[Nov 21, 2025] Pass Splunk Core Certified Power User SPLK-1002 Exam With 296 Questions
Ultimate Guide to Prepare Free Splunk SPLK-1002 Exam Questions and Answer
NEW QUESTION # 40
Which of the following actions can the evalcommand perform?
- A. Save SPL commands to be reused in other searches.
- B. Group transactions by one or more fields.
- C. Create or replace an existing field.
- D. Remove fields from results.
Answer: D
NEW QUESTION # 41
Which syntax is used to represent an argument in a macro definition?
- A. 'argument'
- B. $argument$
- C. %argument%
- D. "argument"
Answer: B
Explanation:
The correct answer is D.
A search macro is a way to reuse a piece of SPL code in different searches. A search macro can take
arguments, which are variables that can be replaced by different values when the macro is called.A search
macro can also contain another search macro within it, which is called a nested macro1.
To represent an argument in a macro definition, you need to use the dollar sign ($) character to enclose the
argument name. For example, if you want to create a search macro that takes one argument named "object",
you can use the following syntax:
[my_macro(object)] search sourcetype=object
This will create a search macro named my_macro that takes one argument named object. When you call the
macro in a search, you need to provide a value for the object argument, such as:
my_macro(web)
This will replace the object argument with the value web and run the following SPL code:
search sourcetype=web
The other options are not correct because they use quotation marks (' or ") or percentage signs (%) to represent
arguments, which are not valid syntax for macro arguments. These characters will be interpreted as literal
values instead of variables.
References:
Use search macros in searches
NEW QUESTION # 42
Which group of users would most likely use pivots?
- A. Knowledge Managers
- B. Architects
- C. Users
- D. Administrators
Answer: A
Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Pivot/IntroductiontoPivot
NEW QUESTION # 43
If there are fields in the data with values that are " " or empty but not null, which of the following would add a
value?
- A. | eval notNULL = "" | nullfill value=0 notNULL
- B. | eval notNULL = "" fillnull value=0 notNULL
- C. | eval notNULL = if(isnull (notNULL), "0" notNULL)
- D. | eval notNULL = if(isnull (notNULL), "0"
Answer: B
Explanation:
The correct answer is D. | eval notNULL = "" fillnull value=0 notNULL
Option A is incorrect because it is missing a comma between the "0" and the notNULL in the if
function. The correct syntax for the if function is if (condition, true_value, false_value).
Option B is incorrect because it is missing the false_value argument in the if function. The correct
syntax for the if function is if (condition, true_value, false_value).
Option C is incorrect because it uses the nullfill command, which only replaces null values, not empty
strings. The nullfill command is equivalent to fillnull value=null.
Option D is correct because it uses the eval command to assign an empty string to the notNULL field,
and then uses the fillnull command to replace the empty string with a zero. The fillnull command can
replace any value with a specified replacement, not just null values.
NEW QUESTION # 44
Which of the following searches will return events contains a tag name Privileged?
- A. Tag= Priv
- B. Tag= Priv*
- C. Tag= Pri*
- D. Tag= Privileged
Answer: C
Explanation:
Reference:https://docs.splunk.com/Documentation/PCI/4.1.0/Install/PrivilegedUserActivity
NEW QUESTION # 45
When would a user select delimited field extractions using the Field Extractor (FX)?
- A. When the file has a header that might provide information about its structure or format.
- B. With structured files such as JSON or XML.
- C. When a log file has values that are separated by the same character, for example, commas.
- D. When a log file contains empty lines or comments.
Answer: C
Explanation:
The correct answer is A. When a log file has values that are separated by the same character, for example, commas.
The Field Extractor (FX) is a utility in Splunk Web that allows you to create new fields from your events by using either regular expressions or delimiters. The FX provides a graphical interface that guides you through the steps of defining and testing your field extractions1.
The FX supports two field extraction methods: regular expression and delimited. The regular expression method works best with unstructured event data, such as logs or messages, that do not have a consistent format or structure. You select a sample event and highlight one or more fields to extract from that event, and the FX generates a regular expression that matches similar events in your data set and extracts the fields from them1.
