Weather Data Management Using Hadoop MapReduce in Zimbabwe-Reference-Cited by-同舟云学术

Weather Data Management Using Hadoop MapReduce in Zimbabwe

Published:2022-11-20 Issue: Volume: Page:305-310
ISSN:2395-602X
Container-title:International Journal of Scientific Research in Science and Technology
language:en
Short-container-title:IJSRST

Author:

Muchaneta Mayepi ¹,Eng. Mainford Mutandavari ²,Tinashe Blessing Chuwe ¹

Affiliation:

1. Department of Information Technology, Harare Institute of Technology, P.O Box BE277, Belvedere, Harare, Zimbabwe

2. Department of Software Engineering, Harare Institute of Technology, P.O Box BE277, Belvedere, Harare, Zimbabwe

Abstract

The Meteorological Services Department (MSD) in Zimbabwe is experiencing huge costs in transferring data of over Gigabytes from its different models of automatic weather stations into centralized database at Head Quarters (HQ) Belvedere in Harare. However, surveys indicate that emerging technologies of big data analytics such as Hadoop MapReduce can be extended into weather data management offering multiplicity of functions that includes: prediction, management of transmission of data and also managing the range of weather elements to monitor at anytime and anywhere. This study therefore sought to design and develop an experimental set-up to understand how Hadoop MapReduce can be used to manage data files from various weather stations simulated as Application Programming Interface (APIs). The developed system was conducted entirely in a cloud environment and the results suggest that Hadoop MapReduce function is an appropriate big data tool to manage weather data and offers better options especially for cash strapped organizations such as Meteorological Services Department (MSD). Adoption of MapReduce is economic and elastic to accord changing weather data management requirements. The research used a small dataset of 100 records which might offer comprehensive model for use for practical purposes. Further studies with more realistic huge datasets might be pertinent.

Publisher

Technoscience Academy

Subject

General Medicine

Reference19 articles.

1. K. D. Foote, “A brief history of data management,” Dataversity , New York , 2020.

2. M. Aguirre-Munizaga and R. Gomez, “A Cloud Computing Based Framework for Storage and Processing of Meteorological Data,” Monash , Washington DC, 2020.

3. E. E. Filho, A. Albuquerque and M. Nagano, “Identifying SME mortality factors in the life cycle stages: an empirical approach of relevant factors for small business owner-managers in Brazil,” Journal of global entrepreneurship research, vol. 7, no. 5, 2017.

4. National Climate Data Center, “Managing legacy climate data in the 20th century,” National Climate Data Center (NCDC), Washington DC, 2020.

5. D. Liberto and J. Berry-Johnson, “Small and Mid-size Enterprise (SME): What is a Small and Mid-size Enterprise (SME)?,” Intercompany Solutions, New York, 2020.