Hi Vladimir, What Kingston SSD model? El 4/8/20 a las 12:22, Vladimir Prokofev escribió: -- Eneko Lacunza | Tel. 943 569 206 | Email elacunza(a)binovo.es Director Técnico | Site. https://www.binovo.es BINOVO IT HUMAN PROJECT S.L | Dir. Astigarragako Bidea, 2 - 2º izda. Oficina 10-11, 20180 Oiartzun

I really would not focus that much on a particular device model. Yes, Kingston SSDs are slower for reads, we knew that since we tested them. But that was before they were used as block.db devices, they first were intended purely as block.wal devices. This was even before bluestore actually, so their primary function was to serve as XFS journals. I see increased read activity on all block.db devices while snaptrims are active, be them Intel or Kingston. Latter just suffer more. This read load was not there before 14.2.10/system upgrade. I'm actually thinking about rolling back to 14.2.8. Any ideas how safe that procedure is? I suppose it should be safe since there was no change in the actual data storage scheme? вт, 4 авг. 2020 г. в 14:33, Vladimir Prokofev <v(a)prokofev.me>me>:

Hi, I found the reasen of this behavior change. With 14.2.10 the default value of "bluefs_buffered_io" was changed from true to false. https://tracker.ceph.com/issues/44818 configureing this to true my problems seems to be solved. Regards Manuel On Wed, 5 Aug 2020 13:30:45 +0200 Manuel Lausch <manuel.lausch(a)1und1.de> wrote: > Hello Vladimir, > > I just tested this with a single node testcluster with 60 HDDs (3 of > them with bluestore without separate wal and db). > > With the 14.2.10, I see on the bluestore OSDs a lot of read IOPs while > snaptrimming. With 14.2.9 this was not an issue. > > I wonder if this would explain the huge amount of slowops on my big > testcluster (44 Nodes 1056 OSDs) while snaptrimming. I > cannot test a downgrade there, because there are no packages of older > releases for CentOS 8 available. > > Regards > Manuel >

Thinking about this a little more, one thing that I remember when I was writing the priority cache manager is that in some cases I saw strange behavior with the rocksdb block cache when compaction was performed.  It appeared that the entire contents of the cache could be invalidated.  I guess that would only make sense if it was trimming old entries from the cache instead of entries associated with (now deleted) sst files or perhaps waiting to delete all SST files until the end of the compaction cycle thus forcing old entries out of the cache and then invalidating the whole works. In any event, I wonder if having the secondary page cache is enough on your clusters to sort of get around all of this by still having the SST files associated with the previously heavily used blocks in page cache kicking around until compaction completes. Maybe the combination of snap trimming or other background work along with compaction is just totally thrashing the rocksdb block cache.  For folks that feel comfortable watching IO hitting your DB devices, can you see if you have increased bursts of reads to the DB device after a compaction event has occurred?  They look like this in the OSD logs: 2020-08-04T17:15:56.603+0000 7fb0cf60d700  4 rocksdb: (Original Log Time 2020/08/04-17:15:56.603585) EVENT_LOG_v1 {"time_micros": 1596561356603574, "job": 5, "event": "compaction_finished", "compaction_time_micros": 744532, "compaction_time_cpu_micros": 607655, "output_level": 1, "num_output_files": 2, "total_output_size": 84712923, "num_input_records": 1714260, "num_output_records": 658541, "num_subcompactions": 1, "output_compression": "NoCompression", "num_single_delete_mismatches": 0, "num_single_delete_fallthrough": 0, "lsm_state": [0, 2, 0, 0, 0, 0, 0]} You can also run this tool to get a nicely formatted list of them, though I don't have it reporting timestamps, just the time offset from the start of the log so looking at the OSD logs directly would be easier to match up timestamps. https://github.com/ceph/cbt/blob/master/tools/ceph_rocksdb_log_parser.py Mark On 8/6/20 8:07 AM, Vladimir Prokofev wrote:

In my case I only have 16GB RAM per node with 5 OSD on each of them, so I actually have to tune osd_memory_target=2147483648 because with the default value of 4GB my osd processes tend to get killed by OOM. That is what I was looking into before the correct solution. I disabled osd_memory_target limitation essentially setting it to default 4GB - it helped in a sense that workload on the block.db device significantly dropped, but overall pattern was not the same - for example there still were no merges on the block.db device. It all came back to the usual pattern with bluefs_buffered_io=true. osd_memory_target limitation was implemented somewhere around 10 > 12 release upgrade I think, before memory auto scaling feature for bluestore was introduced - that's when my osds started to get OOM. They worked fine before that. чт, 6 авг. 2020 г. в 20:28, Mark Nelson <mnelson(a)redhat.com>om>:

I cannot confirm that more memory target will solve the problem completly. In my case the OSDs have 14GB memory target and I did have huge user IO impact while snaptrim (many slow ops the whole time). Since I set bluefs_bufferd_io=true it seems to work without issue. In my cluster I don't use rgw. But I don't see why different types of access the cluster do affect the form the kernel manages its memory. My experience why the kernel begins to swap are mostly numa related and/or memory fragmentation. Manuel On Thu, 6 Aug 2020 15:06:49 -0500 Mark Nelson <mnelson(a)redhat.com> wrote: > a 2GB memory target will absolutely starve the OSDs of memory for > rocksdb block cache which probably explains why you are hitting the > disk for reads and a shared page cache is helping so much. It's > definitely more memory efficient to have a page cache scheme rather > than having more cache for each OSD, but for NVMe drives you can end > up having more contention and overhead.  For older systems with > slower devices and lower amounts of memory the page cache is probably > a win.  FWIW with a 4GB+ memory target I suspect you would see far > fewer cache miss reads (but obviously you can't do that on your > nodes). > > > Mark > > > On 8/6/20 1:47 PM, Vladimir Prokofev wrote: > > In my case I only have 16GB RAM per node with 5 OSD on each of > > them, so I actually have to tune osd_memory_target=2147483648 > > because with the default value of 4GB my osd processes tend to get > > killed by OOM. That is what I was looking into before the correct > > solution. I disabled osd_memory_target limitation essentially > > setting it to default 4GB > > - it helped in a sense that workload on the block.db device > > significantly dropped, but overall pattern was not the same - for > > example there still were no merges on the block.db device. It all > > came back to the usual pattern with bluefs_buffered_io=true. > > osd_memory_target limitation was implemented somewhere around 10 > > > 12 release upgrade I think, before memory auto scaling feature for > > bluestore was introduced - that's when my osds started to get OOM. > > They worked fine before that. > > > > чт, 6 авг. 2020 г. в 20:28, Mark Nelson <mnelson(a)redhat.com>om>: > > > >> Yeah, there are cases where enabling it will improve performance as > >> rocksdb can then used the page cache as a (potentially large) > >> secondary cache beyond the block cache and avoid hitting the > >> underlying devices for reads. Do you have a lot of spare memory > >> for page cache on your OSD nodes? You may be able to improve the > >> situation with bluefs_buffered_io=false by increasing the > >> osd_memory_target which should give the rocksdb block cache more > >> memory to work with directly. One downside is that we currently > >> double cache onodes in both the rocksdb cache and bluestore onode > >> cache which hurts us when memory limited. We have some > >> experimental work that might help in this area by better balancing > >> bluestore onode and rocksdb block caches but it needs to be > >> rebased after Adam's column family sharding work. > >> > >> The reason we had to disable bluefs_buffered_io again was that we > >> had users with certain RGW workloads where the kernel started > >> swapping large amounts of memory on the OSD nodes despite > >> seemingly have free memory available. This caused huge latency > >> spikes and IO slowdowns (even stalls). We never noticed it in our > >> QA test suites and it doesn't appear to happen with RBD workloads > >> as far as I can tell, but when it does happen it's really painful. > >> > >> > >> Mark

Sure. total used free shared buff/cache available Mem: 394582604 355494400 5282932 1784 33805272 29187220 Swap: 1047548 1047548 0 On the node are 24 14TB OSDs with 14G configured memory target. Manuel On Fri, 7 Aug 2020 11:24:53 +0200 Stefan Kooman <stefan(a)bit.nl> wrote:

Hi Mark, The read IOPs in "normal" operation was with bluefs_buffered_io=false somewhat about 1. And now with true around 2. So this seems slightly higher, but far away from any problem. While snapshot trimming the difference is enormous. with false: around 200 with true: around 10 scrubing read IOPs do not appear to be affected. They are around 100 IOPs I'am using librados to access my objects. So I don't know if this would be any different with rgw. Manuel On Fri, 7 Aug 2020 08:08:40 -0500 Mark Nelson <mnelson(a)redhat.com> wrote:

Hi Mark, rocskdb compactions was one of my first ideas as well. But they don't correlate. I checkt this with the ceph_rocskdb_log_parser.py from https://github.com/ceph/cbt.git I saw only a few compactions on the whole cluster. It didn't seem to be the problem, although the compactions sometimes took several seconds. BTW: I configured the following rocksdb options. bluestore rocksdb options = compression=kNoCompression,max_write_buffer_number=32,min_write_buffer_number_to_merge=2,recycle_log_file_num=32,compaction_style=kCompactionStyleLevel,write_buffer_size=67108864,target_file_size_base=67108864,max_background_compactions=31,level0_file_num_compaction_trigger=8,level0_slowdown_writes_trigger=32,level0_stop_writes_trigger=64,max_bytes_for_level_base=536870912,compaction_threads=32,max_bytes_for_level_multiplier=8,flusher_threads=8,compaction_readahead_size=2MB This reduced some IO spikes but the slowops isse while snaptim was not affected by this. Manuel On Fri, 7 Aug 2020 09:43:51 -0500 Mark Nelson <mnelson(a)redhat.com> wrote:

Hi, I'm facing this issue too and I see the attached rocksdb log from Mark in my cluster which means there is a burst read on my block.db. I've sent some information from my issue in this thread[1]. Hope you help me with what's going on in my cluster. Thanks. [1]: https://lists.ceph.io/hyperkitty/list/ceph-users@ceph.io/thread/PHB53F3OD7Q… On Mon, Aug 10, 2020 at 8:05 PM Mark Nelson <mnelson(a)redhat.com> wrote: