In other words, you only want count of matching records as well as count of non-matching records. Using a similar aggregation as @gcusello provides, but just do counts. | inputlookup ABC.csv
| eva...
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In other words, you only want count of matching records as well as count of non-matching records. Using a similar aggregation as @gcusello provides, but just do counts. | inputlookup ABC.csv
| eval lookup="ABC.csv"
| fields Firewall_Name lookup
| append [ | inputlookup XYZ.csv | eval lookup="XYZ.csv" | rename Firewall_Hostname AS Firewall_Name | fields Firewall_Name lookup ]
| stats values(lookup) as lookup by Firewall_Name
| eval lookup = if(mvcount(lookup) > 1, mvjoin(lookup, " + "), lookup . " only")
| stats count by lookup In the scenario you described, you will get a table like lookup count ABC.csv only 150 ABC.csv + XYZ.csv 849 XYZ.csv only 1 If you don't care about ABC.csv only, you can eliminate in the if function, like | inputlookup ABC.csv
| eval lookup="ABC.csv"
| fields Firewall_Name lookup
| append [ | inputlookup XYZ.csv | eval lookup="XYZ.csv" | rename Firewall_Hostname AS Firewall_Name | fields Firewall_Name lookup ]
| stats values(lookup) as lookup by Firewall_Name
| eval lookup = case(mvcount(lookup) > 1, mvjoin(lookup, " + "), lookup == "XYZ.csv", lookup . " only", true(), null())
| stats count by lookup