计算机工程2017，Vol.43Issue(11)：8-15,8.DOI:10.3969/j.issn.1000-3428.2017.11.002
基于流式计算框架的实时数据库分区系统
Real-time Database Partitioning System Based on Streaming Computing Framework
摘要
Abstract
In order to realize the efficient processing of large scale and dynamic partition information in the big data environment,a real-time database partitioning system is proposed combining with the flow computing framework.This system copes with the large scale and dynamic workloads by using stream computing technologies in the big data environment.It designs a real-time data partitioning algorithm to realize automatic and immediate generation of data partitions.The system realizes the scalability and high-throughput adaption by using the horizontal scaling mechanism of streaming computing framework.The experimental results show that the system can realize efficient and real-time database partition in big data environment.It has higher partitioning quality and lower time than tranditional partitioning algorithm.关键词
数据库分区/流式计算框架/大数据管理/分布式存储/动态负载Key words
database partitioning/streaming computing framework/big data management/distributed storage/dynamic load分类
信息技术与安全科学引用本文复制引用
郭蒙雨,康宏,袁晓洁..基于流式计算框架的实时数据库分区系统[J].计算机工程,2017,43(11):8-15,8.基金项目
天津市应用基础与前沿技术研究计划项目(14JCYBJC15500) （14JCYBJC15500）
高等学校博士学科点专项科研基金(20130031120029). （20130031120029）
