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Splunk Core Certified Advanced Power User Sample Questions (Q78-Q83):

NEW QUESTION # 78
Why is the transaction command slow in large splunk deployments?

A. transaction or runs on each Indexer in parallel.
B. transaction runs a hidden eval to format fields.
C. It forces all event data to be returned to the search head.
D. It forces the search to run in fast mode.

Answer: C

Explanation:
The transaction command can be slow in large Splunk deployments because it requires all event data relevant to the transaction to be returned to the search head (Option C). This process can be resource-intensive, especially for transactions that span a large volume of data or time, as it involves aggregating and sorting events across potentially many indexers before the transaction logic can be applied.

NEW QUESTION # 79
Which of the following has a schema or structure embedded in the data itself?

A. Dark data
B. Unstructured data
C. Self-describing data
D. Embedded data

Answer: C

Explanation:
Self-describing data includes information about its structure within the data itself. Examples include formats like JSON and XML, where the data schema is embedded and can be easily interpreted without external references.

NEW QUESTION # 80
Which of the following could be used to build a contextual drilldown?

A. <set>and<reset>elements with arejectsattribute.
B. <set>and<unset>elements with adepend?attribute.
C. <set>and<offset>elements withdependsandrejectsattributes.
D. $earliest$and$latest$tokens set by a global time range picker.

Answer: B

Explanation:
Comprehensive and Detailed Step by Step Explanation:
To build acontextual drilldownin Splunk dashboards, you can use<set>and<unset>elements with adepend?
attribute. These elements allow you to dynamically update tokens based on user interactions, enabling context- sensitive behavior in your dashboard.
Here's why this works:
* Contextual Drilldown: A contextual drilldown allows users to click on a visualization (e.g., a chart or table) and navigate to another view or filter data based on the clicked value.
* Dynamic Tokens: The<set>element sets a token to a specific value when a condition is met, while< unset>clears the token when the condition is no longer valid. Thedepend?attribute ensures that the behavior is conditional and context-aware.
Example:
<drilldown>
<set token="selected_product">$click.value$</set>
<unset token="selected_product" depend="?"></unset>
</drilldown>
In this example:
* When a user clicks on a value, theselected_producttoken is set to the clicked value ($click.value$).
* If the condition specified independ?is no longer true, the token is cleared using<unset>.
Other options explained:
* Option B: Incorrect because$earliest$and$latest$tokens are related to time range pickers, not contextual drilldowns.
* Option C: Incorrect because<reset>is not a valid element in Splunk XML, andrejectsis unrelated to drilldown behavior.
* Option D: Incorrect because<offset>is not used for building drilldowns, anddepends/rejectsdo not apply in this context.
References:
Splunk Documentation on Drilldowns:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/DrilldownIntro
Splunk Documentation on Tokens:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/UseTokenstoBuildDynamicInputs

NEW QUESTION # 81
Which of the following is true about themultikvcommand?

A. Themultikvcommand requires field names to be ALL CAPS whenmultitable=false.
B. Themultikvcommand displays an event for each row in a table-formatted event.
C. Themultikvcommand derives field names from the last column in a table-formatted event.
D. Themultikvcommand creates an event for each column in a table-formatted event.

Answer: B

Explanation:
Comprehensive and Detailed Step by Step Explanation:Themultikvcommand in Splunk is used to extract fields fromtable-like events(e.g., logs with rows and columns). It creates a separate event for each row in the table, making it easier to analyze structured data.
Here's why this works:
* Purpose of multikv: Themultikvcommand parses table-formatted events and treats each row as an individual event. This allows you to work with structured data as if it were regular Splunk events.
* Field Extraction: By default,multikvextracts field names from the header row of the table and assigns them to the corresponding values in each row.
* Row-Based Events: Each row in the table becomes a separate event, enabling you to search and filter based on the extracted fields.
Example: Suppose you have a log with the following structure:
Name Age Location
Alice 30 New York
Bob 25 Los Angeles
Using themultikvcommand:
| multikv
This will create two events:
Event 1: Name=Alice, Age=30, Location=New York
Event 2: Name=Bob, Age=25, Location=Los Angeles
Other options explained:
* Option A: Incorrect becausemultikvderives field names from the header row, not the last column.
* Option B: Incorrect becausemultikvcreates events for rows, not columns.
* Option C: Incorrect becausemultikvdoes not require field names to be in ALL CAPS, regardless of the multitablesetting.
References:
* Splunk Documentation onmultikv:https://docs.splunk.com/Documentation/Splunk/latest
/SearchReference/Multikv
* Splunk Documentation on Parsing Structured Data:https://docs.splunk.com/Documentation/Splunk
/latest/Data/Extractfieldsfromstructureddata

NEW QUESTION # 82
Which statement about the coalesce function is accurate?

A. It can return null or non-null values.
B. It can be used to create a new field in the results set.
C. It can take a maximum of two arguments.
D. It can take only a single argument.

Answer: B

Explanation:
The coalesce function returns the first non-null value from a list of fields, and it can be used within an eval expression to create a new field in the results set. This is useful when handling missing or inconsistent data across multiple fields.

NEW QUESTION # 83
......

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