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What is the difference between map and flatMap in Spark transformations?

Spark/Big Dataeasy0.4 min readPremium
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Asked at 1 company
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Asked at these companies
Coforge
Key Concepts Tested
spark
Expert AnswerPremium
73 wordsInterview-ready
**map**: 1:1. Each input → one output. `map(x => f(x))`. **flatMap**: 1:N. Each input → 0 or more outputs. Returns iterable; flattened. `flatMap(x => list)`. **Example**: map(s => s.split(" ")) → [["a","b"], ["c"]]. flatMap(s => s.split(" ")) → ["a","b","c"]. **Use Cases**: flatMap for tokenization, explode, one-to-many. map for 1:1 transform. **Scalability Trade-offs**: flatMap can explode row count; one row → 100....
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