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Splunk SPLK-1004 Latest Learning Material, Real SPLK-1004 Exam Questions

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Splunk Core Certified Advanced Power User Sample Questions (Q116-Q121):

NEW QUESTION # 116
Which field Is requited for an event annotation?

A. _time
B. annotation_label
C. annotation_category
D. eventype

Answer: A

Explanation:
For an event annotation in Splunk, the required field is time (Option B). The time field specifies the point or range in time that the annotation should be applied to in timeline visualizations, making it essential for correlating the annotation with the correct temporal context within the data.

NEW QUESTION # 117
What are the four types of event actions?

A. eval, link, set, and unset
B. stats, target, set, and unset
C. eval, link, change, and clear
D. stats, target, change, and clear

Answer: C

Explanation:
The four types ofevent actionsin Splunk are:
* eval: Allows you to create or modify fields using expressions.
* link: Creates clickable links that can redirect users to external resources or other Splunk views.
* change: Triggers actions when a field's value changes, such as highlighting or formatting changes.
* clear: Clears or resets specific fields or settings in the context of an event action.
Here's why this works:
* These event actions are commonly used in Splunk dashboards and visualizations to enhance interactivity and provide dynamic behavior based on user input or data changes.
Other options explained:
* Option A: Incorrect becausestatsandtargetare not valid event actions.
* Option B: Incorrect becausesetandunsetare not valid event actions.
* Option D: Incorrect becausestatsandtargetare not valid event actions.
References:
Splunk Documentation on Event Actions:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/EventActions
Splunk Documentation on Dashboard Interactivity:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/PanelreferenceforSimplifiedXML

NEW QUESTION # 118
Repeating JSON data structures within one event will be extracted as what type of fields?

A. Single value
B. Mvindex
C. Multivalue
D. Lexicographical

Answer: C

Explanation:
Repeating JSON data structures within a single event in Splunk are extracted as multivalue fields (Option C).
Multivalue fields allow a single field to contain multiple distinct values, which is common with JSON data structures that include arrays or repeated elements. Splunk's field extraction capabilities automatically recognize and parse these structures, allowing users to work with each value within the multivalue field for analysis and reporting

NEW QUESTION # 119
When using thebincommand, what attributes are used to define the size and number of sets created?

A. binsandminspan
B. binsandspan
C. binsandlimit
D. binsandstartandend

Answer: B

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 # 120
When should summary indexing be used?

A. For reports that run over short time ranges.
B. For reports that run in Smart Mode.
C. For reports that do not qualify for report or data model acceleration.
D. For reports that run on small datasets over long time ranges.

Answer: D

Explanation:
Comprehensive and Detailed Step by Step Explanation:
Summary indexing should be used forreports that run on small datasets over long time ranges. It is particularly useful when you need to aggregate data over extended periods without querying raw events repeatedly.
Here's why this works:
* Efficiency: Summary indexing pre-aggregates data into summary indexes, reducing the amount of data that needs to be processed during runtime. This improves performance for reports that span long time ranges.
* Small Datasets: Summary indexing is most effective when working with smaller datasets because aggregating large volumes of data can become resource-intensive.
Other options explained:
* Option B: Incorrect because summary indexing is not a fallback for reports that fail to qualify for acceleration methods like report or data model acceleration.
* Option C: Incorrect because summary indexing is less beneficial for short time ranges, where querying raw data is often faster.
* Option D: Incorrect because Smart Mode is unrelated to summary indexing; it is a search optimization feature.
Example: Suppose you want to calculate daily sales totals over a year. Instead of querying raw sales data every time, you can use summary indexing to store daily totals and query the summary index instead.
References:
Splunk Documentation on Summary Indexing:https://docs.splunk.com/Documentation/Splunk/latest
/Knowledge/Usesummaryindexing
Splunk Documentation on Report Acceleration:https://docs.splunk.com/Documentation/Splunk/latest
/Knowledge/Acceleratedatamodels

NEW QUESTION # 121
......

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