التفاصيل البيبلوغرافية
| العنوان: |
Scalable Analysis for Covid-19 and Vaccine Data |
| المؤلفون: |
Collins, Chris, Cuevas, Roxana, Hernandez, Edward, Hernandez, Reece, Le, Breanna, Woo, Jongwook |
| سنة النشر: |
2021 |
| المجموعة: |
Computer Science |
| مصطلحات موضوعية: |
Computer Science - Distributed, Parallel, and Cluster Computing |
| الوصف: |
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. |
| نوع الوثيقة: |
Working Paper |
| URL الوصول: |
http://arxiv.org/abs/2108.02898 |
| رقم الانضمام: |
edsarx.2108.02898 |
| قاعدة البيانات: |
arXiv |