Re: Performance experiments with io-stats translator

[Manoj Pillai <mpillai@xxxxxxxxxx>]

On Tue, Jun 6, 2017 at 5:05 PM, Krutika Dhananjay <kdhananj@xxxxxxxxxx> wrote:

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.

Before I get to the results, a little bit about the configuration ...

3 node cluster; 1x3 plain replicate volume with group virt settings, direct-io.

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:

On the client stack: Above client-io-threads and above protocol/client-0 (the first child of AFR).

On the brick stack: Below protocol/server, above and below io-threads and just above storage/posix.

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:

​​Translator Position                       Avg Latency of READ fop as seen by this translator

1. parent of client-io-threads                1666us

∆ (1,2) = 50us

2. parent of protocol/client-0                1616us

∆ (2,3) = 1453us

----------------- end of client stack ---------------------

----------------- beginning of brick stack -----------

3. child of protocol/server                   163us

∆ (3,4) = 7us

4. parent of io-threads                        156us

∆ (4,5) = 20us

5. child-of-io-threads                          136us

∆ (5,6) = 11us

6. parent of storage/posix                   125us
...

---------------- 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, then

even 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.

-Krutika

Really 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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