**Map**: 1:1 transformation. Each input produces one output. Narrow dependency—no shuffle. Examples: `map`, `filter`, `flatMap`.
**Reduce**: N:1 aggregation. Combines elements; may require shuffle for global aggregation. Wide dependency. Examples: `reduce`, `reduceByKey`, `aggregate`.
**Why reduceByKey > groupByKey**: reduceByKey does map-side combine first; less data shuffled. groupByKey shuffles all values.
**Scalability Trade-offs**: Map scales linearly with partitions....
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