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What causes Out of Memory (OOM) issues in Databricks, and how do you resolve them?

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
partitionspark
Expert AnswerPremium
105 wordsInterview-ready
**Driver OOM**: (1) `collect()` on large DF. (2) Schema inference on huge file. (3) Large broadcast. Fix: Avoid collect; use limit or write+read. Provide schema. Reduce broadcast threshold. **Executor OOM**: (1) Data skew—one partition huge. (2) Too few partitions; each too large. (3) Spill disabled or disk full. Fix: Salting; repartition; enable spill; increase partitions. **Why It Happens**: Memory < data per partition....
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