Free Splunk SPLK-1002 Actual Exam Questions

Maybe A too? Using searchtypes command sounds like it could create event types directly from searches, which fits the question wording. So A, B, C, and D all seem possible.

D imo, because building event types from the search results is a quick and valid way in the UI. That option shouldn't be overlooked even if config editing is possible.

Yeah, totally agree with B here. The transaction command can get super slow when dealing with huge datasets since it tries to tie events together, which is more resource-heavy. Stats is designed for fast aggregations and works way better when you just want efficient summaries without event correlation overhead. So in large environments, B definitely makes the most sense.

Good point about scalability, B makes sense since transaction gets heavy fast.

A imo, because event types typically rely on simple search conditions, and A uses a subsearch that filters based on player_id, which can clearly define a specific set of events.

B/D? B has a clear condition with a where clause, which filters events nicely. D uses stats, but event types usually don’t need aggregation, so B might be more straightforward for defining an event type.

D imo, because many search commands, especially transaction, are tricky in workflows. I doubt you can just slap transaction commands into workflow actions without issues.

I’m with the idea that B is right because workflows typically involve scheduled searches rather than real-time ones. A feels off since default real-time doesn’t match usual workflow setups. B

Maybe A makes the most sense since data models organize info and pivots summarize it. Without a data model, pivots wouldn’t have a clean dataset to work from.

It’s A, pivots need the structured data models to work properly.

C imo, the Format menu is usually where you toggle display options like stack mode. A and B seem off since stack command and trellis layout don’t really fit stacking. D feels too limiting.

Maybe D makes the most sense because stack mode is something I’ve only ever seen with timecharts in tools like Splunk. Options A and C sound like they could work, but the stack command or format menu changes usually apply within timecharts specifically. B seems off since trellis layout is more about multiple small charts, not stacking data. So if the question is about a general chart and not specifically a timechart, D fits better since stack mode isn’t a universal feature for every chart type.

It’s D because a POST action usually needs to specify the URI, when to run (time range), and what to search for (search string). Post arguments might be optional or combined with search string here.

A/C? Label and URI are must-haves, but post arguments in C are what really define a POST action’s payload. Search string in A feels more like a filter, not data to send. So C makes more sense to me.

Option B doesn’t really fit because “dev” sounds too vague — it could mean deviation in general, not specifically sample standard deviation. C and D seem off since they’re either too wordy or combine unrelated terms. A is the cleanest and most straightforward function name matching what’s asked.

It’s A because “stdev” directly matches the common abbreviation for sample standard deviation, while the others either sound off or aren’t standard function names. For example, B “dev” could mean deviation but not specifically the sample standard deviation, and C/D include extra words that don’t fit typical syntax. This matches most stats tools I know, so A makes the most sense here.

I’m thinking A might be wrong since in a lot of systems tags are case-sensitive, so that would rule it out. C seems off too because tags usually come from predefined lists or metadata, not from searches themselves. B and D feel more on point since tags do connect to fields/values and help make data easier to handle. Does anyone know if tags are always linked to field/value pairs, or can they sometimes just be simple labels without that structure?

B imo, because tags link fields and values, improving clarity beyond just categorizing.

Eval results aren’t saved permanently; they’re just new fields created on the fly, so A.

A. The eval command basically calculates new fields on the fly during a search, so the results live in those temporary fields tied to each event. They don’t actually get saved anywhere outside that search context like an index or database. That’s why A makes the most sense here.

I’m pretty sure A (zoom out) doesn’t rerun the search since it just changes the view scale, not the data or filters. D, selecting a range, probably does rerun because it’s like applying a time filter. So I agree C (deselect) also won’t rerun since it just clears selection without triggering a new search. So A and C are the ones that don’t rerun.

I think B might rerun the search since selecting a bar often acts like applying a filter. So maybe just A and C don’t trigger a rerun, as they sound more like view adjustments than actual searches. Does that fit with what others see?

It’s A. Events are typically the raw data entries that come back from a search and can naturally be shown as a list. Transactions and statistical values are more aggregated or processed results, so they usually don’t display as simple lists. Even without knowing the exact platform, events make the most sense for list views since they represent individual records or hits.

Maybe A

This feels like A since custom regex is common for flexibility.

D imo, the question seems broad. While many tools do let you use your own regex, some have preset patterns and don't allow full custom regex, so it’s not always guaranteed.

Maybe D, since tags are usually used to filter with specific keywords.

B tbh, event types make more sense here since they’re basically categories for events based on what’s happening. Tags are more like labels you add manually, but event types are predefined categories that help sort events by their nature or search terms. That distinction feels important for this question.

D, since calculated fields usually use fields extracted during indexing or processing.

Maybe D here too. Calculated fields usually work off fields already available, and extracted fields fit that since they’re specifically pulled out during processing. A sounds tricky because fields generated within a search string might just be temporary or part of the expression itself, not really a base for calculation. B and C seem off since lookup tables and regex are more about data manipulation or extraction, not building new calculated values directly. So D feels like the safest bet based on how calculated fields typically function.