A fast and slippery slope for file systems

Ricardo Santana, R. Rangaswami, Vasily Tarasov, Dean Hildebrand
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引用次数: 14

Abstract

There is a vast number and variety of file systems currently available, each optimizing for an ever growing number of storage devices and workloads. Users have an unprecedented, and somewhat overwhelming, number of data management options. At the same time, the fastest storage devices are only getting faster, and it is unclear on how well the existing file systems will adapt. Using emulation techniques, we evaluate five popular Linux file systems across a range of storage device latencies typical to low-end hard drives, latest high-performance persistent memory block devices, and in between. Our findings are often surprising. Depending on the workload, we find that some file systems can clearly scale with faster storage devices much better than others. Further, as storage device latency decreases, we find unexpected performance inversions across file systems. Finally, file system scalability in the higher device latency range is not representative of scalability in the lower, sub-millisecond, latency range. We then focus on Nilfs2 as an especially alarming example of an unexpectedly poor scalability and present detailed instructions for identifying bottlenecks in the I/O stack.
文件系统的快速滑坡
目前可用的文件系统种类繁多,每种文件系统都针对数量不断增长的存储设备和工作负载进行了优化。用户拥有前所未有的、甚至是压倒性的数据管理选项。与此同时,最快的存储设备的速度只会越来越快,目前还不清楚现有的文件系统将如何适应。通过使用仿真技术,我们评估了五种流行的Linux文件系统,这些系统的存储设备延迟范围包括低端硬盘驱动器、最新的高性能持久内存块设备以及两者之间的存储设备延迟。我们的发现常常令人惊讶。根据工作负载的不同,我们发现一些文件系统显然比其他文件系统更适合使用更快的存储设备。此外,随着存储设备延迟的减少,我们发现跨文件系统出现了意想不到的性能反转。最后,较高设备延迟范围内的文件系统可伸缩性不能代表较低、亚毫秒级延迟范围内的可伸缩性。然后,我们将重点介绍Nilfs2,它是一个特别令人担忧的可伸缩性差的例子,并提供了识别I/O堆栈瓶颈的详细说明。
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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