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foreach and fit

Path Finder

I have a timechart with more than 1 time series and would like to run the fit command on each of the time series separately.

Is this possible with foreach or is another approach needed?

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0 Karma


Another approach is needed. What are you actually trying to achieve (ideally from the raw events rather than assume timechart is the place to start)?

0 Karma

Path Finder

The events contains ifHCInOctets counters for switch ports which I calculate the bandwidth.

{"timestamp": "2021-05-01T00:40:02", "device": "switch1", "port_id": "1/0/g2", "port_alias": "LONDON1_Gi1_0_2", "port_type": "network", "ifHCInOctets": "386349938202882"}

By specifying a specific switch port (port_id=1/0/g2), I am able to fit the time series to an algorithm but this approach is not scalable.

index=main sourcetype=_json port device=switch1 port_alias=LONDON* port_id=1/0/g2
| streamstats window=1 global=f current=f last(ifHCInOctets) as last_in by port_id 
| eval in_change = last_in - ifHCInOctets 
| where in_change>=0 
| eval inMbps=in_change*8/1000/1000
| eval c_time=strftime(_time,"%m/%d/%y %H:%M:%S")
| timechart span=15m per_second(inMbps) by port_id
| eval date_minutebin=strftime(_time, "%M")
| eval date_hour=strftime(_time, "%H")
| eval date_wday=strftime(_time, "%A")
| fit DensityFunction 1/0/g2 by "date_minutebin,date_hour,date_wday" into switch1_1_0_g2 threshold=0.05 dist=norm

I would like to fit multiple switch ports (port_id=1/0/g*) into each of their seperate models in one search.

Then afterwards, I would like to apply multiple switch port models to their new respective time series data (using the same approach?).

0 Karma
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