This paper explains the scalable methods used for extracting and analyzing the Covid-19 vaccine data. Using Big Data such as Hadoop and Hive, we collect and analyze the massive data set of the confirmed, the fatality, and the vaccination data set of Covid-19. The data size is about 3.2 Giga-Byte. We show that it is possible to store and process massive data with Big Data. The paper proceeds tempo-spatial analysis, and visual maps, charts, and pie charts visualize the result of the investigation. We illustrate that the more vaccinated, the fewer the confirmed cases.
Cite
@article{arxiv.2108.02898,
title = {Scalable Analysis for Covid-19 and Vaccine Data},
author = {Chris Collins and Roxana Cuevas and Edward Hernandez and Reece Hernandez and Breanna Le and Jongwook Woo},
journal= {arXiv preprint arXiv:2108.02898},
year = {2021}
}