Comparative Analysis of SpatialHadoop and GeoSpark for Geospatial Big Data Analytics
December 22, 2016 Β· Declared Dead Β· π International Conferences on Contemporary Computing and Informatics
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Authors
Rakesh K. Lenka, Rabindra K. Barik, Noopur Gupta, Syed Mohd Ali, Amiya Rath, Harishchandra Dubey
arXiv ID
1612.07433
Category
cs.DC: Distributed Computing
Cross-listed
cs.CY
Citations
49
Venue
International Conferences on Contemporary Computing and Informatics
Last Checked
5 months ago
Abstract
In this digitalised world where every information is stored, the data a are growing exponentially. It is estimated that data are doubles itself every two years. Geospatial data are one of the prime contributors to the big data scenario. There are numerous tools of the big data analytics. But not all the big data analytics tools are capabilities to handle geospatial big data. In the present paper, it has been discussed about the recent two popular open source geospatial big data analytical tools i.e. Spatial- Hadoop and GeoSpark which can be used for analysis and process the geospatial big data in efficient manner. It has compared the architectural view of SpatialHadoop and GeoSpark. Through the architectural comparison, it has also summarised the merits and demerits of these tools according the execution times and volume of the data which has been used.
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