Pass Exam Questions Efficiently With SPLK-1002 Questions (2024) [Q22-Q46]

Pass Exam Questions Efficiently With SPLK-1002 Questions (2024) 

SPLK-1002 Questions – Truly Beneficial For Your Splunk Exam 

Splunk SPLK-1002 exam is designed for individuals who want to demonstrate their expertise in using Splunk Core. Splunk Core Certified Power User Exam certification exam is intended for professionals who manage large and complex Splunk environments, and have a deep understanding of SPL commands, field extraction, data models, and data normalization. The SPLK-1002 exam is a great way to showcase your Splunk skills and enhance your credibility in the industry.

To earn the Splunk Core Certified Power User certification, individuals must pass the SPLK-1002 exam. SPLK-1002 exam consists of 65 multiple-choice questions and has a time limit of 90 minutes. SPLK-1002 exam covers various topics, including searching and reporting, creating and managing knowledge objects, and using field aliases and calculated fields.

QUESTION 22
Which of the following about reports is/are true?

 Reports are knowledge objects.

 Reports can be scheduled.

 Reports can run a script.

 All of the above.

A report is a way to save a search and its results in a format that you can reuse and share with others2. A report is also a type of knowledge object, which is an entity that you create to add knowledge to your data and make it easier to search and analyze2. Therefore, option A is correct. A report can be scheduled, which means that you can configure it to run at regular intervals and send the results to yourself or others via email or other methods2. Therefore, option B is correct. A report can run a script, which means that you can specify a script file to execute when the report runs and use it to perform custom actions or integrations2. Therefore, option C is correct. Therefore, option D is correct because all of the above statements are true for reports.

QUESTION 23
Which of the following are required to create a POST workflow action?

 Label, URI, search string.

 XMI attributes, URI, name.

 Label, URI, post arguments.

 URI, search string, time range picker.

Explanation
POST workflow actions are custom actions that send a POST request to a web server when you click on a field value in your search results. POST workflow actions can be configured with various options, such as label name, base URL, URI parameters, post arguments, app context, etc. One of the options that are required to create a POST workflow action is post arguments. Post arguments are key-value pairs that are sent in the body of the POST request to provide additional information to the web server. Post arguments can include field values from your data by using dollar signs around the field names.

QUESTION 24
What is the correct syntax to find events associated with a tag?

 tag:<field>=<value>

 tags=<value>

 tags:<field>=<value>

 tag=<value>

Explanation
The correct syntax to find events associated with a tag is A. tag:<field>=<value>.
A tag is a way to add descriptive keywords to events based on field values. Tags can be used to filter and group events by common characteristics, such as source type, host, severity, or category1.
To search for events that have a specific tag, you need to use the tag field with the name of the field and the value of the tag as the arguments. The syntax for this is:
tag:<field>=<value>
For example, if you want to search for events that have the tag “error” for the status field, you can use the following syntax:
tag:status=error
This will return only the events that have the status field value tagged as “error”.
The other options are not correct because they use different syntax or fields that are not related to tags. These options are:
B: tags=<value>: This option uses the tags field, which is a multivalue field that contains all the tags associated with an event. However, this field is not searchable by default and requires additional configuration to enable it1.
C: tags:<field>=<value>: This option uses the tags field with a colon instead of an equal sign, which is not valid syntax for searching with fields.
D: tag=<value>: This option uses the tag field without specifying the name of the field, which is not valid syntax for searching with tags.
References:
About tags
Search with tags

QUESTION 25
A calculated field is a shortcut for performing repetitive, long, or complex transformations using which of the
following commands?

