摘要
针对传统的海量数据处理方法硬件成本太高,并行程序编写困难的缺点,在云计算理论的基础上设计了一个用于处理海量数据的校园云计算系统。此云计算系统是在Hadoop分布式计算框架的基础上采用Map-Reduce编程模型实现对海量数据的并行处理,有效解决了成本问题,降低了并行编程的难度。
As the traditional method of massive data processing has shortcomings of high cost in hardware and the difficulties in parallel programming, a campus cloud computing system platform to handle massive data is designed based on the theory of cloud computing. This cloud computing system is based on the Hadoop distributed computing framework, using map-reduce programming model achieve parallel processing of the massive data. This system can save cost and reduce the difficulty of parallel programming.
出处
《计算机系统应用》
2011年第6期6-11,5,共7页
Computer Systems & Applications
基金
国家自然科学基金(90818028)
