Automatic View Selection for Distributed Dimensional Data

Leandro Ordonez-Ante, Gregory Van Seghbroeck, Tim Wauters, Bruno Volckaert, Filip De Turck

2019

Abstract

Small-to-medium businesses are increasingly relying on big data platforms to run their analytical workloads in a cost-effective manner, instead of using conventional and costly data warehouse systems. However, the distributed nature of big data technologies makes it time-consuming to process typical analytical queries, especially those involving aggregate and join operations, preventing business users from performing efficient data exploration. In this sense, a workload-driven approach for automatic view selection was devised, aimed at speeding up analytical queries issued against distributed dimensional data. This paper presents a detailed description of the proposed approach, along with an extensive evaluation to test its feasibility. Experimental results shows that the conceived mechanism is able to automatically derive a limited but comprehensive set of views able to reduce query processing time by up to 89%–98%.

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Paper Citation


in Harvard Style

Ordonez-Ante L., Van Seghbroeck G., Wauters T., Volckaert B. and De Turck F. (2019). Automatic View Selection for Distributed Dimensional Data.In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-369-8, pages 17-28. DOI: 10.5220/0007555700170028


in Bibtex Style

@conference{iotbds19,
author={Leandro Ordonez-Ante and Gregory Van Seghbroeck and Tim Wauters and Bruno Volckaert and Filip De Turck},
title={Automatic View Selection for Distributed Dimensional Data},
booktitle={Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2019},
pages={17-28},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007555700170028},
isbn={978-989-758-369-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Automatic View Selection for Distributed Dimensional Data
SN - 978-989-758-369-8
AU - Ordonez-Ante L.
AU - Van Seghbroeck G.
AU - Wauters T.
AU - Volckaert B.
AU - De Turck F.
PY - 2019
SP - 17
EP - 28
DO - 10.5220/0007555700170028