Using Hadoop Distributed Computing Architecture to Enhance the Processing Speed of Large Medical Data– An Example of Taiwan Health Insurance Database

• Main Authors: Pu-Jen Chang, 張卜仁
• Other Authors: 徐建業
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/x23nn8

碩士 === 臺北醫學大學 === 醫學資訊研究所 === 102 === Currently promoting the cloud of health in Taiwan, medical data began to change, such as Electronic Medical Records, telemedicine data, so that different types of large amounts of data follow. We are often used to merge some of the different database or cooperation with other industries also needs to integrate different types of databases to do research in medical research. This study aimed to use common databases MS SQL、 MySQL, execute the query and analyze and connection Big Data, so face to problem is the temporary lack of space and process data time is too long. In this study, we used the Big Data on the Taiwan Health Insurance Database, execution search syntax in Hadoop and MS SQL、MySQL and confirmed Hadoop applications in the large medical databases time-consuming performance is better than the other. Finally, we use Hadoop systems and Web combined into a Taiwan Health Insurance Database Cloud Data Analysis Systems, and enhancing Hadoop applications in medical data analysis