Proceedings of the International Conference for Phoenixes on Emerging Current Trends in Engineering and Management (PECTEAM 2018)

Massive Data Processing Using Mapreduce Aggregation To Make Digitized India

Authors
S Thilagavathi, S Vimala, K Valarmathi, R Priya, S Sathya
Corresponding Author
S Thilagavathi
DOI
https://doi.org/10.2991/pecteam-18.2018.17How to use a DOI?
Keywords
Digitized India, data skew, MapReduce, Sqoop.
Abstract
Digitized India is used to connect rural areas with high speed Internet. As a result, it is used to reduce crime, manual power, documentation and also increases the job opportunities. Nowadays people are facing many problems when they forget to carry the driving license and also to reduce the corruption, the proposed system combines the driving license with Aadhar card. The details of driving license and Aadhar card data can be combined using the MapReduce Counters. It automatically aggregated over Map and Reduce phases. It is used to create a tool that manages the handling of license using unique identification associated with each individual. It helps the user to travel various places without having the license. So the proposed system will make the digitization of data on a large scale for easy and quick access throughout the India. Sqoop is a tool intended to exchange information amongst Hadoop and social databases. Sqoop utilizes MapReduce to import and export the information, which gives parallel operation and in addition adaptation to non-critical failure. As the result of parallel operations time utilization for transferring the data get decreased radically.
Copyright
© The authors.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Thilagavathi, S
AU  - Vimala, S
AU  - Valarmathi, K
AU  - Priya, R
AU  - Sathya, S
DA  - 2018/02/09
TI  - Massive Data Processing Using Mapreduce Aggregation To Make Digitized India
BT  - International Conference for Phoenixes on Emerging Current Trends in Engineering and Management (PECTEAM 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/pecteam-18.2018.17
DO  - https://doi.org/10.2991/pecteam-18.2018.17
ID  - Thilagavathi2018
ER  -