Thanks. So I was suggesting a repeat of the test but this time with iodepth=1 in the fio job. If reducing the no. of concurrent requests reduces drastically the high latency you're seeing from the client-side, that would strengthen the hypothesis than serialization/contention among concurrent requests at the n/w layers is the root cause here.
-- Manoj
On Thu, Jun 8, 2017 at 11:46 AM, Krutika Dhananjay <kdhananj@xxxxxxxxxx> wrote:
-KrutikaI have 3 vms reading from one mount, and each of these vms is running the above job in parallel.Hi,This is what my job file contains:
[global]
ioengine=libaio
#unified_rw_reporting=1
randrepeat=1
norandommap=1
group_reporting
direct=1
runtime=60
thread
size=16g
[workload]
bs=4k
rw=randread
iodepth=8
numjobs=1
file_service_type=random
filename=/perf5/iotest/fio_5
filename=/perf6/iotest/fio_6
filename=/perf7/iotest/fio_7
filename=/perf8/iotest/fio_8On Tue, Jun 6, 2017 at 9:14 PM, Manoj Pillai <mpillai@xxxxxxxxxx> wrote:On Tue, Jun 6, 2017 at 5:05 PM, Krutika Dhananjay <kdhananj@xxxxxxxxxx> wrote:Based on a 60-second run of randrd test and subsequent analysis of the stats dumped by the individual io-stats instances, the following is what I found:On the brick stack: Below protocol/server, above and below io-threads and just above storage/posix.On the client stack: Above client-io-threads and above protocol/client-0 (the first child of AFR).3 node cluster; 1x3 plain replicate volume with group virt settings, direct-io.Before I get to the results, a little bit about the configuration ...Hi,As part of identifying performance bottlenecks within gluster stack for VM image store use-case, I loaded io-stats at multiple points on the client and brick stack and ran randrd test using fio from within the hosted vms in parallel.3 FUSE clients, one per node in the cluster (which implies reads are served from the replica that is local to the client).io-stats was loaded at the following places:Translator Position Avg Latency of READ fop as seen by this translator1. parent of client-io-threads1666us ∆ (1,2) = 50us2. parent of protocol/client-0 1616us∆ (2,3) = 1453us----------------- end of client stack -------------------------------------- beginning of brick stack -----------3. child of protocol/server163us ∆ (3,4) = 7us4. parent of io-threads156us ∆ (4,5) = 20us5. child-of-io-threads136us ∆ (5,6) = 11us6. parent of storage/posix125us
...---------------- end of brick stack ------------------------So it seems like the biggest bottleneck here is a combination of the network + epoll, rpc layer?I must admit I am no expert with networks, but I'm assuming if the client is reading from the local brick, theneven latency contribution from the actual network won't be much, in which case bulk of the latency is coming from epoll, rpc layer, etc at both client and brick end? Please correct me if I'm wrong.I will, of course, do some more runs and confirm if the pattern is consistent.-KrutikaReally interesting numbers! How many concurrent requests are in flight in this test? Could you post the fio job? I'm wondering if/how these latency numbers change if you reduce the number of concurrent requests.-- Manoj
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