On 7/31/06, David Lang <[email protected]> wrote:
On Mon, 31 Jul 2006, Nate Diller wrote:
> On 7/31/06, David Lang <[email protected]> wrote:
>> On Mon, 31 Jul 2006, Nate Diller wrote:
>>
>> >
>> > On 7/31/06, Matthias Andree <[email protected]> wrote:
>> >> Adrian Ulrich wrote:
>> >>
>> >> > See also: http://spam.workaround.ch/dull/postmark.txt
>> >> >
>> >> > A quick'n'dirty ZFS-vs-UFS-vs-Reiser3-vs-Reiser4-vs-Ext3 'benchmark'
>> >>
>> >> Whatever Postmark does, this looks pretty besides the point.
>> >
>> > why's that? postmark is one of the standard benchmarks...
>> >
>> >> Are these actual transactions with the "D"urability guarantee?
>> >> 3000/s doesn't look too much like you're doing synchronous I/O (else
>> >> figures around 70/s perhaps 100/s would be more adequate), and cache
>> >> exercise is rather irrelevant for databases that manage real (=valuable)
>> >> data...
>> >
>> > Data:
>> > 204.62 megabytes read (8.53 megabytes per second)
>> > 271.49 megabytes written (11.31 megabytes per second)
>> >
>> > looks pretty I/O bound to me, 11.31 MB/s isn't exactly your latest DDR
>> > RAM bandwidth. as far as the synchronous I/O question, Reiser4 in
>> > this case acts more like a log-based FS. That allows it to "overlap"
>> > synchronous operations that are being submitted by multiple threads.
>>
>> what you are missing is that apps that need to do lots of syncing
>> (databases,
>> mail servers) need to wait for the data to hit non-volitile media before
>> the
>> write is complete. this limits such apps to ~1 write per revolution of the
>> platters (yes it's possible for a limited time to have multiple writes to
>> different things happen to be on the same track, but the counter is the
>> extra
>> seek time needed between tracks)
>
> this is true so long as there is only one thread submitting I/O and
> doing fsync(). for something like a mail server, it can run
> multi-threaded, and still get data integrity, if the changes are
> spread out across more than one file.
only if those multiple files all happen to live (along with their metadata) on
the same track.
this is only a limitation for filesystems which do in-place data and
metadata updates. this is why i mentioned the similarities to log
file systems (see rosenblum and ousterhout, 1991). they observed an
order-of-magnitude increase in performance for such workloads on their
system.
>> so any benchmark that shows more transactions then the media has
>> revolutions is
>> highly suspect (now if you have battery-backed cache, or the equivalent you
>> can
>> blow past these limits)
>
> not all workloads are completely serial, transactions themselves may
> have no inter-dependencies at all. so it depends on the benchmark,
> and what workload you're measuring. in cases like this, threading can
> have a big advantage.
in the real-world (and benchmarks that simulate it fairly) the data spans
multiple tracks so your best case is considerably less then the max I listed
becouse you frequently have to seek around a lot to do your writes to multiple
places on disk. more threads running should mean that you are attempting to
write to more places on disk, which will cause more seeks, dropping you further
below the max.
postmark is very much real world. reiser4 just doesn't always do
in-place writes.
NATE
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