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Status Not under consideration
Workspace Storage Scale (formerly known as GPFS)
Created by Guest
Created on Feb 17, 2018

RELATED IDEAS

Compress files on initial placement

V5 Functionality.

Allow a file placement policy to specify compression. The fast compression library combined with the compressed data write will be faster than the time taken to write the uncompressed data to disk and the same for reading. So there is a substantial IO performance improvement to be gained as well as the storage saving. Compression needs to be applied before any encryption policy.

Waiting to compress the file later is a huge waste of system capacity as the file has to be written uncompressed, read back in by a migration policy, compressed and written back out. Instead by compressing the file as part of file placement only a compressed data stream needs to be written once and read back is faster and only needed to be done when required.

Idea priority Urgent
  • Guest
    Reply
    |     Sep 30, 2020

    Due to processing by IBM, this request was reassigned to have the following updated attributes:
    Brand - Servers and Systems Software
    Product family - IBM Spectrum Scale
    Product - Spectrum Scale (formerly known as GPFS) - Public RFEs
    Component - Product functionality

    For recording keeping, the previous attributes were:
    Brand - Servers and Systems Software
    Product family - IBM Spectrum Scale
    Product - Spectrum Scale (formerly known as GPFS) - Public RFEs
    Component - V4 Product functionality

  • Guest
    Reply
    |     Sep 21, 2020

    We do not foresee implementing inline compression in the near future.

  • Guest
    Reply
    |     Jul 2, 2019

    This is a very important cost savings to your clients and its languished for some time without being picked up. You can save a lot of money and/or cpu and io traffic through its implementation. This needs to be given higher priority by the dev team.

  • Guest
    Reply
    |     Jul 2, 2019

    This is a very important cost savings to your clients and its languished for some time without being picked up. You can save a lot of money and/or cpu and io traffic through its implementation. This needs to be given higher priority by the dev team.

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