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NEW QUESTION # 61
Which of the following searches will return events containing a tag named Privileged?
- A. tag=Priv
- B. tag=privileged
- C. tag=priv*
- D. tag=Priv*
Answer: D
NEW QUESTION # 62
During the validation step of the Field Extractor workflow:
Select your answer.
- A. You cannot modify the field extraction
- B. You can validate where the data originated from
- C. You can remove values that aren't a match for the field you want to define
Answer: C
Explanation:
During the validation step of the Field Extractor workflow, you can remove values that aren't a match for the
field you want to define2. The validation step allows you to review and edit the values that have been
extracted by the FX and make sure they are correct and consistent2. You can remove values that aren't a
match by clicking on them and selecting Remove Value from the menu2. This will exclude them from your
field extraction and update the regular expression accordingly2. Therefore, option A is correct, while options
B and C are incorrect because they are not actions that you can perform during the validation step of the Field
Extractor workflow.
NEW QUESTION # 63
Which of the following statements about tags is true?
- A. Tags can make your data more understandable.
- B. Tags are searched by using the syntax tag :: <fieldname>.
- C. Tags are case insensitive.
- D. Tags are created at index time.
Answer: A
Explanation:
Tags are a knowledge object that allow you to assign an alias to one or more field values . Tags are applied to events at search time and can be used as search terms or filters .
Tags can help you make your data more understandable by replacing cryptic or complex field values with meaningful names . For example, you can tag the value 200 in the status field as success, or tag the value 404 as not_found .
NEW QUESTION # 64
Which of the following statements about tags is true? (select all that apply.)
- A. Tags categorize events based on a search.
- B. Tags are case-insensitive.
- C. Tags are based on field/vale pairs.
- D. Tags are designed to make data more understandable.
Answer: C,D
Explanation:
The following statements about tags are true: tags are based on field/value pairs and tags categorize events
based on a search. Tags are custom labels that can be applied to fields or field values to provide additional
context or meaning for your data. Tags can be used to filter or analyze your data based on common concepts or
themes. Tags can be created by using various methods, such as search commands, configuration files, user
interfaces, etc. Some of the characteristics of tags are:
Tags are based on field/value pairs: This means that tags are associated with a specific field name and a
specific field value. For example, you can create a tag called "alert" for the field name "status" and the
field value "critical". This means that only events that have status=critical will have the "alert" tag
applied to them.
Tags categorize events based on a search: This means that tags are defined by a search string that
matches the events that you want to tag. For example, you can create a tag called "web" for the search
string sourcetype=access_combined. This means that only events that match the search string
sourcetype=access_combined will have the "web" tag applied to them.
The following statements about tags are false: tags are case-insensitive and tags are designed to make data
more understandable. Tags are case-sensitive and tags are designed to make data more searchable. Tags are
case-sensitive: This means that tags must match the exact case of the field name and field value that they are
associated with. For example, if you create a tag called "alert" for the field name "status" and the field value
"critical", it will not apply to events that have status=CRITICAL or Status=critical. Tags are designed to make
data more searchable: This means that tags can help you find relevant events or patterns in your data by using
common concepts or themes. For example, if you create a tag called "web" for the search string
sourcetype=access_combined, you can use tag=web to find all events related to web activity.
NEW QUESTION # 65
Which knowledge Object does the Splunk Common Information Model (CIM) use to normalize data. in addition to field aliases, event types, and tags?
- A. Macros
- B. Lookups
- C. Field extractions
- D. Workflow actions
Answer: B
Explanation:
Explanation
Normalize your data for each of these fields using a combination of field aliases, field extractions, and lookups.
https://docs.splunk.com/Documentation/CIM/4.15.0/User/UsetheCIMtonormalizedataatsearchtime
NEW QUESTION # 66
Which of the following statements describes field aliases?
- A. Field alias names are not case sensitive when used as part of a search.
- B. Field alias names replace the original field name.
- C. Field aliases can be used in lookup file definitions.
- D. Field aliases only normalize data across sources and sourcetypes.
Answer: C
NEW QUESTION # 67
Search terms are not case sensitive.
- A. False
- B. True
Answer: B
NEW QUESTION # 68
What does the fillnull command replace null values with, if the value argument is not specified?
- A. 0
- B. NULL
- C. NaN
- D. N/A
Answer: A
Explanation:
The fillnull command replaces null values with 0 by default, if the value argument is not specified. You can
use the value argument to specify a different value to replace null values with, such as N/A or NULL.
NEW QUESTION # 69
A macro has another macro nested within it, and this inner macro requires an argument. How can the user pass
this argument into the SPL?
- A. An argument can be passed through the outer macro.
- B. An argument can be passed to the inner macro by nesting parentheses.
- C. There is no way to pass an argument to the inner macro.
- D. An argument can be passed to the outer macro by nesting parentheses.
Answer: B
Explanation:
The correct answer is D. An argument can be passed to the inner macro by nesting parentheses.
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 macro. A nested macro can
also take arguments, which can be passed from the outer macro or directly from the search string.
