TECH NEWS
MapReduce: The Abstraction Layer That Still Shapes How AI Workloads Scale
Every large-scale data pipeline faces the same fundamental challenge: how do you process terabytes of data across thousands of machines without drowning in the operational complexity of coordination, failure recovery, and load balancing? In 2004, Jeffrey Dean and Sanjay Ghemawat addressed this with their paper "MapReduce: Simplified Data Processing