| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4950121 | Future Generation Computer Systems | 2018 | 38 Pages |
Abstract
We employ six Spark programs, each with five input data sets to evaluate the performance improvements. The results show that ACS speeds up the 30 program-input pairs by a factor of 2.2Ã on average and up to 8.2Ã. In addition, the performance improvements obtained by ACS increase along with the increments of the input data set sizes of Spark workloads, which is a nice property for big data analytics.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Zhendong Bei, Zhibin Yu, Ni Luo, Chuntao Jiang, Chengzhong Xu, Shengzhong Feng,