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MapSQ: A Plugin-based MapReduce Framework for SPARQL Queries on GPU

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Lei ZouAuthors Info & Claims

WWW '18: Companion Proceedings of the The Web Conference 2018

Pages 81 - 82

https://doi.org/10.1145/3184558.3186939

Published: 23 April 2018 Publication History

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Abstract

In this paper, we present a plugin-based framework (MapSQ) with three parts for SPARQL queries utilizing high-performance of GPU to accelerate answering in a convenient way. Selector chooses suitable join order according to characteristics of data and queries. Executor answers subqueries and returns intermediate solutions and GPU Computing obtains the join result of intermediate solutions through MapReduce. Finally, we evaluate MapSQ bulit on gStore and RDF-3X on the LUBM benchmark and YAGO datasets (over 200 million triples). The experimental results show that MapSQ significantly improves the performance of SPARQL query engines with speedup up to 33.

References

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Abdelaziz I., Harbi R., Khayyat Z., and Kalnis P. 2017. A survey and experimental comparison of distributed SPARQL engines for very large RDF data. PVLDB. 10(13): 2049--2060.

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Chen L., Zsu M.T., Zou L., Mo J., and Zhao D. 2011. gStore: Answering SPARQL queries via subgraph matching. PVLDB. 4(8):482--493.

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Guo Y., Liu W., Voss G.,and Mueller-Wittig W. 2014. GCMR: A GPU cluster-based MapReduce framework for large-scale data processing Proc. of HPCC & EUC'14. 580--586.

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Kaldewey T., Lohman G., and Mueller R. 2012. GPU Join processing revisited Proc. of EDBT'12. pp.55--62.

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Weikum G. and Neumann T. 2008. RDF-3X: A RISC-style engine for RDF. PVLDB. 1(1):647--659.

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Cited By

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Yu MQin LZhang YZhang WLin X(2021)DPTL+: Efficient Parallel Triangle Listing on Batch-Dynamic Graphs2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00119(1332-1343)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00119
Zhang XZhang MPeng PSong JFeng ZZou L(2019)A Scalable Sparse Matrix-Based Join for SPARQL Query ProcessingDatabase Systems for Advanced Applications10.1007/978-3-030-18590-9_77(510-514)Online publication date: 22-Apr-2019
https://dl.acm.org/doi/10.1007/978-3-030-18590-9_77

Index Terms

MapSQ: A Plugin-based MapReduce Framework for SPARQL Queries on GPU
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
        Query optimization

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Information & Contributors

Information

Published In

WWW '18: Companion Proceedings of the The Web Conference 2018

April 2018

2023 pages

ISBN:9781450356404

General Chairs:
Pierre-Antoine Champin
Université Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, CNRS, LIRIS, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

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]

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 23 April 2018

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Poster

Funding Sources

National Key Research and Development Program of China
National Natural Science Foundation of China

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WWW '18

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IW3C2

WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Yu MQin LZhang YZhang WLin X(2021)DPTL+: Efficient Parallel Triangle Listing on Batch-Dynamic Graphs2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00119(1332-1343)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00119
Zhang XZhang MPeng PSong JFeng ZZou L(2019)A Scalable Sparse Matrix-Based Join for SPARQL Query ProcessingDatabase Systems for Advanced Applications10.1007/978-3-030-18590-9_77(510-514)Online publication date: 22-Apr-2019
https://dl.acm.org/doi/10.1007/978-3-030-18590-9_77

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H2RDF: adaptive query processing on RDF data in the cloud.

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