Re: Rocksdb compaction and OSD timeout

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Oh that's very good to know.  I'm sure Igor will respond here, but do you know which PR this was related to? (possibly

If we think there's a regression here we should get it into the tracker ASAP.


On 9/7/23 13:45, J-P Methot wrote:
To be quite honest, I will not pretend I have a low level understanding of what was going on. There is very little documentation as to what the bluestore allocator actually does and we had to rely on Igor's help to find the solution, so my understanding of the situation is limited. What I understand is as follows:

-Our workload requires us to move around, delete, write a fairly high amount of RBD data around the cluster.

-The AVL allocator doesn't seem to like that and changes added to it in 16.2.14 made it worse than before.

-It made the OSDs become unresponsive and lag quite a bit whenever high amounts of data was written or deleted, which is, all the time.

-We basically changed the allocator to bitmap and, as we speak, this seems to have solved the problem. I understand that this is not ideal as it's apparently less performant, but here it's the difference between a cluster that gives me enough I/Os to work properly and a cluster that murders my performances.

I hope this helps. Feel free to ask us if you need further details and I'll see what I can do.

On 9/7/23 13:59, Mark Nelson wrote:
Ok, good to know.  Please feel free to update us here with what you are seeing in the allocator.  It might also be worth opening a tracker ticket as well.  I did some work in the AVL allocator a while back where we were repeating the linear search from the same offset every allocation, getting stuck, and falling back to fast search over and over leading to significant allocation fragmentation. That got fixed, but I wouldn't be surprised if we have some other sub-optimal behaviors we don't know about.


On 9/7/23 12:28, J-P Methot wrote:

By this point, we're 95% sure that, contrary to our previous beliefs, it's an issue with changes to the bluestore_allocator and not the compaction process. That said, I will keep this email in mind as we will want to test optimizations to compaction on our test environment.

On 9/7/23 12:32, Mark Nelson wrote:

There are two things that might help you here.  One is to try the new "rocksdb_cf_compaction_on_deletion" feature that I added in Reef and we backported to Pacific in 16.2.13.  So far this appears to be a huge win for avoiding tombstone accumulation during iteration which is often the issue with threadpool timeouts due to rocksdb.  Manual compaction can help, but if you are hitting a case where there's concurrent iteration and deletions with no writes, tombstones will accumulate quickly with no compactions taking place and you'll eventually end up back in the same place. The default sliding window and trigger settings are fairly conservative to avoid excessive compaction, so it may require some tuning to hit the right sweet spot on your cluster. I know of at least one site that's using this feature with more aggressive settings than default and had an extremely positive impact on their cluster.

The other thing that can help improve compaction performance in general is enabling lz4 compression in RocksDB.  I plan to make this the default behavior in Squid assuming we don't run into any issues in testing.  There are several sites that are using this now in production and the benefits have been dramatic relative to the costs.  We're seeing significantly faster compactions and about 2.2x lower space requirement for the DB (RGW workload). There may be a slight CPU cost and read/index listing performance impact, but even with testing on NVMe clusters this was quite low (maybe a couple of percent).


On 9/7/23 10:21, J-P Methot wrote:

Since my post, we've been speaking with a member of the Ceph dev team. He did, at first, believe it was an issue linked to the common performance degradation after huge deletes operation. So we did do offline compactions on all our OSDs. It fixed nothing and we are going through the logs to try and figure this out.

To answer your question, no the OSD doesn't restart after it logs the timeout. It manages to get back online by itself, at the cost of sluggish performances for the cluster and high iowait on VMs.

We mostly run RBD workloads.

Deep scrubs or no deep scrubs doesn't appear to change anything. Deactivating scrubs altogether did not impact performances in any way.

Furthermore, I'll stress that this is only happening since we upgraded to the latest Pacific, yesterday.

On 9/7/23 10:49, Stefan Kooman wrote:
On 07-09-2023 09:05, J-P Methot wrote:

We're running latest Pacific on our production cluster and we've been seeing the dreaded 'OSD::osd_op_tp thread 0x7f346aa64700' had timed out after 15.000000954s' error. We have reasons to believe this happens each time the RocksDB compaction process is launched on an OSD. My question is, does the cluster detecting that an OSD has timed out interrupt the compaction process? This seems to be what's happening, but it's not immediately obvious. We are currently facing an infinite loop of random OSDs timing out and if the compaction process is interrupted without finishing, it may explain that.

Does the OSD also restart after it logged the timeouts?

You might want to perform an offline compaction every $timeperiod to fix any potential RocksDB degradation. That's what we do. What kind of workload do you run (i.e. RBD, CephFS, RGW)?

Do you also see these timeouts occur during deep-scrubs?

Gr. Stefan

Best Regards,
Mark Nelson
Head of Research and Development

Clyso GmbH
p: +49 89 21552391 12 | a: Minnesota, USA
w: | e: mark.nelson@xxxxxxxxx

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