The delimited method is designed for structured event data: data from files with headers, where all of the fields in the events are separated by a common delimiter, such as a comma, a tab, or a space. You select a sample event, identify the delimiter, and then rename the fields that the FX finds1.
Therefore, you would select the delimited field extraction method when you have a log file that has values that are separated by the same character, for example, commas. This method will allow you to easily extract the fields based on the delimiter without writing complex regular expressions.
The other options are not correct because they are not suitable for the delimited field extraction method. These options are:
* B. When a log file contains empty lines or comments: This option does not indicate that the log file has a structured format or a common delimiter. The delimited method might not work well with this type of data, as it might miss some fields or include some unwanted values.
* C. With structured files such as JSON or XML: This option does not require the delimited method, as Splunk can automatically extract fields from JSON or XML files by using indexed extractions or search-time extractions2. The delimited method might not work well with this type of data, as it might not recognize the nested structure or the special characters.
* D. When the file has a header that might provide information about its structure or format: This option does not indicate that the file has a common delimiter between the fields. The delimited method might not work well with this type of data, as it might not be able to identify the fields based on the header information.
References:
* Build field extractions with the field extractor
* Configure indexed field extraction
NEW QUESTION # 46
How is a macro referenced in a search?
- A. By using the macroname command.
- B. By enclosing the macro name in backtick characters (').
- C. By enclosing the macro name in single-quote characters (').
- D. By using the macro command.
Answer: B
Explanation:
The correct answer is C. By enclosing the macro name in backtick characters (`).
A macro is a way to reuse a piece of SPL code in different searches. A macro can take arguments, which are variables that can be replaced by different values when the macro is called. A macro can also contain another macro within it, which is called a nested macro1.
To reference a macro in a search, you need to enclose the macro name in backtick characters (). For example, if you have a macro named my_macro` that takes one argument, you can reference it in a search by using the following syntax:
| my_macro(argument) | ...
This will replace the macro name and argument with the SPL code contained in the macro definition. For example, if the macro definition is:
[my_macro(argument)] search sourcetype=$argument$
And you reference it in a search with:
index=main | my_macro(web) | stats count by host
This will expand the macro and run the following SPL code:
index=main | search sourcetype=web | stats count by host
References:
* Use search macros in searches
NEW QUESTION # 47
Which of the following options should a user add to a search to limit transactions to a five minute time window?
- A. duration=5m
- B. bin=5m
- C. earliest=-5m
- D. maxspan=5m
Answer: D
Explanation:
The maxspan option in the transaction command limits the maximum time span of the transaction to the specified duration, in this case, 5 minutes. This ensures that only events within that time window are grouped into one transaction.
Reference:
Splunk Power User Study Guide, Transaction Command
Splunk Docs: transaction Command
"maxspan sets the maximum time span allowed for transactions."
NEW QUESTION # 48
Which of the following statements describes this search?
sourcetype=access_combined I transaction JSESSIONID | timechart avg (duration)
- A. This is a valid search and will display a stats table showing the maximum pause among transactions.
- B. No results will be returned because the transaction command must include the startswith and endswith
options. - C. This is a valid search and will display a timechart of the average duration, of each transaction event.
- D. No results will be returned because the transaction command must be the last command used in the search pipeline.
Answer: C
Explanation:
This search uses the transaction command to group events that share a common value for JSESSIONID into
transactions1. The transaction command assigns a duration field to each transaction, which is the difference
between the latest and earliest timestamps of the events in the transaction1. The search then uses the timechart
command to create a time-series chart of the average duration of each transaction1. Therefore, option A is
correct because it describes the search accurately. Option B is incorrect because the search does not use the
stats command or the pause field. Option C is incorrect because the transaction command does not require the
startswith and endswith options, although they can be used to specify how to identify the beginning and end of
a transaction1. Option D is incorrect because the transaction command does not have to be the last command
in the search pipeline, although it is often used near the end of a search1.
NEW QUESTION # 49
When using the transaction command, how are evicted transactions identified?
- A. Max_txn field is set to O, or false.
- B. open_txn field is set to 1, or true.
- C. Closed_txn field is set to o, or false.
- D. Txn_field is set to 1, or true.
Answer: C
Explanation:
The transaction command is a Splunk command that finds transactions based on events that meet
various constraints1.
Transactions are made up of the raw text (the _raw field) of each member, the time and date fields of the
earliest member, as well as the union of all other fields of each member1.
The transaction command adds some fields to the raw events that are part of the transaction12. These
fields are:
duration: The difference, in seconds, between the timestamps for the first and last events in the
transaction12.
eventcount: The number of events in the transaction12.
closed_txn: A Boolean field that indicates whether the transaction is closed or evicted2. A
transaction is closed if it meets one of the following conditions: maxevents, maxpause, maxspan,
or startswith2. A transaction is evicted if it does not meet any of these conditions and exceeds the
memory limit specified by maxopentxn or maxopenevents23.
Therefore, evicted transactions can be distinguished from non-evicted transactions by checking the value
of the closed_txn field. The closed_txn field is set to 0, or false, for evicted transactions and 1, or true
for non-evicted, or closed, transactions23.
NEW QUESTION # 50
How can an existing accelerated data model be edited?
- A. It cannot be edited. A new data model would need to be created.
- B. An accelerated data model can be edited from the Pivot tool.
- C. The data model must be de-accelerated before edits can be made to its structure.
- D. An accelerated data model can be edited once its .tsidx file has expired.
Answer: C
Explanation:
An existing accelerated data model can be edited, but the data model must be de-accelerated before any structural edits can be made (Option C). This is because the acceleration process involves pre-computing and storing data, and changes to the data model's structure could invalidate or conflict with the pre-computed data.
Once the data model is de-accelerated and edits are completed, it can be re-accelerated to optimize performance.
NEW QUESTION # 51
Which of the following Statements about macros is true? (select all that apply)
- A. Arguments are defined at execution time.
- B. Argument values are used to resolve the search string at execution time.
- C. Arguments are defined when the macro is created.
- D. Argument values are used to resolve the search string when the macro is created.
Answer: A,D
NEW QUESTION # 52
Which delimiters can the Field Extractor (FX) detect? (select all that apply)
- A. Tabs
- B. Commas
- C. Pipes
- D. Spaces
Answer: B,C,D
Explanation:
Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/FXSelectMethodstep
NEW QUESTION # 53
What is the purpose of the fillnull command?
- A. Replace all values in a specific field with a default value.
- B. Rename a specific field in the search results.
- C. Replace empty values with a specified value.
- D. Create a new field based on the values in an existing field.
Answer: C
Explanation:
The fillnull command in Splunk is used to handle missing data within search results. It plays a crucial role in data normalization and preparation, especially before performing statistical analyses or visualizations.
A: Replace empty values with a specified value: This is the correct answer. The fillnull command is specifically designed to replace null values (empty values) with a specified default value. This is particularly useful in ensuring consistency within your data, especially when performing operations that require numerical values or when you want to distinguish between genuinely missing data and zeroes, for instance.
* Example Usage: ... | fillnull value=0 This command would replace all null values in the search results with 0.
NEW QUESTION # 54
When using | timechart by host, which field is represented in the x-axis?
- A. time
- B. date
- C. _time
- D. host
Answer: C
NEW QUESTION # 55
A calculated field may be based on which of the following?
- A. Extracted fields
- B. Fields generated within a search string
- C. Lookup tables
- D. Regular expressions
Answer: A
Explanation:
In Splunk, calculated fields allow you to create new fields using expressions that can transform or combine the values of existing fields. Although all options provided might seem viable, when selecting only one option that is most representative of a calculated field, we typically refer to:
D: Extracted fields: Calculated fields are often based on fields that have already been extracted from your data. Extracted fields are those that Splunk has identified and pulled out from the event data based on patterns, delimiters, or other methods such as regular expressions or automatic extractions. These fields can then be used in expressions to create calculated fields.
For example, you might have an extracted field for the time in seconds, and you want to create a calculated field for the time in minutes. You would use the extracted field in a calculation to create the new field.
It's important to note that although fields generated within a search string (A) and regular expressions (C) can also be used in the calculation of a new field, and lookup tables (B) can be used to enrich data, option D is typically what one refers to when discussing calculated fields, as it implies a direct transformation or calculation based on fields that have been extracted from the raw data.
NEW QUESTION # 56
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