Nanotechnology research and application often involve the collection and analysis of enormous data sets. For instance, characterizing the properties of nanoparticles or simulating molecular dynamics can generate terabytes to petabytes of data. MapReduce provides an efficient and scalable framework for processing these large data sets. By partitioning data and distributing tasks across multiple nodes, it ensures faster and more efficient data handling and analysis.
