Hi @gcusello,  Thanks for your inputs. A follow up question, Do I have to expect any data loss during the upgrade? or is the add-on capable of backfilling the data lost during the time of upgrade. Also do I need to restart splunk on my server for the changes to reflect?

JSON array must first be converted to multivalue before you can use mv-functions.  The classic method to do this is mvexpand together with spath.   | spath input=spec path=spec.containers{} | mvexpand spec.containers{} | spath input=spec.containers{} | where privileged == "true"   With your sample data, output is like name privileged spec.containers{} spec.field1 spec.field2 spec.field3 A true { "name": "A", "privileged": "true" } X Y Z C true { "name": "C", "privileged": "true" } X Y Z If the array is big and events are many, mvexpand risk running out of memory.  So, Splunk 8 introduced a group of JSON functions.  The following is more memory efficient (and likely more efficient in general), but the output is multivalued.   | spath input=spec path=spec.containers{} | fields - spec.containers{}.* | eval privileged_containers = mvfilter(json_extract('spec.containers{}', "privileged") == "true")   Your sample data would give something like privileged_containers spec.containers{} spec.field1 spec.field2 spec.field3 { "name": "A", "privileged": "true" } { "name": "C", "privileged": "true" } { "name": "A", "privileged": "true" } { "name": "B" } { "name": "C", "privileged": "true" } X Y Z   BTW, please post JSON in raw text and make sure the format is compliant with proper quotes, etc. so volunteers don't have to waste time reconstruct data or worry about noncompliant data.  Here is a compliant emulation that you can play with and compare with real data   | makeresults | eval _raw = "{\"spec\": { \"field1\": \"X\", \"field2\": \"Y\", \"field3\": \"Z\", \"containers\": [ { \"name\": \"A\", \"privileged\": \"true\" }, { \"name\": \"B\" }, { \"name\": \"C\", \"privileged\": \"true\" } ] }}" | spath ``` data emulation above ```   Hope this helps.

If i use the following command, it truncates everything in the second query so that I only have one unique value for every other fields index=main measurement_type=loadTime screen_class_name=HomeFragment | join sessionId [search index=api_analytics sourcetype=api_analytics | `expand_api_analytics` | search iri=home/header | spath input=analytic path=session_id output=sessionId]  

You are still thinking in SQL terms.  Splunk's "schema on the fly" means there is no predefined "primary key" in any data.  Any key, or combination of keys, or evaluation expression with any key or combination of keys, can be used as "primary key". So for example, if I have 3 events with that field value in dataset A and 4 events with that particular field value in dataset B, then I expect to have 12 events in the result dataset (after the merge). What Splunk command/s would be useful to merge these datasets in this fashion?  It is much more profitable for you to share some sample data (anonymize as necessary, or use proper mock data, in text), then describe the desired output.  From your verbal description, it seems that you want an outer join of sorts. The simplest, and perhaps the fastest command would be stats.  To illustrate, I assume that you want to preserve all other fields in both datasets. (<dataset A>) OR (<dataset B>) | stats values(*) as * by not_a_primary_key_but_is_common_in_both_A_and_B Hope this helps

This works and makes total sense. First initialize values in the lookup table and then craft an appended search that will perform stats from the search and populate the lookup table. It's Gold Jerry, Gold Jerry!    

ok,Will try to explain.. Actually, we are having predefined time range filter as "previous month" in time filter.. previous month= -1mon@mon and @mon .(ex: august month) When I am loading the dashboard, I am able to see different data and user from different location, they used to see different data. becoz of -1mon@mon condition used in the time range filter..(taking different epoc time, as starting day of me and other location user is different). So, we tried to use the below query, | eval lnum=if(match("1690848000","^[@a-zA-Z]+"),"str","num"), enum=if(match("1688169600","[a-zA-Z]"),"str","num") | eval latest=case(isnum(1690848000),(1690848000-60),"1690848000"="now",now(),"1690848000"="",now(),lnum!="str","1690848000",1=1,relative_time(now(), "1690848000")) | eval earliest=case(isnum(1688169600),(1688169600-60),"1688169600"="0","0",enum!="str","1688169600",1=1,relative_time(now(), "1688169600")) In this query, if I use without isnum condition , it is working for previous month( same for all location users), if i include isnum condition , its not working. Becoz, isnum is not accepting double quotes(isnum(123), not isnum("123")) and previous month condition(1mon@mon, @mon) is not accepting without double quotes. This the issue we are facing, Can you pls suggest any change in query or any suggestions to fix this?? @yuanliu  And also one other query(for other requirement), how can remove the presets from time range filter?   Highly appreciated if this issue got resolved