Is Intel high performance analytics toolkit a good alternative to Apache Spark?

摘要

This paper compares the performance and stability of two Big Data processing tools: the Apache Spark and the High Performance Analytics Toolkit (HPAT). The comparison was performed using two applications: a unidimensional vector sum and the K-means clustering algorithm. The experiments were performed in distributed and shared memory environments with different numbers and configurations of virtual machines. By analyzing the results we are able to conclude that HPAT has performance improvements in relation to Apache Spark in our case studies. We independently validated the results and potential presented by the HPAT developers. We also provide an analysis of both frameworks in the presence of failures.