DAG-Aware Optimization for Geo-Distributed Data Analytics
Q.G. Wang, Bin Gao, Zhi Zhou, Fei Xu, Chenghao Ouyang · 2023
Geo-distributed data analytics has been proposed to analyze geographically distributed data. Existing studies have achieved significant reductions in execution time and data transfer cost ($) of data analytics jobs by optimizing task placement. Given a directed acyclic graph (DAG)-style job, however, they mainly optimize each stage independently, and they tend to distribute tasks and intermediate data across all locations, potentially inflating execution time and data transfer cost of descendent stages and the whole job.