A demonstration of Lusail - Querying linked data at scale

Essam Mansour, Ibrahim Abdelaziz, Mourad Ouzzani, Ashraf Aboulnaga, Panos Kalnis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

There has been a proliferation of datasets available as interlinked RDF data accessible through SPARQL endpoints. This has led to the emergence of various applications in life science, distributed social networks, and Internet of Things that need to integrate data from multiple endpoints. We will demonstrate Lusail; a system that supports the need of emerging applications to access tens to hundreds of geo-distributed datasets. Lusail is a geo-distributed graph engine for querying linked RDF data. Lusail delivers outstanding performance using (i) a novel locality-aware query decomposition technique that minimizes the intermediate data to be accessed by the subqueries, and (ii) selectivityawareness and parallel query execution to reduce network latency and to increase parallelism. During the demo, the audience will be able to query actually deployed RDF endpoints as well as large synthetic and real benchmarks that we have deployed in the public cloud. The demo will also show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.

Original languageEnglish
Title of host publicationSIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages1603-1606
Number of pages4
VolumePart F127746
ISBN (Electronic)9781450341974
DOIs
Publication statusPublished - 9 May 2017
Event2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017 - Chicago, United States
Duration: 14 May 201719 May 2017

Other

Other2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017
CountryUnited States
CityChicago
Period14/5/1719/5/17

Fingerprint

Demonstrations
Scalability
Engines
Decomposition
Internet of things

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Mansour, E., Abdelaziz, I., Ouzzani, M., Aboulnaga, A., & Kalnis, P. (2017). A demonstration of Lusail - Querying linked data at scale. In SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data (Vol. Part F127746, pp. 1603-1606). Association for Computing Machinery. https://doi.org/10.1145/3035918.3058731

A demonstration of Lusail - Querying linked data at scale. / Mansour, Essam; Abdelaziz, Ibrahim; Ouzzani, Mourad; Aboulnaga, Ashraf; Kalnis, Panos.

SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Vol. Part F127746 Association for Computing Machinery, 2017. p. 1603-1606.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mansour, E, Abdelaziz, I, Ouzzani, M, Aboulnaga, A & Kalnis, P 2017, A demonstration of Lusail - Querying linked data at scale. in SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. vol. Part F127746, Association for Computing Machinery, pp. 1603-1606, 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017, Chicago, United States, 14/5/17. https://doi.org/10.1145/3035918.3058731
Mansour E, Abdelaziz I, Ouzzani M, Aboulnaga A, Kalnis P. A demonstration of Lusail - Querying linked data at scale. In SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Vol. Part F127746. Association for Computing Machinery. 2017. p. 1603-1606 https://doi.org/10.1145/3035918.3058731
Mansour, Essam ; Abdelaziz, Ibrahim ; Ouzzani, Mourad ; Aboulnaga, Ashraf ; Kalnis, Panos. / A demonstration of Lusail - Querying linked data at scale. SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Vol. Part F127746 Association for Computing Machinery, 2017. pp. 1603-1606
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