Hi everyone,
I have a data set such as:
Log1: EventId + EventType1
Log 2: EventId + EventType2
Log 3: EventId + EventType1
Log 4: EventId + EventType2
Log 5: EventId + EventType1
The outcome I am trying to get is something like:
EventId + (evaluatedEvent3) + counts of evaluatedEvents3 per day
Where evaluatedEvent is the occurrence of Event1 and Event2 in a sequence. e.g. If one Event1 and one Event2 are present for ID, it will be counted as one. Similarly, if Event1 is +1 more than Event2, It should not be kept in the Event3 bucket for this ID.
TIA
Can you give an example of the output you would expect from your data example. Is Event1 the same as Log1 or the same as EventType1
It sounds like stats values(X) by eventId might be a solution for your question, but from the last statement, it might mean streamstats would be needed.
It is something like this:
3/12:
Log1: Processing decryptedRecord:{"account":"mainAccount1","EventType":"start"}
Log2: Processing decryptedRecord:{"account":"mainAccount1","EventType":"stop"}
Log3: Processing decryptedRecord:{"account":"mainAccount1","EventType":"start"}
Log4: Processing decryptedRecord:{"account":"mainAccount1","EventType":"stop"}
Log5: Processing decryptedRecord:{"account":"mainAccount1","EventType":"stop"}
4/12:
Log1: Processing decryptedRecord:{"account":"mainAccount1","EventType":"start"}
Log2: Processing decryptedRecord:{"account":"mainAccount1","EventType":"stop"}
Log3: Processing decryptedRecord:{"account":"mainAccount1","EventType":"start"}
my expected output:
| Date| account| Event| count|
| 3/12|mainAccount1| flap | 2|
|4/12| mainAccount1| flap | 1|
where 1 flap is the jump between consequitive start-stop
This example sets up your data as in your reply and then uses bin _time and stats to give you a solution, however, it is quite crude in that it will does not look for consecutive flaps, e.g. in your example you have two stop events on 3/12 with no intervening start, so if you have a start after that, this would not handle that case. You would probably need to use streamstats to handle that case.
Anyway, see where this gets you
| makeresults
| eval event="2020-12-03 10:00:00 Log1: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"start\"}
2020-12-03 10:00:01 Log2: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"stop\"}
2020-12-03 10:00:02 Log3: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"start\"}
2020-12-03 10:00:03 Log4: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"stop\"}
2020-12-03 10:00:04 Log5: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"stop\"}
2020-12-04 10:00:00 Log1: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"start\"}
2020-12-04 10:00:01 Log2: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"stop\"}
2020-12-04 10:00:02 Log3: Processing decryptedRecord:{\"account\":\"mainAccount1\",\"EventType\":\"start\"}"
| makemv tokenizer="(2.*})" event
| mvexpand event
| eval _time=strptime(event,"%F %T")
| rex field=event "Log\d: Processing decryptedRecord:(?<item>\{[^\}]*\})"
| table _time item
| spath input=item
| bin _time span=1d
| stats sum(eval(if(EventType="start",1,0))) as Starts sum(eval(if(EventType="stop",1,0))) as Stops by _time account
| eval flags=min(Starts,Stops)