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

Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Definesearchmacros The macro definition below shows a macro that tracks user sessions based on two arguments: action and JSESSIONID.
sessiontracker(2)
The macro definition does the following:
It specifies the name of the macro as sessiontracker. This is the name that will be used to execute the macro in a search string.
It specifies the number of arguments for the macro as 2. This indicates that the macro takes two arguments when it is executed.
It specifies the code for the macro as index=main sourcetype=access_combined_wcookie action=$action$ JSESSIONID=$JSESSIONID$ | stats count by JSESSIONID. This is the search string that will be run when the macro is executed. The search string can contain any part of a search, such as search terms, commands, arguments, etc. The search string can also include variables for the arguments using dollar signs around them.
In this case, action and JSESSIONID are variables for the arguments that will be replaced by their values when the macro is executed.
Therefore, to correctly configure the macro, you should enter sessiontracker as the name and action, JSESSIONID as the arguments. Alternatively, you can use sessiontracker(2) as the name and leave the arguments blank.

The timechart command buckets data in time intervals depending on the selected time range2. The timechart command is similar to the chart command but it automatically groups events into time buckets based on the _time field2. The size of the time buckets depends on the time range that you select for your search. For example, if you select Last 24 hours as your time range, Splunk will use 30-minute buckets for your timechart. If you select Last 7 days as your time range, Splunk will use 4-hour buckets for your timechart2. Therefore, option B is correct, while options A and C are incorrect because they are not factors that affect the size of the time buckets.

A chart is a graphical representation of your search results that shows the relationship between two or more fields2. You can display a chart in stack mode by changing the Stack Mode option in the Format menu2. Stack mode allows you to stack multiple series on top of each other in a chart to show the cumulative values of each series2. Therefore, option C is correct, while options A, B and D are incorrect because they are not ways to display a chart in stack mode.

In Splunk, when using thechartcommand, theuseotherparameter can be set tofalse(f) to remove the ‘OTHER’ category, which is a bucket that Splunk uses to aggregate low-cardinality groups into a single group to simplify visualization. Here’s how the options break down:
A:| chart count over CurrentStanding by Action useother=fThis command correctly sets theuseother parameter tofalse, which would prevent the ‘OTHER’ category from being displayed in the resulting visualization.
B:| chart count over CurrentStanding by Action usenull=f useother=tThis command hasuseotherset to true(t), which means the ‘OTHER’ category would still be included, so this is not a correct option.
C:| chart count over CurrentStanding by Action limit=10 useother=fSimilar to option A, this command also setsuseothertofalse, additionally imposing a limit to the top 10 results, which is a way to control the granularity of the chart but also to remove the ‘OTHER’ category.
D:| chart count over CurrentStanding by Action limit-10This command has a syntax error (limit-10should belimit=10) and does not include theuseother=fclause. Therefore, it would not remove the ‘OTHER’ category, making it incorrect.
The correct answers to rewrite the syntax to remove the ‘OTHER’ category are options A and C, which explicitly setuseother=f.

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.

If a search returns statistics, it can be viewed as a chart2. Statistics are tabular data that show the relationship between two or more fields2. You can create statistics by using commands such as stats, chart or timechart2. You can view statistics as a chart by selecting the Visualization tab in the Search app and choosing a chart type such as column, line or pie2. Therefore, option B is correct, while options A, C and D are incorrect because they are not types of data that can be viewed as a chart.

Explanation
A workflow action is a link that appears when you click an event field value in your search results1. A workflow action can open a web page or run another search based on the field value1. There are two types of workflow actions: GET and POST1. A GET workflow action appends the field value to the end of a URI and opens it in a web browser1. A POST workflow action sends the field value as part of an HTTP request to a web server1. You can configure a workflow action to open a web page in either the same window or a new window1. Therefore, option D is correct, while options A, B and C are incorrect.

Reference:
https://answers.splunk.com/answers/574643/field-showing-an-additional-and-not-visible-value-1.html

When using the Field Extractor (FX) in Splunk to perform field extraction, any consistent character can be used as a delimiter. The Field Extractor allows users to define how fields are separated in the raw event data, and as long as the delimiter is consistent, the FX tool can parse and extract the fields correctly.
References:
* Splunk Docs: Field Extractor
* Splunk Answers: Field extraction delimiters

Explanation
Explanation/Reference: https://docs.splunk.com/Splexicon:Datamodeldataset

A workflow action is a link that appears when you click an event field value in your search results1. A
workflow action can open a web page or run another search based on the field value1. There are two types of
workflow actions: GET and POST1. A GET workflow action appends the field value to the end of a URI and
opens it in a web browser1. A POST workflow action sends the field value as part of an HTTP request to a
web server1. You can configure a workflow action to open a web page in either the same window or a new
window1. Therefore, option D is correct, while options A, B and C are incorrect.