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The Splunk SPLK-1004 exam is delivered in a proctored, online format and consists of 70 multiple-choice questions. Candidates are given 90 minutes to complete the exam and must achieve a score of 75% or higher to pass. SPLK-1004 Exam is open to Splunk customers, partners, and employees who have completed the Splunk Core Certified User certification.
NEW QUESTION # 61
The fieldproductscontains a multivalued field containing the names of products. What is the result of the commandmvexpand products limit=<x>?
Answer: A
Explanation:
Comprehensive and Detailed Step by Step Explanation:Themvexpandcommand in Splunk is used to expand multivalue fields into separate events. When you usemvexpandon a field likeproducts, which contains multiple values, it creates a new event for each value in the multivalue field. For example, if the productsfield contains the values[productA, productB, productC], runningmvexpand productswill create three separate events, each containing one of the values (productA,productB, orproductC).
The optionallimit=<x>parameter specifies the maximum number of values to expand. Iflimit=2, only the first two values (productAandproductB) will be expanded into separate events, and any remaining values will be ignored.
Key points aboutmvexpand:
* It works only on multivalue fields.
* It does not modify the original field but creates new events based on its values.
* Thelimitparameter controls how many values are expanded.
Example:
| makeresults
| eval products="productA,productB,productC"
| makemv delim="," products
| mvexpand products
This will produce three separate events, one for each product.
References:
* Splunk Documentation onmvexpand:https://docs.splunk.com/Documentation/Splunk/latest
/SearchReference/mvexpand
NEW QUESTION # 62
Which of these generates a summary index containing a count of events byproduct_id?
Answer: D
Explanation:
The correct command to generate a summary index containing a count of events by product_id is:
sistats count by product_id
Here's why this works:
* sistats: This command is specifically designed for creating summary indexes. It pre-aggregates data and stores it in a format optimized for fast retrieval.
* count by product_id: This part of the command calculates the count of events grouped by the product_idfield.
Summary indexing is useful when you want to store pre-aggregated data for faster reporting. For example, instead of querying raw data every time, you can query the summary index to get quick results.
Other options explained:
* Option A: Incorrect becausestats si(product_id)is invalid syntax.
* Option B: Incorrect becausestatsis used for real-time aggregation but does not create summary indexes.
* Option D: Incorrect becausesistats summary index by product_idis invalid syntax.
Example:
index=main | sistats count by product_id
References:
* Splunk Documentation onsistats:https://docs.splunk.com/Documentation/Splunk/latest/SearchReference
/sistats
* Splunk Documentation on Summary Indexing:https://docs.splunk.com/Documentation/Splunk/latest
/Knowledge/Usesummaryindexing
NEW QUESTION # 63
Which of the following could be used to build a contextual drilldown?
Answer: D
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 # 64
Which of the following is true about the preview feature and macros?
Answer: D
Explanation:
Comprehensive and Detailed Step by Step Explanation:
Thepreview featurein Splunk expandsall macroswithin a search, including anynested macros, to show their full definitions. This allows users to review the complete structure of the search query after all macros have been resolved.
Here's why this works:
* Macro Expansion: Macros are placeholders for reusable search logic. When the preview feature is used, Splunk replaces all macro references with their corresponding definitions, including those nested within other macros.
* Full Visibility: Expanding all macros ensures that users can see the entire search logic, which is especially helpful for debugging or understanding complex queries.
Other options explained:
* Option A: Incorrect because the preview feature expands all macros, not just the selected one.
* Option B: Incorrect because the keyboard shortcutTab-Shift-Eis not valid for launching the preview feature.
* Option C: Incorrect because right-clicking on a macro name does not launch the preview feature; it is typically accessed through the Splunk UI or specific commands.
References:
Splunk Documentation on Macros:https://docs.splunk.com/Documentation/Splunk/latest/Knowledge
/Definesearchmacros
Splunk Documentation on Search Preview:https://docs.splunk.com/Documentation/Splunk/latest/Search
/Previewsearches
NEW QUESTION # 65
When using thebincommand, what attributes are used to define the size and number of sets created?
Answer: C
Explanation:
Comprehensive and Detailed Step by Step Explanation:Thebincommand in Splunk is used to group numeric or time-based data into discrete intervals (bins). The attributes used to define thesize and number of setsarebinsandspan.
Here's why this works:
* bins Attribute: Specifies the number of bins (intervals) to create. For example,bins=10divides the data into 10 equal-sized intervals.
* span Attribute: Specifies the size of each bin. For example,span=10creates bins of size 10 for numeric data orspan=1hcreates bins of 1-hour intervals for time-based data.
* Combination: You can use eitherbinsorspanto control the binning process, but not both simultaneously. If you specify both,spantakes precedence.
Other options explained:
* Option A: Incorrect becausestartandendare not attributes of thebincommand; they are unrelated to defining bin size or count.
* Option B: Incorrect becauseminspanis not a valid attribute of thebincommand.
* Option D: Incorrect becauselimitis unrelated to thebincommand; it is typically used in other commands likestatsortop.
Example:
index=_internal
| bin _time span=1h
This groups events into 1-hour intervals based on the_timefield.
References:
* Splunk Documentation onbin:https://docs.splunk.com/Documentation/Splunk/latest/SearchReference
/bin
* Splunk Documentation on Time-Based Binning:https://docs.splunk.com/Documentation/Splunk/latest
/Search/Chartbinneddata
NEW QUESTION # 66
......
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