关键词: Apriori算法, MapReduce计算框架, 哮喘用药组合, HBase分布式数据库

Abstract: On the traditional platform running Apriori algorithm to mining the TCM asthma medication combination rules, there are problems: Occupying a large memory space, low computational efficiency, and PB byte data can not be processed with. Thus this paper puts forward analysis method to mining associations of asthma medicine in TCM treatment based on Hadoop. Using Mapreduce distributed computing framework and HBase distributed database to optimized Apriori algorithm performance: on the one hand parallel processing data with Mapreduce computing framework, combine with characteristic of HBase high speed of read and write data, which accelerate the production of frequent item sets; On the other hand ?abandoned the traditional algorithm self join way of generated candidate sets. Using a combination of loops and recursive way to generation candidate sets for data of each node instead, which improve the candidate set generation efficiency. Experiments show that the use of Hadoop platform to mine the combination of TCM asthma medication, which has higher efficiency, and can more effectively guide clinical practice.

Key words: Apriori algorithm, MapReduce computing framework, asthma medication combination, HBase distributed database