MapReduce is a programming model designed for processing large data sets across distributed computing environments. Originally developed by Google in 2004, it allows for the efficient execution of parallel tasks on clusters of computers. The model consists of two primary functions: the “Map” function, which processes input data and produces key-value pairs, and the “Reduce” function, which aggregates these pairs to generate a final output. This approach simplifies the complexities of parallelization, fault tolerance, and data distribution, making it accessible even for programmers with limited experience in distributed systems. MapReduce has been widely popularized through frameworks like Hadoop.