MapReduce is a batch processing model for splitting large data jobs across a cluster. Developers write map and reduce functions; the runtime handles partitioning, shuffle, retries, and output.

Raw MapReduce is no longer the default for most new systems, but its execution model still explains core distributed data ideas: data locality, deterministic retry, shuffle cost, and batch fault tolerance.

In this chapter, you will learn: