Small file access optimization based on GlusterFS

Xie Tao, Liang Alei
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引用次数: 6

Abstract

This paper describes a strategy to optimize small file's reading and writing performance on traditional distributed file system. Traditional distributed file system like GlusterFS stores data within local file system (XFS, EXT3, EXT4, etc.), which shows a significant bottleneck on file metadata lookup. We try to re-design metadata structure by merging small file into large file, thus to reduce size of metadata, so we can store the whole files' metadata inside main memory. We design and implement the whole strategy on GlusterFS, test results show a great performance optimization on small file operation.
基于GlusterFS的小文件访问优化
本文介绍了一种在传统分布式文件系统上优化小文件读写性能的策略。像GlusterFS这样的传统分布式文件系统将数据存储在本地文件系统(XFS、EXT3、EXT4等)中,这在文件元数据查找方面显示出明显的瓶颈。我们尝试通过将小文件合并为大文件来重新设计元数据结构,从而减小元数据的大小,从而将整个文件的元数据存储在主存中。我们在GlusterFS上设计并实现了整个策略,测试结果表明在小文件操作上有很大的性能优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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