In 2004, Google published a research paper by Jeffrey Dean and Sanjay Ghemawat that introduced MapReduce, a simple yet powerful programming model for processing and generating large datasets.

The idea was so transformative that it became the backbone of the open-source Apache Hadoop project and inspired a new generation of big data frameworks like Apache Spark and Flink.

At its heart, MapReduce takes a massive problem, breaks it into smaller, independent pieces, processes them in parallel, and then aggregates the results.

1. Why MapReduce Was Needed