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

机译：解决分布式文件系统中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：采用了分布式文件系统（例如HDFS，DFS等）来支持云存储，并旨在优化大型文件的访问。但是不幸的是，海量小文件的问题被忽略了，并严重限制了分布式文件系统的性能。为了改善甚至解决小文件问题，本文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，并将研究对象从文件级转移到任务级。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。该策略根据访问任务合并小文件，并根据任务的转移概率选择完善的目标。最后，建立了系统效率分析模型，并与原始的HDFS，HAR和Dong的方案进行了比较，实验结果表明，该策略有效地降低了MDS的工作量和请求响应的延迟。

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