Experimental Analysis of Distributed Graph Systems

June 21, 2018 · Declared Dead · 🏛 Proceedings of the VLDB Endowment

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Authors Khaled Ammar, Tamer Ozsu arXiv ID 1806.08082 Category cs.DC: Distributed Computing Citations 35 Venue Proceedings of the VLDB Endowment Last Checked 3 months ago
Abstract
This paper evaluates eight parallel graph processing systems: Hadoop, HaLoop, Vertica, Giraph, GraphLab (PowerGraph), Blogel, Flink Gelly, and GraphX (SPARK) over four very large datasets (Twitter, World Road Network, UK 200705, and ClueWeb) using four workloads (PageRank, WCC, SSSP and K-hop). The main objective is to perform an independent scale-out study by experimentally analyzing the performance, usability, and scalability (using up to 128 machines) of these systems. In addition to performance results, we discuss our experiences in using these systems and suggest some system tuning heuristics that lead to better performance.
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