research-article

Online Partitioning of Multi-Labeled Graphs

Authors:

Ioanna Filippidou,

Yannis KotidisAuthors Info & Claims

GRADES'15: Proceedings of the GRADES'15

Article No.: 3, Pages 1 - 6

https://doi.org/10.1145/2764947.2764950

Published: 31 May 2015 Publication History

Abstract

Graph partitioning is an old problem that is finding renewed interest in the era of big, complex datasets and parallel computing frameworks that can benefit from a proper partitiong of big graph data across multiple nodes in a cluster. In this paper we look into a specific instance of the problem termed online graph partitioning that addresses the need to partition large graphs that do not fit in main memory. A neglected aspect of modern graph datasets is that real graphs have labels! Node labels may, for instance, correspond to categorical attributes (such as country, profession, participating groups, etc.) of the entities depicted by the vertices of the graph. Edge labels may represent different relationship types (e.g. "friend-of", "likes", etc.). In this work we first revisit the formulation of the graph partitioning problem for graphs with labels on both nodes and edges. We introduce "relation-cut", as a new metric that extends the traditional "edge-cut" metric used in graph partitioning in order to take into account the existence of different edge-types. Then, we combine this metric with a novel "label-cut" metric that takes into consideration the displacement of related nodes with similar labels across partitions. In our experiments we adapt two recent online partitioning algorithms for the new proposed metric and provide a thorough evaluation on a variety of real and synthetic graphs. Our experiments demonstrate that the proposed technique balances the generated cuts on both relations and labels on the resulting partitions.

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Cited By

Shan XShi XMa WWang J(2021)Distributed Storage and Query for Domain Knowledge GraphsWeb and Big Data. APWeb-WAIM 2020 International Workshops10.1007/978-981-16-0479-9_10(116-128)Online publication date: 1-Apr-2021
https://doi.org/10.1007/978-981-16-0479-9_10
Shan XShi XSong YZhang MSong B(2020)Dynamic Partition of Large Graphs Combining Local Nodes Exchange with Directed Dynamic MaintenanceWeb Information Systems and Applications10.1007/978-3-030-60029-7_40(441-453)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60029-7_40
Spyropoulos VVasilakopoulou CKotidis Y(2016)Digree: A middleware for a graph databases polystore2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840900(2580-2589)Online publication date: Dec-2016
https://doi.org/10.1109/BigData.2016.7840900
Show More Cited By

Index Terms

Online Partitioning of Multi-Labeled Graphs
1. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory
      1. Graph algorithms
      2. Graph enumeration

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cover image ACM Conferences

GRADES'15: Proceedings of the GRADES'15

May 2015

54 pages

ISBN:9781450336116

DOI:10.1145/2764947

Copyright © 2015 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 the author(s) 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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SIGMOD: ACM Special Interest Group on Management of Data

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Publication History

Published: 31 May 2015

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SIGMOD/PODS'15

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SIGMOD/PODS'15: International Conference on Management of Data

May 31 - June 4, 2015

VIC, Melbourne, Australia

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Cited By

Shan XShi XMa WWang J(2021)Distributed Storage and Query for Domain Knowledge GraphsWeb and Big Data. APWeb-WAIM 2020 International Workshops10.1007/978-981-16-0479-9_10(116-128)Online publication date: 1-Apr-2021
https://doi.org/10.1007/978-981-16-0479-9_10
Shan XShi XSong YZhang MSong B(2020)Dynamic Partition of Large Graphs Combining Local Nodes Exchange with Directed Dynamic MaintenanceWeb Information Systems and Applications10.1007/978-3-030-60029-7_40(441-453)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60029-7_40
Spyropoulos VVasilakopoulou CKotidis Y(2016)Digree: A middleware for a graph databases polystore2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840900(2580-2589)Online publication date: Dec-2016
https://doi.org/10.1109/BigData.2016.7840900
Filippidou IKotidis Y(2016)Effective and efficient graph augmentation in large graphs2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840681(875-880)Online publication date: Dec-2016
https://doi.org/10.1109/BigData.2016.7840681

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