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The Future is Big Graphs! A Community View on Graph Processing Systems

Authors :
Sakr, Sherif
Bonifati, Angela
Voigt, Hannes
Iosup, Alexandru
Ammar, Khaled
Angles, Renzo
Aref, Walid
Arenas, Marcelo
Besta, Maciej
Boncz, Peter A.
Daudjee, Khuzaima
Della Valle, Emanuele
Dumbrava, Stefania
Hartig, Olaf
Haslhofer, Bernhard
Hegeman, Tim
Hidders, Jan
Hose, Katja
Iamnitchi, Adriana
Kalavri, Vasiliki
Kapp, Hugo
Martens, Wim
Özsu, M. Tamer
Peukert, Eric
Plantikow, Stefan
Ragab, Mohamed
Ripeanu, Matei R.
Salihoglu, Semih
Schulz, Christian
Selmer, Petra
Sequeda, Juan F.
Shinavier, Joshua
Szárnyas, Gábor
Tommasini, Riccardo
Tumeo, Antonino
Uta, Alexandru
Varbanescu, Ana Lucia
Wu, Hsiang-Yun
Yakovets, Nikolay
Yan, Da
Yoneki, Eiko
Publication Year :
2020

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?<br />Comment: 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

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2012.06171
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3434642