Special Report: Parallelized R In-Memory Reduces Execution Time and Analyzes Large Data Sets
R is a leading programming language of data science, consisting of powerful functions to tackle problems related to big data processing. However, R running on a single node can only perform efficient data analysis on small data sets. Rapids Data's distributed R computing engine breaks through the single-machine restriction commonly encountered in the big data industry.
Please complete the form and download the report to learn how parallelized R in-memory reduces execution time and analyzes large data sets.