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How do you decide the number of partitions for repartitioning data in Spark?

Spark/Big Datahard0.4 min readPremium
Frequency
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Asked at 1 company
Category
452
questions in Spark/Big Data
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88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
PWC
Key Concepts Tested
optimizationpartitionsparksql
Expert AnswerPremium
88 wordsInterview-ready
**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. Partition count: target 100–200MB per partition; total_partitions = data_size_MB / 150; or 2–4 times total cores. Rules: more for shuffle-heavy; fewer for small data. spark.sql.shuffle.partitions (default 200)....
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