Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs

Abstract

The rapid growth in the volume of many real-world graphs (e.g., social networks, web graphs, and spatial networks) has led to the development of various vertex-centric distributed graph computing systems in recent years. However, real-world graphs from different domains have very different characteristics, which often create bottlenecks in vertex-centric parallel graph computation. We identify three such important characteristics from a wide spectrum of real-world graphs, namely (1)skewed degree distribution, (2)large diameter, and (3)(relatively) high density. Among them, only (1) has been studied by existing systems, but many real-world powerlaw graphs also exhibit the characteristics of (2) and (3). In this paper, we propose a block-centric framework, called Blogel, which naturally handles all the three adverse graph characteristics. Blogel programmers may think like a block and develop efficient algorithms for various graph problems. We propose parallel algorithms to partition an arbitrary graph into blocks efficiently, and blockcentric programs are then run over these blocks. Our experiments on large real-world graphs verified that Blogel is able to achieve orders of magnitude performance improvements over the state-ofthe-art distributed graph computing systems.

Extracted Key Phrases

12 Figures and Tables

020402014201520162017
Citations per Year

92 Citations

Semantic Scholar estimates that this publication has 92 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Yan2014BlogelAB, title={Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs}, author={Da Yan and James Cheng and Yi Lu and Wilfred Ng}, journal={PVLDB}, year={2014}, volume={7}, pages={1981-1992} }