SPLK-1004 Splunk Core Certified Advanced Power User Questions and Answers

The tstats command in Splunk is used to generate statistics on indexed fields, particularly from data models that have been accelerated (Option B). This command is highly efficient for summarizing large volumes of data because it operates on indexed-time summarizations rather than raw data, enabling faster search performance and reduced processing time. The tstats command is especially useful in scenarios where quick aggregation and analysis of indexed data are required, making it a powerful tool for exploring and reporting on data model information. While tstats can be seen as an alternative to some uses of the summary command (Option A), its primary utility is in its ability to leverage data model accelerations and indexed field statistics, rather than creating or referring to summary indexes. It does not specifically generate statistics on search-time fields (Option D) or create an accelerated data model (Option C), but rather it queries against existing accelerated data models.

Contextual drilldown (Option D) is the type of drilldown that allows passing a value from a user click (e.g., from a table row or chart element) into another dashboard or an external page. This feature enables the creation of interactive dashboards where clicking on a specific element dynamically updates another part of the dashboard or navigates to a different page with relevant information, using the clicked value as a context for the subsequent view.

Using report acceleration (Option C) is a performance improvement technique unique to dashboards in Splunk. Report acceleration involves pre-computing the results of a report (which can be a saved search or a dashboard panel) and storing these results in a summary index, allowing dashboards to load faster by retrieving the pre-computed data instead of running the full search each time. This technique is especially useful for dashboards that rely on complex searches or searches over large datasets.

A cascading input is used as a way to filter other input selections within a dashboard or form (Option C). It enables a dynamic user interface where the selection made in one input (e.g., a dropdown menu) determines the available options in another input. This setup allows for more intuitive and relevant user interactions, as each choice narrows down the subsequent options to ensure they are contextually appropriate.

When Splunk's lookup feature finds fewer than the minimum matches specified for each lookup value, it returns the default value NULL for those unmatched entries until the minimum match threshold is reached (Option A). This behavior ensures that lookups return consistent and expected results, even when the available data does not meet the specified criteria for a minimum number of matches.

Wildcards can be used in the from clause of the tstats command in Splunk (Option C). The from clause specifies the data model or dataset from which to retrieve the statistics, and using wildcards here allows users to query across multiple data models or datasets that share a common naming pattern, making the search more flexible and encompassing.

To always return events from between 2:00 AM and 5:00 AM, assuming a standard time zone across the environment, the correct Splunk search syntax is earliest=-2h@h AND latest=-5h@h (Option B). This syntax uses relative time modifiers to specify a range starting 2 hours ago from the current hour (-2h@h) and ending 5 hours ago from the current hour (-5h@h), effectively capturing the desired time window.

To create a Log Event alert action in Splunk, a power user needs the edit_alerts capability (Option D). This capability allows the user to configure and manage alert actions, including setting up alerts to log specific events based on predefined conditions within Splunk's alerting framework.

The | makeresults command in Splunk generates a single event containing default fields, with theprimary purpose of creating sample data or a placeholder event for testing and development purposes. The most notable field it generates is _time, but it does not create a specific 'results' field per se. However, it's commonly used to create a base event for further manipulation with eval or other commands in search queries for demonstration, testing, or constructing specific scenarios.

When searching against summary data in Splunk, it's common to reference the name of the saved search or report that populated the summary index. The correct search syntax to retrieve data from the summary index populated by a report named "Linux logins" is index=summary search_name="Linux logins" | top src_ip user (Option B). This syntax uses the search_name field, which holds the name of the saved search or report that generated the summary data, allowing for precise retrieval of the intended summary data.

To generate a field with a value of "hello" using the makeresults command in Splunk, the correct syntax is | makeresults | eval field="hello" (Option C). The makeresults command creates a single event, and the eval command is used to add a new field (named "field" in this case) with the specified value ("hello"). This is a common method for creating sample data or for demonstration purposes within Splunk searches.

The transaction command in Splunk groups events into transactions based on common fields or characteristics. For the transaction command to function correctly and group events into meaningful transactions, the incoming events must be supplied in ascending chronological order (Option C). This ensures that related events are sequenced correctly according to their occurrence over time, allowing for accurate transaction grouping and analysis

The valid syntax for using the split function in Splunk is ... | eval areaCodes = split(phoneNumber, "_") (Option B). The split function divides a string into an array of substrings based on a specified delimiter, in this case, an underscore. The resulting array is stored in the new field areaCodes.

The regex is passed to the makemv command in Splunk using the delim argument (Option B). This argument specifies the delimiter used to split a single string field into multiple values, effectively creating a multivalue field from a field that contains delimited data.

When using a nested search macro in Splunk, an argument value can be passed to the inner macro by specifying the argument in the outer macro's invocation (Option A). This allows the outer macro to accept arguments from the user or another search command and then pass those arguments into the inner macro, enabling dynamic and flexible macro compositions that can adapt based on input parameters.