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Downloadable SPLK-1004 PDF & Reliable SPLK-1004 Dumps Questions
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The Splunk SPLK-1004 exam is a timed, 57-question multiple-choice test that covers a variety of topics, including advanced search techniques, data modeling, field extractions, macros, and advanced visualizations. SPLK-1004 Exam also includes scenario-based questions that require the user to apply their knowledge to real-world situations.
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Splunk Core Certified Advanced Power User Sample Questions (Q98-Q103):
NEW QUESTION # 98
Which search generates a field with a value of "hello"?
- A. | makeresults field="hello"
- B. | makeresults | eval field="hello"
- C. | makeresults | fields="hello"
- D. | makeresults | eval field=make{"hello"}
Answer: B
Explanation:
The correct search to generate a field with a value of"hello"is:
Copy
1
| makeresults | eval field="hello"
Here's why this works:
* makeresults: This command creates a single event with no fields.
* eval: Theevalcommand is used to create or modify fields. In this case, it creates a new field namedfield and assigns it the value"hello".
Example:
| makeresults
| eval field="hello"
This will produce a result like:
_time field
------------------- -----
<current_timestamp> hello
References:
* Splunk Documentation onmakeresults:https://docs.splunk.com/Documentation/Splunk/latest
/SearchReference/Makeresults
* Splunk Documentation oneval:https://docs.splunk.com/Documentation/Splunk/latest/SearchReference
/Eval
NEW QUESTION # 99
Which commands should be used in place of a subsearch if possible?
- A. untable and/or xyseries
- B. mvexpand and/or where
- C. bin and/or where
- D. stats and/or eval
Answer: D
Explanation:
stats and eval are recommended over subsearches because they are more efficient and scalable. Subsearches can be slow and resource-intensive, whereas stats aggregates data, and eval performs calculations within the search.
The stats and eval commands should be used instead of subsearches whenever possible because subsearches have performance limitations. They return only a maximum of 10,000 results or execute within 60 seconds by default, which may cause incomplete results. Using stats allows aggregation of large datasets efficiently, while eval can manipulate field values within a search rather than relying on subsearches.
Reference:
Splunk Documentation - Stats Command
Splunk Documentation - Eval Command
NEW QUESTION # 100
Which search generates a field with a value of "hello"?
- A. | makeresults field="hello"
- B. | makeresults | eval field="hello"
- C. | makeresults | fields="hello"
- D. | makeresults | eval field=make{"hello"}
Answer: B
Explanation:
The correct search to generate a field with a value of"hello"is:
Copy
1
| makeresults | eval field="hello"
Here's why this works:
* makeresults: This command creates a single event with no fields.
* eval: Theevalcommand is used to create or modify fields. In this case, it creates a new field namedfield and assigns it the value"hello".
Example:
| makeresults
| eval field="hello"
This will produce a result like:
_time field
------------------- -----
<current_timestamp> hello
References:
Splunk Documentation onmakeresults:https://docs.splunk.com/Documentation/Splunk/latest/SearchReference
/Makeresults
Splunk Documentation oneval:https://docs.splunk.com/Documentation/Splunk/latest/SearchReference/Eval
NEW QUESTION # 101
Which of these generates a summary index containing a count of events by productId?
- A. | stats sum (productId)
- B. | stats count by productId
- C. sistats summary_index by productid
- D. | sistats count by productId
Answer: B
Explanation:
To generate a summary index containing a count of events by productId, the correct search command would be | stats count by productId (Option A). This command aggregates the events by productId, counting the number of events for each unique productId value. The stats command is a fundamental Splunk command used for aggregation and summarization, making it suitable for creating summary data like counts by specific fields.
NEW QUESTION # 102
Which of the following could be used to build a contextual drilldown?
- A. <set>and<unset>elements with adepend?attribute.
- B. <set>and<reset>elements with arejectsattribute.
- C. <set>and<offset>elements withdependsandrejectsattributes.
- D. $earliest$and$latest$tokens set by a global time range picker.
Answer: A
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 # 103
......
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