COVID-19和疫苗数据的可扩展分析
Scalable Analysis for Covid-19 and Vaccine Data
摘要：
本文解释了用于提取和分析Covid-19疫苗数据的可扩展方法。利用Hadoop和Hive等大数据，我们收集并分析了COVID-19确诊、死亡和疫苗接种数据集的海量数据集。数据大小约为3.2千兆字节。我们表明，使用大数据存储和处理海量数据是可能的。本文进行了时空分析，并通过可视化地图、图表和饼图将调查结果可视化。我们举例说明，接种疫苗越多，确诊病例越少。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
