Before revision:  For the first time, we identify eight big data dwarfs, each of which captures the common requirements of each class of unit of computation  while being reasonably divorced from individual implementations  among a wide variety of big data analytics workloads .
After revision:  For the first time, we identify eight big data dwarfs, each of which captures the common requirements of each class of unit of computation while being reasonably divorced from individual implementations among a wide variety of big data and AI workloads, we identify eight data dwarfs that takes up most of run time, including Matrix, Sampling, Logic, Transform, Set, Graph, Sort and Statistic .