 transaction

 lookup

 stats

 eval

The correct answer is D. eval.
A calculated field is a field that is added to events at search time by using an eval expression. A calculated
field can use the values of two or more fields that are already present in the events to perform calculations. A
calculated field can be defined with Splunk Web or in the props.conf file.They can be used in searches,
reports, dashboards, and data models like any other extracted field1.
A calculated field is a shortcut for performing repetitive, long, or complex transformations using the eval
command. The eval command is used to create or modify fields by using expressions.The eval command can
perform mathematical, string, date and time, comparison, logical, and other operations on fields or values2.
For example, if you want to create a new field named total that is the sum of two fields named price and tax,
you can use the eval command as follows:
| eval total=price+tax
However, if you want to use this new field in multiple searches, reports, or dashboards, you can create a
calculated field instead of writing the eval command every time. To create a calculated field with Splunk Web,
you need to go to Settings > Fields > Calculated Fields and enter the name of the new field (total), the name of
the sourcetype (sales), and the eval expression (price+tax). This will create a calculated field named total that
will be added to all events with the sourcetype sales at search time.You can then use the total field like any
other extracted field without writing the eval expression1.
The other options are not correct because they are not related to calculated fields. These options are:
A: transaction: This command is used to group events that share some common values into a single
record, called a transaction.A transaction can span multiple events and multiple sources, and can be
useful for correlating events that are related but not contiguous3.
B: lookup: This command is used to enrich events with additional fields from an external source, such as
a CSV file or a database. A lookup can add fields to events based on the values of existing fields, such
as host, source, sourcetype, or any other extracted field.
C: stats: This command is used to calculate summary statistics on the fields in the search results, such as
count, sum, average, etc. It can be used to group and aggregate data by one or more fields.
References:
About calculated fields
eval command overview
transaction command overview
[lookup command overview]
[stats command overview]

QUESTION 26
What is the correct syntax to search for a tag associated with a value on a specific fiedsd?

 Tag-<field?

 Tag<filed(tagname.)

 Tag=<filed>::<tagname>

 Tag::<filed>=<tagname>

QUESTION 27
Which of the following statements describes POST workflow actions?

 Configuration of a POST workflow action includes choosing a sourcetype.

 POST workflow actions can be configured to send email to the URI location.

 By default, POST workflow actions are shown in both the event and field menus.

 POST workflow actions can be configured to send POST arguments to the URI location.

Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/SetupaPOSTworkflowaction

QUESTION 28
Which search would limit an “alert” tag to the “host” field?

 tag=alert

 host::tag::alert

 tag==alert

 tag::host=alert

The search below would limit an “alert” tag to the “host” field.
tag::host=alert
The search does the following:
It uses tag syntax to filter events by tags. Tags are custom labels that can be applied to fields or field values to provide additional context or meaning for your data.
It specifies tag::host=alert as the tag filter. This means that it will only return events that have an “alert” tag applied to their host field or host field value.
It uses an equal sign (=) to indicate an exact match between the tag and the field or field value.

QUESTION 29
After manually editing; a regular expression (regex), which of the following statements is true?

 Changes made manually can be reverted in the Field Extractor (FX) UI.

 It is no longer possible to edit the field extraction in the Field Extractor (FX) UI.

 It is not possible to manually edit a regular expression (regex) that was created using the Field Extractor (FX) UI.

 The Field Extractor (FX) UI keeps its own version of the field extraction in addition to the one that was manually edited.

After manually editing a regular expression (regex) that was created using the Field Extractor (FX) UI, it is no longer possible to edit the field extraction in the FX UI. The FX UI is a tool that helps you extract fields from your data using delimiters or regular expressions. The FX UI can generate a regex for you based on your selection of sample values or you can enter your own regex in the FX UI. However, if you edit the regex manually in the props.conf file, the FX UI will not be able to recognize the changes and will not let you edit the field extraction in the FX UI anymore. You will have to use the props.conf file to make any further changes to the field extraction. Changes made manually cannot be reverted in the FX UI, as the FX UI does not keep track of the changes made in the props.conf file. It is possible to manually edit a regex that was created using the FX UI, as long as you do it in the props.conf file.
Therefore, only statement B is true about manually editing a regex.

QUESTION 30
Which of the following statements describe data model acceleration? (select all that apply)

 Root events cannot be accelerated.

 Accelerated data models cannot be edited.

