On 06.05.2014 23:49, Chris Murphy wrote:
On May 6, 2014, at 4:41 AM, Hendrik Siedelmann
<hendrik.siedelm...@googlemail.com> wrote:
Hello all!
I would like to use btrfs (or anyting else actually) to maximize
raid0 performance. Basically I have a relatively constant stream of
data that simply has to be written out to disk.
I think the only way to know what works best for your workload is to
test configurations with the actual workload. For optimization of
multiple device file systems, it's hard to beat XFS on raid0 or even
linear/concat due to its parallelization, if you have more than one
stream (or a stream that produces a lot of files that XFS can
allocate into separate allocation groups). Also mdadm supports use
specified strip/chunk sizes, whereas currently on Btrfs this is fixed
to 64KiB. Depending on the file size for your workload, it's possible
a much larger strip will yield better performance.
Thanks, that's quite a few knobs I can try out - I just have a lot of
data - with a rate up to 450MB/s that I want to write out in time,
preferably without having to rely on too expensive hardware.
Another optimization is hardware RAID with a battery backed write
cache (the drives' write cache are disabled) and using nobarrier
mount option. If your workload supports linear/concat then it's fine
to use md linear for this. What I'm not sure of is if it's an OK
practice to disable barriers if the system is on a UPS (rather than a
battery backed hardware RAID cache). You should post the workload and
hardware details on the XFS list to get suggestions about such
things. They'll also likely recommend the deadline scheduler over
cfq.
Actually data integrity does not matter for the workload. If everything
is succesfull the result will be backed up - before that full filesystem
corruption is acceptable as a failure mode.
Unless you have a workload really familiar to the responder, they'll
tell you any benchmarking you do needs to approximate the actual
workflow. A mismatched benchmark to the workload will lead you to the
wrong conclusions. Typically when you optimize for a particular
workload, other workloads suffer.
Chris Murphy
Thanks again for all the infos! I'll get back if everything works fine -
or if it doesn't ;-)
Cheers
Hendrik
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