Efficient fault-tolerance for iterative graph processing on distributed dataflow systems

Conference/Journal
IEEE
Authors
Chen Xu Markus Holzemer Manohar Kaul Volker Markl
BibTex
Abstract
Abstract: Real-world graph processing applications often require combining the graph data with tabular data. Moreover, graph processing usually is part of a larger analytics workflow consiting of data preparation, analysis and model building, and model application. General- purpose distributed dataflow frameworks execute all steps of such workflows holistically. This holistic view enables these systems to reason about and automatically optimize the processing. Most big graph processing algorithms are iterative and incur a long runtime, ...