 Private data models cannot be accelerated.

 You must have administrative permissions or the accelerate_dacamodel capability to accelerate a data model.

QUESTION 31
These kinds of charts represent a series in a single bar with multiple sections

 Multi-Series

 Split-Series

 Omit nulls

 Stacked

Stacked charts represent a series in a single bar with multiple sections. A chart is a graphical representation of
data that shows trends, patterns, or comparisons. A chart can have different types, such as column, bar, line,
area, pie, etc. A chart can also have different modes, such as split-series, multi-series, stacked, etc. A stacked
chart is a type of chart that shows multiple series in a single bar or area with different sections for each series

QUESTION 32
How is a Search Workflow Action configured to run at the same time range as the original search?

 Set the earliest time to match the original search.

 Select the same time range from the time-range picker.

 Select the “Use the same time range as the search that created the field listing” checkbox.

 Select the “Overwrite time range with the original search” checkbox.

To configure a Search Workflow Action to run at the same time range as the original search, you need to
select the “Use the same time range as the search that created the field listing” checkbox. This will ensure that
the workflow action search uses the same earliest and latest time parameters as the original search.

QUESTION 33
Which field extraction method should be selected for comma-separated data?

 Regular expression

 Delimiters

 eval expression

 table extraction

Explanation
The correct answer is B. Delimiters. This is because the delimiters method is designed for structured event data, such as data from files with headers, where all of the fields in the events are separated by a common delimiter, such as a comma or space. You can select a sample event, identify the delimiter, and then rename the fields that the field extractor finds. You can learn more about the delimiters method from the Splunk documentation1. The other options are incorrect because they are not suitable for comma-separated data. The regular expression method works best with unstructured event data, where you select and highlight one or more fields to extract from a sample event, and the field extractor generates a regular expression that matches similar events and extracts the fields from them. The eval expression is a command that lets you calculate new fields or modify existing fields using arithmetic, string, and logical operations. The table extraction is a feature that lets you extract tabular data from PDF files or web pages. You can learn more about these methods from the Splunk documentation23 .

QUESTION 34
Which of the following statements describes Search workflow actions?

 By default. Search workflow actions will run as a real-time search.

 Search workflow actions can be configured as scheduled searches,

 The user can define the time range of the search when created the workflow action.

 Search workflow actions cannot be configured with a search string that includes the transaction command

Search workflow actions are custom actions that run a search when you click on a field value in your search
results. Search workflow actions can be configured with various options, such as label name, search string,
time range, app context, etc. One of the options is to define the time range of the search when creating the
workflow action. You can choose from predefined time ranges, such as Last 24 hours, Last 7 days, etc., or
specify a custom time range using relative or absolute time modifiers. Search workflow actions do not run as
real-time searches by default, but rather use the same time range as the original search unless specified
otherwise. Search workflow actions cannot be configured as scheduled searches, as they are only triggered by
user interaction. Search workflow actions can be configured with any valid search string that includes any
search command, such as transaction.

QUESTION 35
Which field will be used to populate the field if the productName and product:d fields have values for a given event?

 | eval productINFO=coalesco(productName,productid)

 Both field values will be used and the product INFO field will become a multivalue field for the given event.

 The value for the productName field because it appears first.

 Neither field value will be used and the field will be assigned a NULL value for the given event.

 The value for the field because it appears second.

