Re: [HTCondor-users] accurate way to query the number of jobs globally

[Pek Daniel <pekdaniel@xxxxxxxxx>]

Thanks guys!

Steffen: if you have 10 million jobs, then condor_q have to process
and stream out to the pipe 10M * 80 (columns per line) = 800MByte of
data, and after wc -l have to read the whole thing just to get a
single number in the end. It sounds a bit of overshooting. But it's
possible that it's the best I can do....

Tim: that's what you have on condor_status -schedd output is most of
the time stale data. For example when I remove all my jobs from the
cluster, it still shows wrong numbers for a while (minutes), didn't
get updated instantly, even if condor_q -global already shows empty
queue.

Daniel

2014-02-28 15:25 GMT+01:00 Tim Theisen <tim@xxxxxxxxxxx>:
> Hi Daniel,
>
> Try:
>     condor_status -schedd
>
> It will give you the number of running jobs as well as a few other bits of
> information.
>
> ...Tim
>
>
> On 02/28/2014 08:03 AM, Pek Daniel wrote:
>>
>> Thanks for your answer!
>>
>> This command gives me back the complete list of jobs in the cluster,
>> which is undesirable in case of tens of millions of queued jobs - also
>> the list includes the non-running jobs, although I can help on it by
>> constraining the results.
>>
>> But what I need is only the _number_ of the _running_ jobs.
>>
>> Daniel
>>
>> 2014-02-28 14:51 GMT+01:00 Renaud Guezennec <renaud@xxxxxxx>:
>>>
>>> Hi,
>>>
>>> Try this :
>>> condor_q -global
>>>
>>> It may be useful.
>>>
>>>
>>> On 02/28/2014 02:45 PM, Pek Daniel wrote:
>>>>
>>>> Hi,
>>>>
>>>> I'd like to know what's the most efficient, but at the same time most
>>>> accurate way (stale data isn't acceptable, although strict consistency
>>>> isn't necessary either) to get _only the number_ of currently running
>>>> jobs in the cluster globally? I could write a python script for it,
>>>> but there might be a more efficient way which I don't know about...
>>>>
>>>> Thanks,
>>>> Daniel
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>
> --
> Tim Theisen
> Release Manager
> HTCondor & Open Science Grid
> Center for High Throughput Computing
> Department of Computer Sciences
> University of Wisconsin - Madison
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