Logging versus Soft Updates: Asynchronous Meta-data Protection in File Systems

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Logging versus Soft Updates: Asynchronous Meta-data Protection in File Systems

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Title: Logging versus Soft Updates: Asynchronous Meta-data Protection in File Systems
Author: Seltzer, Margo I.; Granger, Gregory R.; McKusick, M. Kirk; Smith, Keith A.; Soules, Craig A. N.; Stein, Christopher A.

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Citation: Seltzer, Margo I., Gregory R. Granger, M. Kirk McKusick, Keith A. Smith, Craig A.N. Soules, and Christopher A. Stein. 1999. Logging versus Soft Updates: Asynchronous Meta-data Protection in File Systems. Harvard Computer Science Group Technical Report TR-07-99.
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Abstract: The UNIX Fast File System (FFS) is probably the most widely-used file system for performance comparisons. However, such comparisons frequently overlook many of the performance enhancements that have been added over the past decade. In this paper, we explore the two most commonly used approaches for improving the performance of meta-data operations and recovery: logging and Soft Updates. The commercial sector has moved en masse to logging file systems, as evidenced by their presence on nearly every server platform available today: Solaris, AIX, Digital UNIX, HP-UX, Irix, and Windows NT. On all but Solaris, the default file system uses logging. In the meantime, Soft Updates holds the promise of providing stronger reliability guarantees than logging, with faster recovery and superior performance in certain boundary cases. In this paper, we explore the benefits of both Soft Updates and logging, comparing their behavior on both microbenchmarks and workload-based macrobenchmarks. We find that logging alone is not sufficient to “solve” the meta-data update problem. If synchronous semantics are required (i.e., meta-data operations are durable once the system call returns), then the logging systems cannot realize their full potential. Only when this synchronicity requirement is relaxed can logging systems approach the performance of systems like Soft Updates. Our asynchronous logging and Soft Updates systems perform comparably in most cases. While Soft Updates excels in some meta-data intensive microbenchmarks, it outperforms logging on only two of the four workloads we examined and performs less well on one.
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Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:24829598
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