The correct answer is B. The value for the productName field because it appears first.
The coalesce function is an eval function that takes an arbitrary number of arguments and returns the first value that is not null. A null value means that the field has no value at all, while an empty value means that the field has a value, but it is “” or zero-length1.
The coalesce function can be used to combine fields that have different names but represent the same data, such as IP address or user name. The coalesce function can also be used to rename fields for clarity or convenience2.
The syntax for the coalesce function is:
coalesce(<field1>,<field2>,…)
The coalesce function will return the value of the first field that is not null in the argument list. If all fields are null, the coalesce function will return null.
For example, if you have a set of events where the IP address is extracted to either clientip or ipaddress, you can use the coalesce function to define a new field called ip, that takes the value of either clientip or ipaddress, depending on which is not null:
| eval ip=coalesce(clientip,ipaddress)
In your example, you have a set of events where the product name is extracted to either productName or productid, and you use the coalesce function to define a new field called productINFO, that takes the value of either productName or productid, depending on which is not null:
| eval productINFO=coalesce(productName,productid)
If both productName and productid fields have values for a given event, the coalesce function will return the value of the productName field because it appears first in the argument list. The productid field will be ignored by the coalesce function.
Therefore, the value for the productName field will be used to populate the productINFO field if both fields have values for a given event.
Reference:
Search Command> Coalesce
USAGE OF SPLUNK EVAL FUNCTION : COALESCE

QUESTION 36
After manually editing; a regular expression (regex), which of the following statements is true?

 Changes made manually can be reverted in the Field Extractor (FX) UI.

 It is no longer possible to edit the field extraction in the Field Extractor (FX) UI.

 It is not possible to manually edit a regular expression (regex) that was created using the Field Extractor
(FX) UI.

 The Field Extractor (FX) UI keeps its own version of the field extraction in addition to the one that was manually edited.

After manually editing a regular expression (regex) that was created using the Field Extractor (FX) UI, it is no
longer possible to edit the field extraction in the FX UI. The FX UI is a tool that helps you extract fields from
your data using delimiters or regular expressions. The FX UI can generate a regex for you based on your
selection of sample values or you can enter your own regex in the FX UI. However, if you edit the regex
manually in the props.conf file, the FX UI will not be able to recognize the changes and will not let you edit
the field extraction in the FX UI anymore. You will have to use the props.conf file to make any further
changes to the field extraction. Changes made manually cannot be reverted in the FX UI, as the FX UI does
not keep track of the changes made in the props.conf file. It is possible to manually edit a regex that was
created using the FX UI, as long as you do it in the props.conf file.
Therefore, only statement B is true about manually editing a regex.

QUESTION 37
Which of the following searches show a valid use of macro? (Select all that apply)

 index=main source=mySource oldField=* |’makeMyField(oldField)’| table _time newField

 index=main source=mySource oldField=* | stats if(‘makeMyField(oldField)’) | table _time newField

 index=main source=mySource oldField=* | eval newField=’makeMyField(oldField)’| table _time
newField

 index=main source=mySource oldField=* | “‘newField(‘makeMyField(oldField)’)'” | table _time newField

Reference:https://answers.splunk.com/answers/574643/field-showing-an-additional-and-not-visible-value-1.html
To use a macro in a search, you must enclose the macro name and any arguments in single quotation marks1.
For example, ‘my_macro(arg1,arg2)’ is a valid way to use a macro with two arguments. You can use macros
anywhere in your search string where you would normally use a search command or expression1. Therefore,
options A and C are valid searches that use macros, while options B and D are invalid because they do not
enclose the macros in single quotation marks.

QUESTION 38
Which of the following is the correct way to use the data model command to search field in the data model
within the web dataset?

 | datamodel web search | filed web *

 | Search datamodel web web | filed web*

 | datamodel web web field | search web*

 Datamodel=web | search web | filed web*

The data model command allows you to run searches on data models that have been accelerated1. The syntax
for using the data model command is | datamodel <model_name> <dataset_name> [search <search_string>]1.
Therefore, option A is the correct way to use the data model command to search fields in the data model
within the web dataset. Options B and C are incorrect because they do not follow the syntax for the data model
command. Option D is incorrect because it does not use the data model command at all.

QUESTION 39
Which is not a comparison operator in Splunk

 <=

 =

 !=

 >

 ?=

Explanation
A comparison operator is a symbol that compares two values and returns a Boolean result (true or false)2. Splunk supports various comparison operators such as <, >, =, !=, <=, >=, IN and LIKE2. However,
?= is not a valid comparison operator in Splunk and will cause a syntax error if used in a search string2.
Therefore, option E is correct, while options A, B, C and D are incorrect because they are valid comparison operators in Splunk

QUESTION 40
When should transaction be used?

