The Future is Big Graphs! A Community View on Graph Processing Systems
Distributed, Parallel, and Cluster Computing
2020-12-14 v1 Databases
Abstract
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?
Cite
@article{arxiv.2012.06171,
title = {The Future is Big Graphs! A Community View on Graph Processing Systems},
author = {Sherif Sakr and Angela Bonifati and Hannes Voigt and Alexandru Iosup and Khaled Ammar and Renzo Angles and Walid Aref and Marcelo Arenas and Maciej Besta and Peter A. Boncz and Khuzaima Daudjee and Emanuele Della Valle and Stefania Dumbrava and Olaf Hartig and Bernhard Haslhofer and Tim Hegeman and Jan Hidders and Katja Hose and Adriana Iamnitchi and Vasiliki Kalavri and Hugo Kapp and Wim Martens and M. Tamer Özsu and Eric Peukert and Stefan Plantikow and Mohamed Ragab and Matei R. Ripeanu and Semih Salihoglu and Christian Schulz and Petra Selmer and Juan F. Sequeda and Joshua Shinavier and Gábor Szárnyas and Riccardo Tommasini and Antonino Tumeo and Alexandru Uta and Ana Lucia Varbanescu and Hsiang-Yun Wu and Nikolay Yakovets and Da Yan and Eiko Yoneki},
journal= {arXiv preprint arXiv:2012.06171},
year = {2020}
}
Comments
12 pages, 3 figures, collaboration between the large-scale systems and data management communities, work started at the Dagstuhl Seminar 19491 on Big Graph Processing Systems, to be published in the Communications of the ACM