Advanced search
1 file | 372.80 KB Add to list
Author
Organization
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%.
Keywords
Interactive Querying, View Selection, Clustering, Distributed Data, Dimensional Data, Data Warehouse, MATERIALIZED VIEW

Downloads

  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 372.80 KB

Citation

Please use this url to cite or link to this publication:

MLA
Ordonez Ante, Leandro, et al. “Automatic View Selection for Distributed Dimensional Data.” PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019), 2019, pp. 17–28, doi:10.5220/0007555700170028.
APA
Ordonez Ante, L., Van Seghbroeck, G., Wauters, T., Volckaert, B., & 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 (IOTBDS 2019) (pp. 17–28). Heraklion, GREECE. https://doi.org/10.5220/0007555700170028
Chicago author-date
Ordonez Ante, Leandro, Gregory Van Seghbroeck, Tim Wauters, Bruno Volckaert, and Filip De Turck. 2019. “Automatic View Selection for Distributed Dimensional Data.” In PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019), 17–28. https://doi.org/10.5220/0007555700170028.
Chicago author-date (all authors)
Ordonez Ante, Leandro, Gregory Van Seghbroeck, Tim Wauters, Bruno Volckaert, and Filip De Turck. 2019. “Automatic View Selection for Distributed Dimensional Data.” In PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019), 17–28. doi:10.5220/0007555700170028.
Vancouver
1.
Ordonez Ante L, Van Seghbroeck G, Wauters T, Volckaert B, De Turck F. Automatic view selection for distributed dimensional data. In: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019). 2019. p. 17–28.
IEEE
[1]
L. Ordonez Ante, G. Van Seghbroeck, T. Wauters, B. Volckaert, and F. De Turck, “Automatic view selection for distributed dimensional data,” in PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019), Heraklion, GREECE, 2019, pp. 17–28.
@inproceedings{8614933,
  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%.},
  author       = {Ordonez Ante, Leandro and Van Seghbroeck, Gregory and Wauters, Tim and Volckaert, Bruno and De Turck, Filip},
  booktitle    = {PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS 2019)},
  isbn         = {9789897583698},
  keywords     = {Interactive Querying,View Selection,Clustering,Distributed Data,Dimensional Data,Data Warehouse,MATERIALIZED VIEW},
  language     = {eng},
  location     = {Heraklion, GREECE},
  pages        = {17--28},
  title        = {Automatic view selection for distributed dimensional data},
  url          = {http://dx.doi.org/10.5220/0007555700170028},
  year         = {2019},
}

Altmetric
View in Altmetric
Web of Science
Times cited: