My datasets are much larger but these represent the crux of my hurdle
sourcetype=sale_by
fields: sid, user
sourcetype=sale_made
fields: sid, amount
Where: sale_made.sid = sale_by.sid
I have this search that works:
sourcetype=sale_by | join sid [ search sourcetype=sale_made ] | stats sum(amount) by user
Can this be done more efficiently with stats?
Hi eddiet,
Sure, try this:
sourcetype=sale_by OR sourcetype=sale_made
| stats values(user) AS user sum(amount) AS amount by sid
| stats values(amount) AS amount by user
This is not tested and also depends on your events and the expected result, but it should give you an idea how it can be done.
You can read this answer https://answers.splunk.com/answers/129424/how-to-compare-fields-over-multiple-sourcetypes-without-jo... to learn more about this topic.
Hope this helps ...
cheers, MuS
Try this:
sourcetype=sale_by OR sourcetype=sale_made
| stats values(user) AS user sum(amount) as amount BY sid
| stats sum(amount) as amount BY user
Hi eddiet,
Sure, try this:
sourcetype=sale_by OR sourcetype=sale_made
| stats values(user) AS user sum(amount) AS amount by sid
| stats values(amount) AS amount by user
This is not tested and also depends on your events and the expected result, but it should give you an idea how it can be done.
You can read this answer https://answers.splunk.com/answers/129424/how-to-compare-fields-over-multiple-sourcetypes-without-jo... to learn more about this topic.
Hope this helps ...
cheers, MuS
Wow, almost a jinx!