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Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

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Abstract

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.

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Notes

  1. http://www.opengeospatial.org.

  2. www.census.gov/geo/www/tiger

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Acknowledgments

This work has been supported by the following Brazilian research agencies: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Financiadora de Estudos e Projetos (FINEP). The second author has been funded by grant number 229675/2013-1 from CNPq and grant number 14/14103-9 from FAPESP/CAPES. The third author has been funded by grant number 246263/2012-1 from CNPq.

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Authors and Affiliations

  1. Center for Informatics, Federal University of Pernambuco (UFPE), Recife, PE, 50740-560, Brazil

    Rodrigo Costa Mateus & Valéria Cesário Times

  2. São Paulo Federal Institute of Education, Science and Technology (IFSP), São Carlos, SP, 13565-905, Brazil

    Thiago Luís Lopes Siqueira

  3. Department of Computer Science, Federal University of São Carlos (UFSCar), São Carlos, SP, 13565-905, Brazil

    Thiago Luís Lopes Siqueira & Ricardo Rodrigues Ciferri

  4. Department of Computer & Decision Engineering, Université Libre de Bruxelles (ULB), Brussels, 1050, Belgium

    Thiago Luís Lopes Siqueira

  5. Department of Computer Science, University of São Paulo at São Carlos (USP), São Carlos, SP, 13560-970, Brazil

    Cristina Dutra de Aguiar Ciferri

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  1. Rodrigo Costa Mateus
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Correspondence to Valéria Cesário Times.

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Mateus, R.C., Siqueira, T.L.L., Times, V.C. et al. Spatial data warehouses and spatial OLAP come towards the cloud: design and performance. Distrib Parallel Databases 34, 425–461 (2016). https://doi.org/10.1007/s10619-015-7176-z

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