Depending on your netflow export type, your routers should export the
sampling rate as part of the template packets (for netflow v9 at least).
Nfsen should pick this up and correct the interal values with this sampling
in mind. If it doesn't work, you can manually set a fixed sampling rate per
collector - inside nfsen.conf -> %sources:
%sources = (
'myRouter' => { 'port' => '9901', 'col' => '#00ff00', 'type' =>
'netflow', 'optarg' => ' -s -1000 '},
);
Quote from man nfcapd:
-s <rate>
Apply default sampling rate rate to all netflow records, unless
the sampling rate is announced by the exporting device. In that case the
announced sam-
pling rate is applied. If <rate> is negative, this will hard
overwrite any device specific announced sampling rates.
On Mon, Jun 16, 2014 at 10:09 PM, Scott Granados <sc...@granados-llc.net>
wrote:
> Hi,
> I am collecting data from several sources all at the same sample
> rate of 1:1000. My graphs how ever aren’t scaled accordingly. I’ve been
> googling but haven’t found a definite pointer as to how to set the sample
> rate or scaling correctly. Is there a knob I can set by source or what’s
> the best method to rescale my data or at least record / create graphs going
> forward with the appropriate scaling factor / sample rate. I’m running
> 1.3.6 NFSEN. Any pointers would be most appreciated. Also, other than the
> NFSEN homepage itself and the archives is there a good source for basic
> documentation and examples I can query first before providing noise on the
> list? :)
>
> Thanks
> Scott
>
>
>
> ------------------------------------------------------------------------------
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> Find What Matters Most in Your Big Data with HPCC Systems
> Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
> Leverages Graph Analysis for Fast Processing & Easy Data Exploration
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------------------------------------------------------------------------------
HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
Find What Matters Most in Your Big Data with HPCC Systems
Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
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