The transaction command is a Splunk command that finds transactions based on events that meet

various constraints .

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 member .

The transaction command groups events together by matching one or more fields that have the

same value across the events . For example, | transaction clientip will group events that have the

same value in the clientip field.

The relationship between data models and pivots is that data models provide the datasets for pivots.

Data models are collections of datasets that represent your data in a structured and hierarchical way.

Data models define how your data is organized into objects and fields. Pivots are user interfaces that

allow you to create data visualizations that present different aspects of a data model. Pivots let you

select options from menus and forms to create charts, tables, maps, etc., without writing any SPL

code. Pivots use datasets from data models as their source of data. Pivots and data models are not

the same thing, as pivots are tools for visualizing data models. Pivots do not provide datasets for data

models, but rather use them as inputs.

Therefore, only statement A is true about the relationship between data models and pivots.

The fields sidebar is a panel that shows the fields that are present in your search results2. The fields

sidebar has two sections: selected fields and interesting fields2. Selected fields are fields that you

choose to display in your search results by clicking on them in the fields sidebar or by using the fields

command2. Interesting fields are fields that appear in at least 20 percent of events or have high

variability among values2. For each field in the fields sidebar, you can select one of the following

options: events with this field, rare values, top values by time or top values2. If you select rare

values, Splunk will automatically pipe your search results to the rare command, which shows the

least common values of a field2. Therefore, option B is correct, while options A, C and D are incorrect

because they do not pipe your search results to the rare command.

Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Pivot/IntroductiontoPivot

A pivot is a tool that allows you to create reports and dashboards using data models without writing

any SPL commands2. You can use pivots to explore, filter, split and visualize your data using a

graphical interface2. Pivots are designed for users who want to analyze and report on their data

without having to learn the SPL syntax or the underlying structure of the data2. Therefore, option A is

correct, while options B, C and D are incorrect because they are not the typical group of users who

would use pivots.

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The transaction command is used to group events that share a common value for one or more fields

into transactions2. The transaction command assigns a transaction ID to each group of events and

creates new fields such as duration, eventcount and eventlist for each transaction2. To identify all of

the contributing events within a transaction that contains at least one REJECT event, you can use the

following syntax: index=main | transaction sessionid | search REJECT2. This search will first group the

events by sessionid, then filter out the transactions that do not contain REJECT in any of their

events2. Therefore, option B is correct, while options A, C and D are incorrect because they do not

follow the correct syntax for using the transaction command or the search command.

Reference: https://www.edureka.co/blog/splunk-events-event-types-and-tags/

As mentioned before, an event type is a way to categorize events based on a search string that

matches the events2. Event types can be tagged, which means that you can apply descriptive labels

to event types and use them in your searches2. Therefore, option A is correct. Event types categorize

events based on a search string, which means that you can define an event type by specifying a

search string that matches the events you want to include in the event type2. Therefore, option C is

correct. Event types can be a useful method for capturing and sharing knowledge, which means that

you can use event types to organize your data into meaningful categories and share them with other

users in your organization2. Therefore, option D is correct. Event types do not have to include a time

range, which means that you can create an event type without specifying a time range for the

events2. Therefore, option B is incorrect.

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A delimiter field extraction is a method of extracting fields from data that uses a character or a string

to separate fields in each event. A delimiter field extraction can be performed by using the Field

Extractor (FX) tool or by editing the props.conf file. A delimiter field extraction can be applied to any

file format that uses a delimiter to separate fields, such as CSV, TSV, PSV, etc. A CSV file is a comma-

separated values file that uses commas as delimiters. Therefore, a CSV file can be extracted using a

delimiter field extraction.