research-article

SGVCut: A Vertex-Cut Partitioning Tool for Random Walks-based Computations over Social Network graphs

Authors:

Camelia Constantin,

Cédric du MouzaAuthors Info & Claims

SSDBM '17: Proceedings of the 29th International Conference on Scientific and Statistical Database Management

Article No.: 39, Pages 1 - 4

https://doi.org/10.1145/3085504.3091114

Published: 27 June 2017 Publication History

Abstract

Several distributed frameworks have recently emerged to perform computations on large-scale graphs. However some recent studies have highlighted that vertex-partitioning approaches, e.g. Giraph, failed to achieve workload-balanced partitioning for skewed graphs, typically having a heavy-tail degree distribution. While edge-partitioning approaches such as PowerGraph and GraphX provide beter balancing and performances for graph computation, they supply a generic framework, independent from the computation. This demonstration presents SGVCut to display our edge partitions designed for random walks-based computation, which is the foundation of many graph algorithms, on skewed graphs. The demonstration scenario introduces SGVCut interface and illustrates the benefits of our approach compare to other partitioning strategies for different settings and algorithms.

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Cited By

Ayall TLiu HZhou CSeid AGereme FAbishu HYacob Y(2022)Graph Computing Systems and Partitioning Techniques: A SurveyIEEE Access10.1109/ACCESS.2022.321942210(118523-118550)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3219422
Li PZhou FXu ZLi YXu J(2020)Privacy-Preserving Graph Operations for Social Network AnalysisSecurity and Privacy in Social Networks and Big Data10.1007/978-981-15-9031-3_27(303-317)Online publication date: 22-Sep-2020
https://doi.org/10.1007/978-981-15-9031-3_27
Taimouri MSaadatfar H(2019)RBSEP: a reassignment and buffer based streaming edge partitioning approachJournal of Big Data10.1186/s40537-019-0257-56:1Online publication date: 19-Oct-2019
https://doi.org/10.1186/s40537-019-0257-5
Show More Cited By

Index Terms

SGVCut: A Vertex-Cut Partitioning Tool for Random Walks-based Computations over Social Network graphs
1. Computing methodologies
  1. Distributed computing methodologies
    1. Distributed algorithms

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cover image ACM Other conferences

SSDBM '17: Proceedings of the 29th International Conference on Scientific and Statistical Database Management

June 2017

373 pages

ISBN:9781450352826

DOI:10.1145/3085504

General Chair:
Alok Choudhary,
Program Chair:
Kesheng Wu,
Publications Chair:
Bin Dong

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Northwestern University: Northwestern University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 June 2017

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SSDBM '17

SSDBM '17: 29th International Conference on Scientific and Statistical Database Management

June 27 - 29, 2017

IL, Chicago, USA

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Overall Acceptance Rate 56 of 146 submissions, 38%

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Cited By

Ayall TLiu HZhou CSeid AGereme FAbishu HYacob Y(2022)Graph Computing Systems and Partitioning Techniques: A SurveyIEEE Access10.1109/ACCESS.2022.321942210(118523-118550)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3219422
Li PZhou FXu ZLi YXu J(2020)Privacy-Preserving Graph Operations for Social Network AnalysisSecurity and Privacy in Social Networks and Big Data10.1007/978-981-15-9031-3_27(303-317)Online publication date: 22-Sep-2020
https://doi.org/10.1007/978-981-15-9031-3_27
Taimouri MSaadatfar H(2019)RBSEP: a reassignment and buffer based streaming edge partitioning approachJournal of Big Data10.1186/s40537-019-0257-56:1Online publication date: 19-Oct-2019
https://doi.org/10.1186/s40537-019-0257-5
Zhao FShen YGui XJin H(2018)SDBPR: Social distance-aware Bayesian personalized ranking for recommendationFuture Generation Computer Systems10.1016/j.future.2018.12.052Online publication date: Dec-2018
https://doi.org/10.1016/j.future.2018.12.052

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