[1]田翠姣,苏义武.DataX 工具在新冠肺炎数据上报中的应用[J].计算机技术与发展,2020,30(11):216-220.[doi:10. 3969 / j. issn. 1673-629X. 2020. 11. 040]
　TIAN Cui-jiao,SU Yi-wu.Application of DataX Tool in Data Reporting of New Coronavirus Pneumonia[J].,2020,30(11):216-220.[doi:10. 3969 / j. issn. 1673-629X. 2020. 11. 040]
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DataX 工具在新冠肺炎数据上报中的应用()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年11期
页码:
216-220
栏目:
应用开发研究
出版日期:
2020-11-10

文章信息/Info

Title:
Application of DataX Tool in Data Reporting of New Coronavirus Pneumonia
文章编号:
1673-629X(2020)11-0216-05
作者:
田翠姣; 苏义武
武汉大学中南医院,湖北 武汉 430071
Author(s):
TIAN Cui-jiao; SU Yi-wu
Zhongnan Hospital of Wuhan University,Wuhan 430071,China
关键词:
新冠肺炎; DataX; CSV; JSON; 数据上报
Keywords:
new coronavirus pneumonia; DataX; CSV; JSON; data reporting
分类号:
TP39
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 11. 040
摘要:
新冠肺炎疫情防控期间,精确的数据上报越发显得重要,国家医政医管局发文要求每天定时上传确诊和疑似患者全量医疗数据。该文重点讨论了利用 DataX 工具进行数据提取的方法以及该工具是否具有推广价值。 搭建 DataX 运行环境,编写测试脚本并运行,检测输出数据各项指标,观测任务执行时间,并与之前手工模式进行对比。使用基于 DataX 的工具环境后,实际执行效率明显高于原先手工执行 SQL 语句导出数据的方式。 DataX 不仅能快速导出数据,而且能将不同数据库的数据抽取到目标库,实现数据的整合,此外,数据导出高效、准确,除了较好地完成本次上报任务外,还能满足医疗机构日常工作中各类数据上报的需求。
Abstract:
During the prevention and control of novel coronavirus pneumonia, accurate data reporting is becoming more and more important. The National Medical Administration and Hospital Authority issued a document requiring that full medical data of confirmed and suspected patients be upl- oaded regularly every day. We mainly discuss the method of data extraction using DataX tool and whether the tool is promoted. Set up DataX running environment,write test script and run it,test output data indicators,observe task execution time,and compare with previous manual mode. After using the tool environment based on DataX,the actual execution efficiency is significantly higher than the original way of manually executing SQL statements to export data. DataX can not only export data quickly,but also extract data from different databases to the target database to realize data integration. In addition, data export is efficient and accurate. Besides completing the reporting task,it can also meet the needs of various data reporting in the daily work of medical institutions.

相似文献/References:

[1]曾庆鹏,崔 鹏.基于 PRAU-Net 的新冠肺炎 CT 图像分割研究[J].计算机技术与发展,2024,34(03):133.[doi:10. 3969 / j. issn. 1673-629X. 2024. 03. 020]
　ZENG Qing-peng,CUI Peng.Research of COVID-19 CT Image Segmentation Based on PRAU-Net[J].,2024,34(11):133.[doi:10. 3969 / j. issn. 1673-629X. 2024. 03. 020]

更新日期/Last Update: 2020-11-10