Distributed R is an open source, high-performance platform for the R language. It splits tasks between multiple processing nodes to reduce execution time and analyze large data sets. Distributed R enhances R by adding distributed data-structures, parallelism primitives to run functions on distributed data, a task scheduler, and multiple data loaders. It is primarily used to implement distributed versions of machine learning tasks.