 Only in a large distributed Splunk environment.

 When calculating results from one or more fields.

 When event grouping is based on start/end values.

 When grouping events results in over 1000 events in each group.

Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Search/Abouttransactions

QUESTION 41
When using the transaction command, how are evicted transactions identified?

 Closed_txn field is set to o, or false.

 Max_txn field is set to O, or false.

 Txn_field is set to 1, or true.

 open_txn field is set to 1, or true.

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.

QUESTION 42
Which of the following workflow actions can be executed from search results? (select all that apply)

 GET

 POST

 LOOKUP

 Search

As mentioned before, there are two types of workflow actions: GET and POST1. Both types of workflow
actions can be executed from search results by clicking on an event field value that has a workflow action
configured for it1. Another type of workflow action is Search, which runs another search based on the field
value1. Therefore, options A, B and D are correct, while option C is incorrect because LOOKUP is not a type
of workflow action.

QUESTION 43
Which of the following statements describes the use of the Field Extractor (FX)?

 The Field Extractor automatically extracts all fields at search time.

 The Field Extractor uses PERL to extract fields from the raw events.

 Fields extracted using the Field Extractor persist as knowledge objects.

 Fields extracted using the Field Extractor do not persist and must be defined for each search.

QUESTION 44
Using the export function, you can export a maximum of 2000 results.

 True

 False

QUESTION 45
Which Knowledge Object does the Splunk Common Information Model (CIM) use to normalize data, in addition to field aliases, event types, and tags?

 Macros

 Lookups

 Workflow actions

 Field extractions

Explanation/Reference: https://docs.splunk.com/Documentation/CIM/4.15.0/User/UsetheCIMtonormalizedataatsearchtime

QUESTION 46
Why would the following search produce multiple transactions instead of one?

 The maxspan option is not included.

 The transaction command has a limit of 1000 events per transaction.

 The transaction and commands cannot be used together.

 The stats list () function is used.

In Splunk, the transaction command is used to group events that share common characteristics into a single transaction1. By default, the transaction command groups all matching events into a single transaction1.
However, you can use the maxspan option to limit the time span of the transactions1. If the time span between the first and last event in a transaction exceeds the maxspan value, the transaction command will start a new transaction1.
Therefore, if the maxspan option is not included in the search, the transaction command might produce multiple transactions instead of one if the time span between the first and last event in a transaction exceeds the default maxspan value1.
Here is an example of how you can use the maxspan option in a search:
index=main sourcetype=access_combined | transaction someuniqefield maxspan=1h In this search, the transaction command groups events that share the same someuniqefield value into a single transaction, but only if the time span between the first and last event in the transaction does not exceed 1 hour1. If the time span exceeds 1 hour, the transaction command will start a new transaction1.

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How to Prepare For Splunk Core Certified Power User splk-1002 Exam

Preparation Guide for Splunk Core Certified Power User splk-1002 Exam

Introduction

Splunk has created a track for IT professionals to certify as a Certified Power User on the Splunk platform. This certification program provides Splunk professionals with a way to demonstrate their skills. The assessment is based on a rigorous exam using the industry-standard methodology to determine whether a candidate meets Splunk’s proficiency standards.

According to Splunk, a Splunk Core Certified Power User splk-1002 Exam enables organizations to leverage SPL searching and reporting commands and can create knowledge objects. With a thorough understanding of Splunk core Power user, an individual can explain the SplunkSPL searching and reporting commands and can create knowledge objects Processes and standards to drive business objectives.

Certification is evidence of your skills, expertise in those areas in which you like to work. If the candidate wants to work on Splunk Core Certified Power User splk-1002 and prove his knowledge, Certification offered by Splunk. This Splunk Core Certified Power User splk-1002 Certification helps a candidate to validates his skills in Splunk Core Certified Power User splk-1002 Technology

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