International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 90 - Issue 10 |
Published: March 2014 |
Authors: Ravindra P. Bachate, H. A. Hingoliwala |
![]() |
Ravindra P. Bachate, H. A. Hingoliwala . MRDS Data Processing and Mining using Hadoop in Cloud. International Journal of Computer Applications. 90, 10 (March 2014), 1-3. DOI=10.5120/15753-4260
@article{ 10.5120/15753-4260, author = { Ravindra P. Bachate,H. A. Hingoliwala }, title = { MRDS Data Processing and Mining using Hadoop in Cloud }, journal = { International Journal of Computer Applications }, year = { 2014 }, volume = { 90 }, number = { 10 }, pages = { 1-3 }, doi = { 10.5120/15753-4260 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2014 %A Ravindra P. Bachate %A H. A. Hingoliwala %T MRDS Data Processing and Mining using Hadoop in Cloud%T %J International Journal of Computer Applications %V 90 %N 10 %P 1-3 %R 10.5120/15753-4260 %I Foundation of Computer Science (FCS), NY, USA
This project explores the use of Hadoop framework for MRDS (Mineral Resources data system) data processing and mining in cloud. Cloud computing provides efficient computation and analysis for large data. To improve the performance of system for massive data, Hadoop provides Map Reduce technique. Hadoop has a distributed file system (HDFS) that stores data on the cluster nodes. This project focuses on to provide real time information of mineral resources stored in cloud environment with minimum data processing time. Storing MRDS data in to the cloud ensures the availability and reliability of it.