Collecting BlueStore per Object DB overhead

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Hi,

I've been investigating the per object overhead for BlueStore as I've
seen this has become a topic for a lot of people who want to store a lot
of small objects in Ceph using BlueStore.

I've writting a piece of Python code which can be run on a server
running OSDs and will print the overhead.

https://gist.github.com/wido/b1328dd45aae07c45cb8075a24de9f1f

Feedback on this script is welcome, but also the output of what people
are observing.

The results from my tests are below, but what I see is that the overhead
seems to range from 10kB to 30kB per object.

On RBD-only clusters the overhead seems to be around 11kB, but on
clusters with a RGW workload the overhead goes higher to 20kB.

I know that partial overwrites and appends contribute to higher overhead
on objects and I'm trying to investigate this and share my information
with the community.

I have two use-cases who want to store >2 billion objects with a avg
object size of 50kB (8 - 80kB) and the RocksDB overhead is likely to
become a big problem.

Anybody willing to share the overhead they are seeing with what use-case?

The more data we have on this the better we can estimate how DBs need to
be sized for BlueStore deployments.

Wido

# Cluster #1
osd.25 onodes=178572 db_used_bytes=2188378112 avg_obj_size=6196529
overhead=12254
osd.20 onodes=209871 db_used_bytes=2307915776 avg_obj_size=5452002
overhead=10996
osd.10 onodes=195502 db_used_bytes=2395996160 avg_obj_size=6013645
overhead=12255
osd.30 onodes=186172 db_used_bytes=2393899008 avg_obj_size=6359453
overhead=12858
osd.1 onodes=169911 db_used_bytes=1799356416 avg_obj_size=4890883
overhead=10589
osd.0 onodes=199658 db_used_bytes=2028994560 avg_obj_size=4835928
overhead=10162
osd.15 onodes=204015 db_used_bytes=2384461824 avg_obj_size=5722715
overhead=11687

# Cluster #2
osd.1 onodes=221735 db_used_bytes=2773483520 avg_obj_size=5742992
overhead_per_obj=12508
osd.0 onodes=196817 db_used_bytes=2651848704 avg_obj_size=6454248
overhead_per_obj=13473
osd.3 onodes=212401 db_used_bytes=2745171968 avg_obj_size=6004150
overhead_per_obj=12924
osd.2 onodes=185757 db_used_bytes=3567255552 avg_obj_size=5359974
overhead_per_obj=19203
osd.5 onodes=198822 db_used_bytes=3033530368 avg_obj_size=6765679
overhead_per_obj=15257
osd.4 onodes=161142 db_used_bytes=2136997888 avg_obj_size=6377323
overhead_per_obj=13261
osd.7 onodes=158951 db_used_bytes=1836056576 avg_obj_size=5247527
overhead_per_obj=11551
osd.6 onodes=178874 db_used_bytes=2542796800 avg_obj_size=6539688
overhead_per_obj=14215
osd.9 onodes=195166 db_used_bytes=2538602496 avg_obj_size=6237672
overhead_per_obj=13007
osd.8 onodes=203946 db_used_bytes=3279945728 avg_obj_size=6523555
overhead_per_obj=16082

# Cluster 3
osd.133 onodes=68558 db_used_bytes=15868100608 avg_obj_size=14743206
overhead_per_obj=231455
osd.132 onodes=60164 db_used_bytes=13911457792 avg_obj_size=14539445
overhead_per_obj=231225
osd.137 onodes=62259 db_used_bytes=15597568000 avg_obj_size=15138484
overhead_per_obj=250527
osd.136 onodes=70361 db_used_bytes=14540603392 avg_obj_size=13729154
overhead_per_obj=206657
osd.135 onodes=68003 db_used_bytes=12285116416 avg_obj_size=12877744
overhead_per_obj=180655
osd.134 onodes=64962 db_used_bytes=14056161280 avg_obj_size=15923550
overhead_per_obj=216375
osd.139 onodes=68016 db_used_bytes=20782776320 avg_obj_size=13619345
overhead_per_obj=305557
osd.138 onodes=66209 db_used_bytes=12850298880 avg_obj_size=14593418
overhead_per_obj=194086
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