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Community-based RDF graph partitioning

Abstract:

A common approach to processing large RDF datasets is to partition the data in a cluster of shared-nothing servers and then use a distributed query evaluation algorithm. It is commonly assumed in the literature that the performance of query processing in such systems is limited mainly by network communication. In this paper, we show that this assumption does not always hold: we present a new RDF partitioning method based on Louvain community detection, which drastically reduces communication,...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
http://ceur-ws.org/Vol-2757/

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Institution:
University of Oxford
Division:
ContEd
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0003-2506-4118
Publisher:
CEUR Workshop Proceedings Publisher's website
Volume:
2757
Pages:
33-48
Host title:
SSWS 2020: Scalable Semantic Web Knowledge Base Systems
Publication date:
2020-12-02
Acceptance date:
2020-09-13
Event title:
SSWS 2020: 13th International Workshop on Scalable Semantic Web Knowledge Base Systems
Event location:
Athens, Greece
Event website:
http://www.ssws-ws.org/SSWS2020/index.html
Event start date:
2020-11-02T00:00:00Z
Event end date:
2020-11-02T00:00:00Z
ISSN:
1613-0073
Language:
English
Keywords:
Pubs id:
1132717
Local pid:
pubs:1132717
Deposit date:
2020-09-18

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