I have two sets of data:
1. sourcetype=app "DEBUG A" function=UpdateCartItemStatus status=Rejected
2. sourcetype=app "DEBUG B" function=UpdateCartItemStatus
Set 1 (DEBUG A) also has the fields unitID1, unitID2, and user1
Set 2 (DEBUG B) also has the fields unitID1, unitID2, and user2
I would like to join data set 1 with data set 2 on unitID1 and unitID2 and get a count of the number of instances this occurs per user2. Ideally this would be as efficient as possible as the data sources are large, searches can span long periods of time, and they are constantly being refreshed. A join is not required, it was just the first thing I thought of.
I am using the dashboard editor for Splunk Enterprise.
Hm...let me clarify:
I want to count how many times Mary updated the status as "Printed" and DEBUG A reported that it was Rejected. The output should have a count of 2 for user=Mary.
Thus, I want to link datapoint 3 to datapoint 1 on and datapoint 4 to datapoint 2 using unitID1 and unitID2.
How about this
search to get all data using append | transaction unitID2 unitID1 startswith="debug=A" endswith="debug=B" maxevents=2 keepevicted=f
transaction command has a few more options you can explore
Yes, all four of those datapoints would have the same unitID1, but there are millions of datapoints with different unitIDs. We know 3 should be linked to 1 because they share the same unitID1 and unitID2.