Article

RMLStreamer-SISO: An RDF Stream Generator from Streaming Heterogeneous Data

Authors:

Gerald Haesendonck,

Ben De Meester,

Anastasia DimouAuthors Info & Claims

The Semantic Web – ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022, Proceedings

Pages 697 - 713

https://doi.org/10.1007/978-3-031-19433-7_40

Published: 23 October 2022 Publication History

Abstract

Stream-reasoning query languages such as CQELS and C-SPARQL enable query answering over RDF streams. Unfortunately, there currently is a lack of efficient RDF stream generators to feed RDF stream reasoners. State-of-the-art RDF stream generators are limited with regard to the velocity and volume of streaming data they can handle. To efficiently generate RDF streams in a scalable way, we extended the RMLStreamer to also generate RDF streams from dynamic heterogeneous data streams. This paper introduces a scalable solution that relies on a dynamic window approach to generate RDF streams with low latency and high throughput from multiple heterogeneous data streams. Our evaluation shows that our solution outperforms the state-of-the-art by achieving millisecond latency (compared to seconds that state-of-the-art solutions need), constant memory usage for all workloads, and sustainable throughput of around 70,000 records/s (compared to 10,000 records/s that state-of-the-art solutions take). This opens up the access to numerous data streams for integration with the semantic web.

Resource type: Software

License: MIT License

URL: https://github.com/RMLio/RMLStreamer/releases/tag/v2.3.0

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Cited By

Freund MSchmid SDorsch RHarth A(2024)FlexRML: A Flexible and Memory Efficient Knowledge Graph MaterializerThe Semantic Web10.1007/978-3-031-60635-9_3(40-56)Online publication date: 26-May-2024
https://dl.acm.org/doi/10.1007/978-3-031-60635-9_3
Arenas-Guerrero JAlobaid ANavas-Loro MPérez MCorcho O(2023)Boosting Knowledge Graph Generation from Tabular Data with RML ViewsThe Semantic Web10.1007/978-3-031-33455-9_29(484-501)Online publication date: 28-May-2023
https://dl.acm.org/doi/10.1007/978-3-031-33455-9_29

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RMLStreamer-SISO: An RDF Stream Generator from Streaming Heterogeneous Data

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Published In

cover image Guide Proceedings

The Semantic Web – ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022, Proceedings

Oct 2022

898 pages

ISBN:978-3-031-19432-0

DOI:10.1007/978-3-031-19433-7

Editors:
Ulrike Sattler
University of Manchester, Manchester, UK
,
Aidan Hogan
University of Chile, Santiago, Chile
,
Maria Keet
University of Cape Town, Cape Town, South Africa
,
Valentina Presutti
University of Bologna, Bologna, Italy
,
João Paulo A. Almeida
Universidade Federal do Espírito Santo, Vitória, Brazil
,
Hideaki Takeda
National Institute of Informatics, Tokyo, Japan
,
Pierre Monnin
Orange, Belfort, France
,
Giuseppe Pirrò
Sapienza University of Rome, Rome, Italy
,
Claudia d’Amato
University of Bari, Bari, Italy

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 23 October 2022

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Cited By

Freund MSchmid SDorsch RHarth A(2024)FlexRML: A Flexible and Memory Efficient Knowledge Graph MaterializerThe Semantic Web10.1007/978-3-031-60635-9_3(40-56)Online publication date: 26-May-2024
https://dl.acm.org/doi/10.1007/978-3-031-60635-9_3
Arenas-Guerrero JAlobaid ANavas-Loro MPérez MCorcho O(2023)Boosting Knowledge Graph Generation from Tabular Data with RML ViewsThe Semantic Web10.1007/978-3-031-33455-9_29(484-501)Online publication date: 28-May-2023
https://dl.acm.org/doi/10.1007/978-3-031-33455-9_29

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