join or append are the most intuitive direction to go in, but it's not very efficient and it's pretty cumbersome.
I will show what can be done by using a run everywhere example. This will report on one field user which is available in both sourcetypes and some others group or run_time which is only available in one sourcetype.
The use case here is to show which user, group and run_time we have per date_hour.
Let's start with the obvious one: Have you met chart?
index=_internal earliest=-2h@h latest=-0h@h sourcetype=splunkd OR sourcetype=scheduler | chart values(user) AS user values(group) AS group values(run_time) AS run_time by date_hour
The next obvious will be: Have you met stats?
index=_internal earliest=-2h@h latest=-0h@h sourcetype=splunkd OR sourcetype=scheduler | stats values(user) AS user values(group) AS group values(run_time) AS run_time by date_hour
Now move on for some fancy stats stuff?
index=_internal earliest=-2h@h latest=-0h@h sourcetype=splunkd OR sourcetype=scheduler
| eval hour-{sourcetype}=date_hour
| stats values(hour-*) AS * values(user) AS user values(group) AS group values(run_time) AS run_time
| mvexpand splunkd
| mvexpand scheduler
| where splunkd=scheduler
| rename splunkd AS date_hour
| fields - scheduler
the eval on hour-{sourcetype}=date_hour will create a new field which looks in this case like hour-splunkd and hour-scheduler which will be used later in the where clause....
or another nice run everywhere example:
index=_internal sourcetype="splunkd" OR sourcetype="splunk_web_access" | streamstats count by status, idx, sourcetype | stats values(idx) AS idx, values(status) AS status, values(sourcetype) AS sourcetype | mvexpand status | eval Status = if(match(idx,status), "MATCH", "NO MATCH") | table status, idx, Status
So why all this hustle and not use join instead?
Because it is not neccesary to join all search just because you have different sources.
Because you can use stats or chart for it.
Because it will be faster.
Because it is fun to challenge basic Splunk commands and do some tricks with them 🙂
Just for the record, all the above example run on my laptop and Splunk 6 for about 2.5 seconds while the join to get the same result take about 4.5 seconds:
index=_internal sourcetype=splunkd earliest=-2h@h latest=-0h@h | join date_hour [ search index=_internal sourcetype=scheduler earliest=-2h@h latest=-0h@h ] | stats values(date_hour) AS date_hour values(user) AS user values(group) AS group
One more thing: I know that in some use cases one is forced to use join or append, but before that - just give stats a chance .....
cheers, MuS
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