Re: Object Map Costs (Was: Snapshot Costs (Was: Re: Pool Sizes))

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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/a68106934c5ed28d0195d6104bce5981aca9aa9d/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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> ceph-users@xxxxxxxxxxxxxx
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