基于智能聚类的医院分类大数据自动存储方法  

Automatic Storage Method of Hospital Classified Big Data Based on Intelligent Clustering

作　　者：马小明 刘永涛[1] 陈晓楠 MA Xiao-ming;LIU Yong-tao;CHEN Xiao-nan(The SecondAffiliated Hospital of Hebei North University,Zhangjiakou 075100 China)

机构地区：[1]河北北方学院附属第二医院,河北张家口075100

出　　处：《自动化技术与应用》2022年第11期84-87,共4页Techniques of Automation and Applications

摘　　要：常规的存储方法在处理多维数据时,其自身的抗压能力不能承受多维数据产生的工作负载,针对这一问题,提出基于智能聚类的医院分类大数据自动存储方法。利用智能聚类技术处理医院分类大数据,将数据分为不同的类别,将聚类后的数据传输到各个存储节点,依据各个传输任务的计算成本,合理调度各个任务的执行时间和资源,规定传输节点内的数据格式,在多维存储空间构建完成后,将数据存储在数据库内。实验结果表明:面对由多维数据导致的工作负载,提出的基于智能聚类的存储方法数据读写频率高达140 MB/s,并发处理性能优,提升了抗压能力。Conventional storage methods can't bear the workload of multidimensional data when dealing with multidimensional data.To solve this problem,an automatic storage method of hospital classified big data based on Intelligent clustering is proposed.Intelli-gent clustering technology is used to process hospital classified big data.The data is divided into different categories,and the clustered data is transmitted to each storage node.According to the calculation cost of each transmission task,the execution time and resources of each task are reasonably scheduled,and the data format in the transmission node is specified.After the multi-di-mensional storage space is constructed,the data is stored in the database.Experimental results show that:in the face of the work-load caused by multi-dimensional data,the proposed storage method based on Intelligent clustering has high data reading and writing frequency of 140 MB/s,excellent concurrent processing performance,and improved the compression ability.

关 键 词：智能聚类 医院信息化 分类处理 数据存储 分布式存储 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]