Comparative Analysis of SpatialHadoop and GeoSpark for Geospatial Big Data Analytics

December 22, 2016 Β· Declared Dead Β· πŸ› International Conferences on Contemporary Computing and Informatics

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Distributed Computing

Died the same way β€” πŸ‘» Ghosted