RMLStreamer-SISO: an RDF stream generator from streaming heterogeneous data
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.
Keywords
Cite
@article{arxiv.2210.14599,
title = {RMLStreamer-SISO: an RDF stream generator from streaming heterogeneous data},
author = {Sitt Min Oo and Gerald Haesendonck and Ben De Meester and Anastasia Dimou},
journal= {arXiv preprint arXiv:2210.14599},
year = {2022}
}