Hi,
Depending on how you plan to use the omap - you might also want to avoid a large number of key/value pairs as well. CephFS got it's directory fragment size capped due to large omaps being painful to deal with (see: http://tracker.ceph.com/issues/16164 and http://tracker.ceph.com/issues/16177).
Cheers,
KJ
On Thu, Mar 9, 2017 at 3:02 PM, Max Yehorov <myehorov@xxxxxxxxxx> wrote:
re: python library
you can do some mon calls using this:
##----------
from ceph_argparse import json_command as json_command
rados_inst = rados.Rados(....)
cluster_handle = rados_inst.connect()
cmd = {'prefix': 'pg dump', 'dumpcontents': ['summary', ], 'format': 'json'}
retcode, jsonret, errstr = json_command(cluster_handle, argdict=cmd)
##----------
MON commands
https://github.com/ceph/ceph/blob/ a68106934c5ed28d0195d6104bce59 81aca9aa9d/src/mon/ MonCommands.h
On Wed, Mar 8, 2017 at 2:01 PM, Kent Borg <kentborg@xxxxxxxx> wrote:
> I'm slowly working my way through Ceph's features...
>
> I recently happened upon object maps. (I had heard of LevelDB being in there
> but never saw how to use it: That's because I have been using Python! And
> the Python library is missing lots of features! Grrr.)
>
> How fast are those omap calls?
>
> Which is faster: a single LevelDB query yielding a few bytes vs. a single
> RADOS object read of that many bytes at a specific offset?
>
> How about iterating through a whole set of values vs. reading a RADOS object
> holding the same amount of data?
>
> Thanks,
>
> -kb, the Kent who is guessing LevelDB will be slower in both cases, because
> he really isn't using the key/value aspect of LevelDB but is still paying
> for it.
>
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