Parallel Computing for Data Science

This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science. The book prepares readers to write effective parallel code in various languages and learn more about different R packages and other tools. It covers the classic "n observations, p variables" matrix format and common data structures. Many examples illustrate the range of issues encountered in parallel programming.