The Esign And Implementation Of Chronic Disease Management Information System In The Environment Of Big Data

With the rapid development of health information technology and growth of medical data, the traditional medical information system has been unable to adapt to the new needs of the industry, especially with the explosive growth of data. It cannot help people use data mining methods to find value from data people have. When we apply the big data technology and its advanced computing concept to the medical industry, many problems can be solved. Not only to assist doctors to make effective decisions, but also to major medical institutions of data seamless combination of elastic mass data storage, also can help people effective management the analysis utilized to improve application scalability.In this paper, we designed a management information system for chronic disease, using data processing technology. By this way, we solved the problem that the traditional medical information has, such as cannot be able to applied to large-scale medical applications, cannot share medical data with other hospital or clinics, can not help doctors make effective decisions and so on.In this paper, the first thing we do is to study technology of large data, so we can sure which of it we will use to our system, then we use Spark distributed computing framework, HDFS storage system, HBase, Hive, Echarts to form chronic disease management information system in order to solve massive data storage and compute problems. When we finished built the big data platform for professional medical, we need to use Hibench benchmark to test our platform, make sure this platform with high availability and high fault tolerance. Then we Sqoop data from Oracle to Spark. When got the data from HDFS, we can use batch increment calculation to get the result people need. Finally, we use Kafka, Spark Streaming to process real-time data.