A comparison of file system workloads
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A Comparison of File System Workloads . D. Roselli J. Lorch T. Anderson University of California, Berkeley. Motivation. Wanted to find common file usage patterns Focused on how workload and file system parameters affect disk behavior Cache sizes Memory mapping Delayed write policy

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A Comparison of File System Workloads

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A comparison of file system workloads

A Comparison ofFile System Workloads

D. Roselli

J. Lorch

T. Anderson

University of California, Berkeley


Motivation

Motivation

  • Wanted to find common file usage patterns

  • Focused on how workload and file system parameters affect disk behavior

    • Cache sizes

    • Memory mapping

    • Delayed write policy

    • File layout policies


Trace collection

Trace collection

  • Three Unix environments:

    • 20 workstations used for undergraduate classes

    • 13 workstations usedby faculty, graduate students and staff working on research projects

    • One web server

  • One set of eight desktops running Windows NT


Trace collection issues

Trace collection issues

  • Modified Unix kernel in order to record full pathnames of all files being accessed

    • Auditing subsystem of HP-UX only recorded file names as specified by the user

      • Often relative to current directory


Estmating block lifetimes i

Estmating block lifetimes (I)

  • A previous study measured block lifetimes as delete time minus create time

  • This delete-based method

    • Did not take into account the lifetimes of blocks that were not deleted during measurement interval

    • Underestimated block lifetimes


Estimating block lifetimes ii

Estimating block lifetimes (II)

  • Create-based method partitions trace into two parts

    • First part is used to collect information on block creation times

    • Proceed as in delete-based method for blocks that were deleted during total observation period

    • Assume that other blocks have lived for at lest the duration of the second part of the trace


Example

Example

D2

X

Time

Trace

starts

Create

Block B

First part of trace

ends

Trace

ends

If block B was never deleted while trace was

collected, its lifetime must be greater than D2


Conclusions i

Conclusions (I)

  • Different systems show

    • Different I/O loads

    • Different block lifetimes and lifetime distributions


Conclusions ii

Conclusions (II)

  • Block overwrites

    • Cause the most significant fraction of deleted blocks

    • Show substantial locality

    • A small write buffer is sufficient for nearly all workloads

    • Ideal write delay vary with workload

      • Standard 30 second delay

      • Slightly longer delays


Conclusions iii

Conclusions (III)

  • Even small caches can sharply reduce disk read traffic

  • Very large caches will not cause disk traffic to be dominated by writes

  • A small number of memory mapped files are shared among many active processes

    • Should keep file in memory as long as it is memory-mapped by any process


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