We are tuning the prefetching window from the client side by specifying a different 'rasize' at mount time.

The workload we are using is iozone, just the hardware is, to some extent, for HPC.

We think how many OSDs is a file stored across also impact the performance, since that somehow determines how much optimization space are there. More OSDs, More performance potential to exploit, so maybe
you could try more OSDs.

Would like to hear your further test results.

Cheers,
Li Wang

On 07/31/2013 12:42 PM, Chen, Xiaoxi wrote:
My 0.02, we have done some readahead test tuning on server(ceph osd) side, the 
result showing that when readahead = 0.5 * object_size(4M in default), we can 
get max read throughput. Readahead value larger than this generally will not 
help, but also not harm the performance.

For your case, seems your workload(HPC) are fully sequential, so larger read 
ahead and prefetch should be helpful, but for RBD part, it's a bit harder to so 
such tuning.

-----Original Message-----
From: ceph-devel-ow...@vger.kernel.org 
[mailto:ceph-devel-ow...@vger.kernel.org] On Behalf Of Mark Nelson
Sent: Monday, July 29, 2013 10:49 PM
To: Li Wang
Cc: ceph-devel@vger.kernel.org; Sage Weil
Subject: Re: Read ahead affect Ceph read performance much

On 07/29/2013 05:24 AM, Li Wang wrote:
We performed Iozone read test on a 32-node HPC server. Regarding the
hardware of each node, the CPU is very powerful, so does the network,
with a bandwidth > 1.5 GB/s. 64GB memory, the IO is relatively slow,
the throughput measured by 'dd' locally is around 70MB/s. We
configured a Ceph cluster with 24 OSDs on 24 nodes, one mds, one to
four clients, one client per node. The performance is as follows,

      Iozone sequential read throughput (MB/s)
Number of clients     1          2         4
Default resize    180.0954   324.4836   591.5851
Resize: 256MB     645.3347   1022.998    1267.631

The complete iozone parameter for one client is, iozone -t 1 -+m
/tmp/iozone.nodelist.50305030 -s 64G -r 4M -i 0 -+n -w -c -e -b
/tmp/iozone.nodelist.50305030.output, on each client node, only one
thread is started.

for two clients, it is,
iozone -t 2 -+m /tmp/iozone.nodelist.50305030 -s 32G -r 4M -i 0 -+n -w
-c -e -b /tmp/iozone.nodelist.50305030.output

As the data shown, a larger read ahead window could result in >300%
speedup!

Very interesting!  I've done some similar tests and saw somewhat different 
results (I actually in some cases saw improvement with lower readahead!).  I 
suspect that this may be very hardware dependent.  Were you using RBD or 
CephFS?  In either case, was it the kernel client or userland (IE QEMU/KVM or 
FUSE)?  Also, where did you adjust readahead?
Was this on the client volume or under the OSDs?

I've got to prepare for the talk later this week, but I will try to get my 
readahead test results out soon as well.


Besides, Since the backend of Ceph is not the traditional hard disk,
it is beneficial to capture the stride read prefetching. To prove
this, we tested the stride read with the following program, as we
know, the generic read ahead algorithm of Linux kernel will not
capture stride-read prefetch, so we use fadvise() to manually force pretching.
the record size is 4MB. The result is even more surprising,

              Stride read throughput (MB/s)
Number of records prefetched  0      1      4      16      64      128
Throughput                  42.82  100.74 217.41  497.73  854.48  950.18

As the data shown, with a read ahead size of 128*4MB, the speedup over
without read ahead could be up to 950/42 > 2000%!

The core logic of the test program is below,

stride = 17
recordsize = 4MB
for (;;) {
    for (i = 0; i < count; ++i) {
      long long start = pos + (i + 1) * stride * recordsize;
      printf("PRE READ %lld %lld\n", start, start + block);
      posix_fadvise(fd, start, block, POSIX_FADV_WILLNEED);
    }
    len = read(fd, buf, block);
    total += len;
    printf("READ %lld %lld\n", pos, (pos + len));
    pos += len;
    lseek(fd, (stride - 1) * block, SEEK_CUR);
    pos += (stride - 1) * block;
}

Given the above results and some more, We plan to submit a blue print
to discuss the prefetching optimization of Ceph.

Cool!


Cheers,
Li Wang




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