Hi Jan,

Thank you very much for the suggestion.

Regards,
Jevon
On 5/8/15 19:36, Jan Schermer wrote:
Hi,
comments inline.

On 05 Aug 2015, at 05:45, Jevon Qiao <qiaojianf...@unitedstack.com> wrote:

Hi Jan,

Thank you for the detailed suggestion. Please see my reply in-line.
On 5/8/15 01:23, Jan Schermer wrote:
I think I wrote about my experience with this about 3 months ago, including 
what techniques I used to minimize impact on production.

Basicaly we had to
1) increase pg_num in small increments only, bcreating the placement groups 
themselves caused slowed requests on OSDs
2) increse pgp_num in small increments and then go higher
So you totally completed the step 1 before jumping into step 2. Have you ever 
tried mixing them together? Increase pg_number, increase pgp_number, increase 
pg_number…
Actually we first increased both to 8192 and then decided to go higher, but 
that doesn’t matter.
The only reason for this was that the first step took could run unattended at 
night without disturbing the workload.*
The second step had to be attended.

* in other words, we didn’t see “slow requests” because of our threshold 
settings, but while PGs were creating the cluster paused IO for non-trivial 
amounts of time. I suggest you do this in as small steps as possible, depending 
on your SLAs.

We went from 4096 placement groups up to 16384

pg_num (the number of on-disk created placement groups) was increased like this:
# for i in `seq 4096 64 16384` ; do ceph osd pool set $pool pg_num $i ; sleep 
60 ; done
this ran overnight (and was upped to 128 step during the night)

Increasing pgp_num was trickier in our case, first because it was heavy 
production and we wanted to minimize the visible impact and second because of 
wildly differing free space on the OSDs.
We did it again in steps and waited for the cluster to settle before continuing.
Each step upped pgp_num by about 2% and as we got higher (>8192) we increased this to 
much more - the last step was 15360->16384 with the same impact the initial 
4096->4160 had.
The strategy you adopted looks great. I'll do some experiments on a test 
cluster to evaluate the real impact in each step
The end result is much better but still nowhere near optimal - bigger impact 
would be upgrading to a newer Ceph release and setting the new tunables because 
we’re running Dumpling.

Be aware that PGs cost some space (rough estimate is 5GB per OSD in our case), 
and also quite a bit of memory - each OSD has 1.7-2.0GB RSS right now while it 
only had about 1GB before. That’s a lot of memory and space with higher OSD 
counts...
This is a good point. So along with the increment of PGs, we also need to take 
the current status of the cluster(the available disk space and memory for each 
OSD) into account and evaluate whether it is needed to add more resources.
Depends on how much free space you have. We had some OSDs at close to 85% 
capacity before we started (and other OSD’s at only 30%). When increasing the 
number of PGs the data shuffled greatly - but this depends on what CRUSH rules 
you have (and what version you are running). Newer versions with newer tunables 
will make this a lot easier I guess.

And while I haven’t calculated the number of _objects_ per PG, but we have 
differing numbers of _placement_groups_ per OSD (one OSD hosts 500, another 
hosts 1300) and this seems to be the cause of poor data balancing.
In our environment, we also encountered the imbalance mapping between PGs and 
OSD. What kind of bucket algorithm was used in your environment? Any idea on 
how to minimize it?
We are using straw because of dumpling. Straw2 should make everything better :-)

Jan

Thanks,
Jevon
Jan


On 04 Aug 2015, at 18:52, Marek Dohojda <mdoho...@altitudedigital.com> wrote:

I have done this not that long ago.  My original PG estimates were wrong and I 
had to increase them.

After increasing the PG numbers the Ceph rebalanced, and that took a while.  To 
be honest in my case the slowdown wasn’t really visible, but it took a while.

My strong suggestion to you would be to do it in a long IO time, and be 
prepared that this willl take quite a long time to accomplish.  Do it slowly  
and do not increase multiple pools at once.

It isn’t recommended practice but doable.



On Aug 4, 2015, at 10:46 AM, Samuel Just <sj...@redhat.com> wrote:

It will cause a large amount of data movement.  Each new pg after the
split will relocate.  It might be ok if you do it slowly.  Experiment
on a test cluster.
-Sam

On Mon, Aug 3, 2015 at 12:57 AM, 乔建峰 <scaleq...@gmail.com> wrote:
Hi Cephers,

This is a greeting from Jevon. Currently, I'm experiencing an issue which
suffers me a lot, so I'm writing to ask for your comments/help/suggestions.
More details are provided bellow.

Issue:
I set up a cluster having 24 OSDs and created one pool with 1024 placement
groups on it for a small startup company. The number 1024 was calculated per
the equation 'OSDs * 100'/pool size. The cluster have been running quite
well for a long time. But recently, our monitoring system always complains
that some disks' usage exceed 85%. I log into the system and find out that
some disks' usage are really very high, but some are not(less than 60%).
Each time when the issue happens, I have to manually re-balance the
distribution. This is a short-term solution, I'm not willing to do it all
the time.

Two long-term solutions come in my mind,
1) Ask the customers to expand their clusters by adding more OSDs. But I
think they will ask me to explain the reason of the imbalance data
distribution. We've already done some analysis on the environment, we
learned that the most imbalance part in the CRUSH is the mapping between
object and pg. The biggest pg has 613 objects, while the smallest pg only
has 226 objects.

2) Increase the number of placement groups. It can be of great help for
statistically uniform data distribution, but it can also incur significant
data movement as PGs are effective being split. I just cannot do it in our
customers' environment before we 100% understand the consequence. So anyone
did this under a production environment? How much does this operation affect
the performance of Clients?

Any comments/help/suggestions will be highly appreciated.

--
Best Regards
Jevon

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