Name
Abstract | ||
|---|---|---|
Demography relates to statistical measures in social sciences, which is the study of human population in a certain period. Its main focus is to calculate birth & death rate, mobility, literacy ratio, and marriages. The immense population growth is presenting new challenges to handle massive quantities of demographic data (big data). With the evolution of computer age and software development, different procedures have been introduced to deal with big data. Most of the systems are based on traditional rational database, which lack in their capability to handle big data efficiently and accurately. Apache Hadoop platform is becoming famous for handling big data problems. Herein, we propose a demography big data handling system under Hadoop ecosystem to solve the issue of demography large-scale data handling. The main components of our system are Sqoop, HBase and Hive. Our system defines a method to export data from different RDBMS to Hadoop HBase. Moreover, HBase- Hive integration is a good architecture to store and query data for analysis efficiently. The results indicate that the presented approach better handles the distributed datasets as a single dataset to analyze for future estimates. Our approach will provide advancement in handling sophisticated demography big data and will eventually improve analytics such as promoting sustainable agriculture, preventing poverty, and decreasing death rate. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SNPD.2018.8441032 | 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) |
Keywords | Field | DocType |
RDBMS,HBase,Hive,Big Data Analysis,MapReduce,Demography Big Data | Population,Architecture,Relational database,Demography,Computer science,Relational database management system,Analytics,Group method of data handling,Big data,Software development | Conference |
ISBN | Citations | PageRank |
978-1-5386-5890-1 | 1 | 0.39 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syeda Sana Bukhari | 1 | 1 | 0.39 |
| JinHyuck Park | 2 | 1 | 0.39 |
| Dong-Ryeol Shin | 3 | 124 | 27.03 |