Measurements of a distributed file system

Author:

Baker Mary G.1,Hartman John H.1,Kupfer Michael D.1,Shirriff Ken W.1,Ousterhout John K.1

Affiliation:

1. Computer Science Division, Electrical Engineering and Computer Sciences, University of California, Berkeley, CA

Abstract

We analyzed the user-level file access patterns and caching behavior of the Sprite distributed file system. The first part of our analysis repeated a study done in 1985 of the: BSD UNIX file system. We found that file throughput has increased by a factor of 20 to an average of 8 Kbytes per second per active user over 10-minute intervals, and that the use of process migration for load sharing increased burst rates by another factor of six. Also, many more very large (multi-megabyte) files are in use today than in 1985. The second part of our analysis measured the behavior of Sprite's main-memory file caches. Client-level caches average about 7 Mbytes in size (about one-quarter to one-third of main memory) and filter out about 50% of the traffic between clients and servers. 35% of the remaining server traffic is caused by paging, even on workstations with large memories. We found that client cache consistency is needed to prevent stale data errors, but that it is not invoked often enough to degrade overall system performance.

Publisher

Association for Computing Machinery (ACM)

Cited by 35 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Hybrid Block Storage for Efficient Cloud Volume Service;ACM Transactions on Storage;2023-10-03

2. A new benchmark harness for systematic and robust evaluation of streaming state stores;Proceedings of the Seventeenth European Conference on Computer Systems;2022-03-28

3. A Large-scale Analysis of Hundreds of In-memory Key-value Cache Clusters at Twitter;ACM Transactions on Storage;2021-08-31

4. Consistent Sampling of Churn Under Periodic Non-Stationary Arrivals in Distributed Systems;ACM Transactions on Modeling and Performance Evaluation of Computing Systems;2019-12-31

5. COMBFT;Proceedings of the 48th International Conference on Parallel Processing;2019-08-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3