MapReduce: Execution Models for Distributed Computing

This lecture introduces the MapReduce programming model for distributed computing, focusing on its vision, sample applications like word-count, and under-the-hood mechanisms like shuffling and reducing. It discusses the simplicity and complexity of distributed computation, the challenges with MapReduce, and its impact on big data processing.