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An Effective Strategy for Improving Small File Problem in Distributed File System

机译:一种改进分布式文件系统小文件问题的有效策略

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Distributed file systems, such as HDFS, DFS, etc, are adopted to support cloud storage and are designed for optimizing large files access. But unfortunately, the problem of massive small files is neglected and seriously restricts the performance of distributed file systems. To improve and even solve the small file problem, in this paper, user access task is defined. The correlations among the access tasks, applications and access files are constructed by the improved PLSA, and the research object is transferred from file-level to task-level. Then, an effective strategy is proposed to improving small file problem in distributed file system. The strategy merges small files in term of access tasks and selects perfecting targets based on the transition probability of the tasks. Finally, the system efficiency analysis model is established and experimental results, compared with original HDFS, HAR and the schemes of Dong, demonstrate that the proposed strategy effectively reduce the MDS workload and the request response delay.
机译:采用分布式文件系统,如HDFS,DFS等来支持云存储,并设计用于优化大文件访问。但遗憾的是,忽略了大量小文件的问题并严重限制了分布式文件系统的性能。为了提高甚至解决小文件问题,在本文中,定义了用户访问任务。通过改进的PLSA构建访问任务,应用程序和访问文件之间的相关性,并且研究对象从文件级传输到任务级别。然后,提出了一种有效的策略来改善分布式文件系统中的小文件问题。该策略在访问任务中融合了小文件,并根据任务的转换概率选择完善目标。最后,建立了系统效率分析模型和实验结果,与原始HDFS,RAR和Dong方案相比,证明了所提出的策略有效降低了MDS工作量和请求响应延迟。

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