Vladimír Hanušniak, Marian Svalec, Juraj Branický, L. Takac, M. Zábovský
{"title":"Exploitation of Hadoop framework for point cloud geographic data storage system","authors":"Vladimír Hanušniak, Marian Svalec, Juraj Branický, L. Takac, M. Zábovský","doi":"10.1109/ICDIPC.2015.7323028","DOIUrl":null,"url":null,"abstract":"It has been planned that the whole region of Slovak Republic's surface would be scanned, and there arose a need for storing the resulting data and making it publicly available. For this purpose, a scalable file-based database system for storing and accessing a large amount of geographic point cloud data was developed. The principle of the system was tested and proved to be sufficient in most situations, but under certain circumstances, single-computer solution was not satisfactory. So, the system was re-implemented using the Hadoop framework and experiments with many configurations were done. The results of the experiments are presented in this paper along with our conclusions.","PeriodicalId":339685,"journal":{"name":"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)","volume":"294 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIPC.2015.7323028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
It has been planned that the whole region of Slovak Republic's surface would be scanned, and there arose a need for storing the resulting data and making it publicly available. For this purpose, a scalable file-based database system for storing and accessing a large amount of geographic point cloud data was developed. The principle of the system was tested and proved to be sufficient in most situations, but under certain circumstances, single-computer solution was not satisfactory. So, the system was re-implemented using the Hadoop framework and experiments with many configurations were done. The results of the experiments are presented in this paper along with our conclusions.