To pass an argument to the inner macro, you need to use parentheses to enclose the argument value and
separate it from the outer macro argument. For example, if you have a search macro namedouter_macro
(1)that contains another search macro namedinner_macro (2), and both macros take one argument each, you
can pass an argument to the inner macro by using the following syntax:
outer_macro (argument1, inner_macro (argument2))
This will replace the argument1 and argument2 with the values you provide in the search string. For example,
if you want to pass "foo" as the argument1 and "bar" as the argument2, you can write:
outer_macro ("foo", inner_macro ("bar"))
This will expand the macros with the corresponding arguments and run the SPL code contained in them.
References:
Search macro examples
Use search macros in searches
NEW QUESTION # 70
What does the following search do?
- A. Creates a table with the count of all types of corndogs eaten split by user.
- B. Creates a table of the total count of users and split by corndogs.
- C. Creates a table of the total count of mysterymeat corndogs split by user.
- D. Creates a table that groups the total number of users by vegetarian corndogs.
Answer: C
NEW QUESTION # 71
The Splunk search language supports the + wildcard.
- A. False
- B. True
Answer: A
NEW QUESTION # 72
What is needed to define a calculated field?
- A. Data model
- B. Eval expression
- C. Event type
- D. Regular expression
Answer: B
Explanation:
A calculated field in Splunk is created using an eval expression, which allows users to perform calculations or transformations on field values during search time.
References:
Splunk Docs - Calculated fields
NEW QUESTION # 73
Which of the following searches show a valid use of macro? (Select all that apply)
- A. Option C
- B. Option B
- C. Option D
- D. Option A
Answer: A,D
NEW QUESTION # 74
which of the following commands are used when creating visualizations(select all that apply.)
- A. iplocation
- B. Geom
- C. Choropleth
- D. Geostats
Answer: A,B,D
Explanation:
The following commands are used when creating visualizations: geom, geostats, and iplocation.
Visualizations are graphical representations of data that show trends, patterns, or comparisons. Visualizations can have different types, such as charts, tables, maps, etc. Visualizations can be created by using various commands that transform the data into a suitable format for the visualization type. Some of the commands that are used when creating visualizations are:
* geom: This command is used to create choropleth maps that show geographic regions with different colors based on some metric. The geom command takes a KMZ file as an argument that defines the geographic regions and their boundaries. The geom command also takes a field name as an argument that specifies the metric to use for coloring the regions.
* geostats: This command is used to create cluster maps that show groups of events with different sizes and colors based on some metric. The geostats command takes a latitude and longitude field as arguments that specify the location of the events. The geostats command also takes a statistical function as an argument that specifies the metric to use for sizing and coloring the clusters.
* iplocation: This command is used to create location-based visualizations that show events with different
* attributes based on their IP addresses. The iplocation command takes an IP address field as an argument and adds some additional fields to the events, such as Country, City, Latitude, Longitude, etc. The iplocation command can be used with other commands such as geom or geostats to create maps based on IP addresses.
NEW QUESTION # 75
Which of the following describes the Splunk Common Information Model (CIM) add-on?
- A. The CIM add-on contains data models to help you normalize data.
- B. The CIM add-on is automatically installed in a Splunk environment.
- C. The CIM add-on contains dashboards that show how to map data.
- D. The CIM add-on uses machine learning to normalize data.
Answer: A
NEW QUESTION # 76
The timechart command is an example of which of the following command types?
- A. Generating
- B. Transforming
- C. Statistical
- D. Orchestrating
Answer: B
Explanation:
The correct answer is B. Transforming.
The explanation is as follows:
The timechart command is a Splunk command that creates a time series chart with corresponding table of statistics12.
A timechart is a statistical aggregation applied to a field to produce a chart, with time used as the X-axis1. You can specify a split-by field, where each distinct value of the split-by field becomes a series in the chart1.
Transforming commands are commands that change the format of the search results into a data structure that can be easily visualized3. Transforming commands often use stats functions to aggregate and summarize data3.
Therefore, the timechart command is an example of a transforming command, as it transforms the search results into a chart and a table using stats functions123.
NEW QUESTION # 77
The gauge command:
- A. creates a radial gauge visualization
- B. creates a single-value visualization
- C. allows you to set colored ranges for a single-value visualization
Answer: C
NEW QUESTION # 78
A calculated field is a shortcut for performing repetitive, long, or complex transformations using which of the following commands?
- A. lookup
- B. eval
- C. stats
- D. transaction
Answer: B
Explanation:
Explanation
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]
NEW QUESTION # 79
Which group of users would most likely use pivots?
- A. Architects
- B. Knowledge Managers
- C. Administrators
- D. Users
Answer: B
NEW QUESTION # 80
This is what Splunk uses to categorize the data that is being indexed.
- A. Source
- B. Host
- C. Sourcetype
- D. Index
Answer: C
NEW QUESTION # 81
When using the Field Extractor (FX), which of the following delimiters will work? (select all that apply)
- A. Colons
- B. Spaces
- C. Tabs
- D. Pipes
Answer: B,C,D
NEW QUESTION # 82
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