[rrd-users] Rrdtool for counting irregular events
linux at thehobsons.co.uk
Sat May 19 20:50:20 CEST 2012
Rafal Gwizdala wrote:
>Can rrdtool be used for measuring frequency of irregular events? I
>mean the updates would occur in irregular patterns and I'd like to
>measure the frequency of them / number of occurrences per some base
It's tricky - you can do it but there are significant compromises needed.
Firstly, you can set a long heartbeat value. That will allow you to
go a long time between updates without making the data become
unknown. But that alone will not deal with all the problems.
If you only update infrequently then you'll get some strange results.
Say you had an update at midnight, and then the next update wasn't
until the next midnight. Assuming heartbeat is long enough, then the
second update will result in the whole day being set at a uniform
(and very low) rate - eg if there were 3 events, then the rate would
be 3/86400 = 3.47e-5. Also, for the whole day, any graphs would show
as unknown - because until the second update, RRD cannot know what
value you may put in and hence it cannot "close off" any time steps.
Alternatively, if what you are saying is that you'll enter an update
of "1" each time <something> happens, then again you'll find yourself
with unknown data from the last completeted step until the next
update occurs. Then the whole period will show as a very low rate.
The later you should be able to work around by doing an update with 0
before each update with 1. Then you'll see long periods with a zero
rate, interspersed with short periods with a not so low rate. If your
step time was (say) 5 minutes (300 seconds), then a single event
within a 5 minute step time would result in a 5 minute period of rate
1/300 = 3.33e-3.
In order to get the unknown data to "go away", you could periodically
update with a value of 0 which will "complete" some step periods so
they show a value (mostly 0) instead of unknown. You will need to
figure out how to avoid clashes if the periodic update happens at the
same time as a real event.
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