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Splunk SPLK-1004 exam measures the candidate's ability to create complex searches, calculations, and reports using Splunk Enterprise. SPLK-1004 exam also evaluates the candidate's understanding of advanced visualization techniques, including the creation of dashboards and charts. Furthermore, the exam tests the candidate's ability to manage Splunk Enterprise, including configuration, data management, and advanced security features. Additionally, the exam assesses the candidate's understanding of the Splunk platform's detailed architecture, data modeling, and data normalization concepts.
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Splunk Core Certified Advanced Power User Sample Questions (Q100-Q105):
NEW QUESTION # 100
Which of the following best describes the process for tokenizing event data?
Answer: D
Explanation:
The process for tokenizing event data in Splunk is best described as breaking the event data up by major breakers and then further breaking it up by minor breakers (Option B). Major breakers typically identify the boundaries of events, while minor breakers further segment the event data intofields. This hierarchical approach to tokenization allows Splunk to efficiently parse and structure the incoming data for analysis.
NEW QUESTION # 101
What are the four types of event actions?
Answer: C
Explanation:
The four types of event actions in Splunk are eval, link, change, and clear (Option C). These actions can be used in dashboard panel configurations to dynamically interact with or manipulate event data based on user inputs or other criteria. Eval is used for calculating fields, link for creating hyperlinks, change for modifying field values, and clear for removing field values or other data elements.
NEW QUESTION # 102
What is one way to troubleshoot dashboards?
Answer: D
Explanation:
Comprehensive and Detailed Step by Step Explanation:
One effective way to troubleshoot dashboards in Splunk is to create an HTML panel using tokens to verify that tokens are being set correctly. This allows you to debug token values and ensure that dynamic behavior (e.
g., drilldowns, filters) is functioning as expected.
Here's why this works:
* HTML Panels for Debugging : By embedding an HTML panel in your dashboard, you can display the current values of tokens dynamically. For example:
<html>
Token value: $token_name$
</html>
* This helps you confirm whether tokens are being updated correctly based on user interactions or other inputs.
* Token Verification: Tokens are essential for dynamic dashboards, and verifying their values is a critical step in troubleshooting issues like broken drilldowns or incorrect filters.
Other options explained:
* Option B: Incorrect because deleting and recreating a dashboard is not a practical or efficient troubleshooting method.
* Option C: Incorrect because there is no specific "Troubleshooting dashboard" in the Searching and Reporting app.
* Option D: Incorrect because theprevious_searchescommand is unrelated to dashboard troubleshooting; it lists recently executed searches.
References:
Splunk Documentation on Dashboard Troubleshooting:https://docs.splunk.com/Documentation/Splunk/latest
/Viz/Troubleshootdashboards
Splunk Documentation on Tokens:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/UseTokenstoBuildDynamicInputs
NEW QUESTION # 103
Which of the following statements is accurate regarding the append command?
Answer: C
Explanation:
The append command in Splunk is often used with a subsearch to add additional data to the end of the primary search results, and it can access historical data (Option B). This capability is useful for combining datasets from different time ranges or sources, enriching the primary search results with supplementary information.
NEW QUESTION # 104
Which of the following statements is correct regarding bloom filters?
Answer: D
Explanation:
Comprehensive and Detailed Step by Step Explanation:The correct statement about bloom filters in Splunk is:
Copy
1
Hot buckets have no bloom filters as their contents are always changing.
Here's why this is correct:
* Bloom Filters: Bloom filters are data structures used by Splunk to quickly determine whether a specific value exists in a bucket. They are designed for cold and warm buckets where the data is static.
* Hot Buckets: Hot buckets contain actively ingested data, which is constantly changing. Since bloom filters are precomputed and immutable, they cannot be applied to hot buckets.
Other options explained:
* Option B: Incorrect because bloom filters can only return false positives (indicating a value might exist when it doesn't), but they never return false negatives.
* Option C: Incorrect because all buckets use the same hashing algorithm to create bloom filters.
* Option D: Incorrect because bloom filters only contain binary values (0 or 1), not trinary values.
References:
* Splunk Documentation on Bloom Filters:https://docs.splunk.com/Documentation/Splunk/latest/Indexer
/Bloomfilters
* Splunk Documentation on Buckets:https://docs.splunk.com/Documentation/Splunk/latest/Indexer
/HowSplunkstoresindexes
NEW QUESTION # 105
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