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Authors: Jitka Komarkova ; Jakub Spidlen ; Devanjan Bhattacharya and Oldrich Horak

Affiliation: University of Pardubice, Czech Republic

Keyword(s): Distributed Processing, Apache Hadoop, Elevation Data, Small Cluster.

Related Ontology Subjects/Areas/Topics: Data Communication Networking ; Distributed and Mobile Software Systems ; Distributed Architectures ; Parallel and High Performance Computing ; Performance Evaluation ; Software Engineering ; Software Project Management ; Telecommunications

Abstract: Geoinformation technologies require fast processing of high and quickly increasing volumes of all types of spatial data. Parallel computational approach and distributed systems represent technologies which are able to provide required services, with reasonable costs. MapReduce is one example of such approach. It has been successfully implemented in large clusters in several instances. The applications include spatial and imagery data processing. The contribution deals with its implementation and operational performance using only a very small cluster (consisting of a few commodity personal computers) to process large-volume spatial data. Open-source implementation of MapReduce, named, Apache Hadoop, is used. The contribution is focused on a low-price solution and it deals with speed of processing and distribution of processed files. Authors run several experiments to evaluate the benefit of distributed data processing in a small-sized cluster and to find possible limitations. Size of processed files and number of processed values is used as the most important criteria for performance evaluation. Point elevation data were used during the experiments. (More)

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Paper citation in several formats:
Komarkova, J.; Spidlen, J.; Bhattacharya, D. and Horak, O. (2013). Distributed Processing of Elevation Data by Means of Apache Hadoop in a Small Cluster. In Proceedings of the 8th International Joint Conference on Software Technologies (ICSOFT 2013) - ICSOFT-EA; ISBN 978-989-8565-68-6; ISSN 2184-2833, SciTePress, pages 340-344. DOI: 10.5220/0004591303400344

@conference{icsoft-ea13,
author={Jitka Komarkova. and Jakub Spidlen. and Devanjan Bhattacharya. and Oldrich Horak.},
title={Distributed Processing of Elevation Data by Means of Apache Hadoop in a Small Cluster},
booktitle={Proceedings of the 8th International Joint Conference on Software Technologies (ICSOFT 2013) - ICSOFT-EA},
year={2013},
pages={340-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004591303400344},
isbn={978-989-8565-68-6},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Software Technologies (ICSOFT 2013) - ICSOFT-EA
TI - Distributed Processing of Elevation Data by Means of Apache Hadoop in a Small Cluster
SN - 978-989-8565-68-6
IS - 2184-2833
AU - Komarkova, J.
AU - Spidlen, J.
AU - Bhattacharya, D.
AU - Horak, O.
PY - 2013
SP - 340
EP - 344
DO - 10.5220/0004591303400344
PB - SciTePress

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