Splunk SPLK-1004 Online Practice Questions and Exam Preparation

Splunk SPLK-1004 Online Questions & Answers

• Question 31:

  Which of the following is accurate regarding predefined drilldown tokens?

  A. They capture data from a form Input.
  B. They vary by visualization type
  C. There are eight categories of predefined drilldown tokens.
  D. They are defined by a panel's base search.
  B. They vary by visualization type

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  Explanation/Reference:

  Predefined drilldown tokens in Splunk vary by visualization type (Option B). These tokens are placeholders that capture dynamic values based on user interactions with dashboard elements, such as clicking on a chart segment or table row. The specific tokens available and their meanings can differ depending on the type of visualization, as each visualization type may present and interact with data differently.

• Question 32:

  When using the bin command, which argument sets the bin size?

  A. mazDataSizeMB
  B. max
  C. volume
  D. span
  D. span

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  Explanation/Reference:

  When using the bin command in Splunk, the span argument is used to set the size of each bin (Option D). The span argument determines the granularity or width of each bin when segmenting data over a time range or numerical field, which is essential for time series analysis, histogram generation, or other aggregated data visualizations.

• Question 33:

  Which of the following is accurate about cascading inputs?

  A. They can be reset by an event handler.
  B. The final input has no impact on previous inputs.
  C. Only the final input of the sequence can supply a token to searches.
  D. Inputs added to panels can not participate.
  A. They can be reset by an event handler.

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  Explanation/Reference:

  Cascading inputs in Splunk dashboards allow the selection in one input (like a dropdown, radio button, etc.) to determine the available options in the subsequent input, creating a dependent relationship between them. An event handler can be configured to reset subsequent inputs based on the selection made in a preceding input (Option A), ensuring that only relevant options are presented to the user as they make selections. This approach enhances the dashboard's usability by guiding the user through a logical flow of choices, where each selection refines the scope of the following options.

• Question 34:

  Which of these generates a summary index containing a count of events by productId?

  A. | stats count by productId
  B. | stats sum (productId)
  C. | sistats count by productId
  D. sistats summary_index by productid
  A. | stats count by productId

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  Explanation/Reference:

  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.

• Question 35:

  What is a performance improvement technique unique to dashboards?

  A. Using stats instead of transaction
  B. Using global searches
  C. Using report acceleration
  D. Using datamodel acceleration
  C. Using report acceleration

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  Explanation/Reference:

  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.

• Question 36:

  Which commands can run on both search heads and indexers?

  A. Transforming commands
  B. Centralized streaming commands
  C. Dataset processing commands
  D. Distributable streaming commands
  D. Distributable streaming commands

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  Explanation/Reference:

  Distributable streaming commands in Splunk can run on both search heads and indexers (Option D). These commands operate on each event independently and can be distributed across indexers for parallel execution, which enhances search efficiency and scalability. This category includes commands like search, where, eval, and many others that do not require the entire dataset to be available to produce their output.

• Question 37:

  Which stats function is used to return a sorted list of unique field values?

  A. values
  B. sum
  C. count
  D. list
  A. values

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  Explanation/Reference:

  The values function in the stats command in Splunk is used to return a sorted list of unique field values (Option A). This function is particularly useful for summarizing data by listing all unique values of a specified field across the events returned by the search, which can provide insights into the diversity and distribution of the data associated with that field.

• Question 38:

  When possible, what is the best choice for summarizing data to improve search performance?

  A. Us the fieldsummary command.
  B. Data model acceleration
  C. Report acceleration
  D. Summary indexing
  D. Summary indexing

• Question 39:

  When using a nested search macro, how can an argument value be passed to the inner macro?

  A. The argument value may be passed to the outer macro.
  B. An argument cannot be used with an inner nested macro.
  C. An argument cannot be used with an outer nested macro.
  D. The argument value must be specified in the outer macro.
  A. The argument value may be passed to the outer macro.

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  Explanation/Reference:

  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.

• Question 40:

  Which of the following would exclude all entries contained in the lookup file baditems. csv from search results?

  A. NOT [inputlookup baditems.csv]
  B. NOT (lookup baditems.csv OUTPUT item)
  C. WHERE item NOT IN (baditems.csv)
  D. [NOT inputlookup baditems.csv]
  A. NOT [inputlookup baditems.csv]

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  Explanation/Reference:

  The correct syntax to exclude all entries contained in the lookup file baditems.csv from search results is NOT [inputlookup baditems.csv]. This syntax uses a subsearch with the inputlookup command to retrieve the contents of the baditems.csv lookup file and then uses the NOT operator to exclude those results from the main search. This approach is efficient for filtering out unwanted data based on a predefined list of criteria stored in a lookup file.