Hadoop MapReduce

Hadoop MapReduce is a distributed computing framework designed to process massive datasets by parallelizing computations across a cluster of machines. Current research focuses on optimizing MapReduce for specific tasks, such as clustering algorithms (e.g., Minimum Sum-of-Squares Clustering) and subgroup discovery, often incorporating hybrid parallel approaches to enhance performance and scalability beyond traditional data parallelism. This framework remains significant for its ability to handle big data challenges in diverse fields, including medical image analysis, educational data mining, and general machine learning applications, improving efficiency and enabling analyses previously infeasible with sequential methods.