadcast** small tables. (3) **Partition by key** when writing—next read avoids shuffle. (4) **Repartition** before multiple shuffles—one repartition vs. many. (5) **Coalesce** after filter to reduce output. (6) **Salting** for skew....
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