MapReduce is a programming model designed for processing large datasets in a distributed computing environment. Introduced by Google in 2004, it allows for the efficient handling of vast amounts of data by breaking down tasks into smaller, manageable components. The model consists of two primary functions: the “Map” function, which processes input data and generates key-value pairs, and the “Reduce” function, which aggregates these pairs to produce a final output. This approach enables parallel processing across multiple machines, enhancing scalability and fault tolerance, making it a cornerstone of big data processing frameworks like Hadoop and Spark.