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Data & Analytics · Intermediate

MapReduce

A programming model that processes large datasets in parallel with a map phase producing key-value pairs and a reduce phase aggregating them.

Definition

MapReduce writes intermediate results to disk between stages, which makes it slower than Spark's in-memory processing for iterative workloads. The shuffle between map and reduce is its most expensive step.

Example

Word count: map emits (word, 1), reduce sums the counts per word.

Exam tip

Spark is faster than MapReduce mainly because it keeps intermediate data in memory.

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