SPLK-1002 Exam Dumps

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.

Explanation: The search below groups events by two or more fields (clientip and host), creates transactions with start and end constraints (maxspan=30s and maxpause=5s), and calculates the duration of each transaction.
index=main | transaction clientip host maxspan=30s maxpause=5s
The search does the following:
It filters the events by the index main, which is a default index in Splunk that contains all data that is not sent to other indexes.
It uses the transaction command to group events into transactions based on two fields: clientip and host. The transaction command creates new events from groups of events that share the same clientip and host values.
It specifies the start and end constraints for the transactions using the maxspan and maxpause arguments. The maxspan argument sets the maximum time span between the first and last events in a transaction. The maxpause argument sets the maximum time span between any two consecutive events in a transaction. In this case, the maxspan is 30 seconds and the maxpause is 5 seconds, meaning that any transaction that has a longer time span or pause will be split into multiple transactions.
It creates some additional fields for each transaction, such as duration, eventcount, startime, etc. The duration field shows the time span between the first and last events in a transaction.

A transaction is a group of events that share some common characteristics, such as fields, time, or both. A transaction can be created by using the transaction command or by defining an event type with transactiontype=true in props.conf. Events in a transaction have one or more fields in common that relate them to each other. For example, you can create a transaction based on JSESSIONID, which is a unique identifier for each user session in web logs. Events in a transaction do not have to have the same timestamp, sourcetype, or exact same set of fields. They only have to share one or more fields that define the transaction.

Explanation: Data models and pivot are both knowledge objects in Splunk that allow you to analyze and visualize your data in different ways. 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. Pivot is a user interface that allows you to create data visualizations that present different aspects of a data model. Pivot does not require users to input SPL searches on data models, but rather lets them select options from menus and forms. Data models are not created out of datasets called pivots, but rather pivots are created from datasets in data models.

Explanation: GET workflow actions are custom actions that open a URL link when you click on a field value in your search results. GET workflow actions can be configured with various options, such as label name, base URL, URI parameters, app context, etc. One of the options is to choose whether to open the URL link in the current window or in a new window. GET workflow actions do not have to be configured with POST arguments, as they use GET method to send requests to web servers. Configuration of GET workflow actions does not include choosing a sourcetype, as they do not generate any data in Splunk. Label names for GET workflow actions must include a field name surrounded by dollar signs, as this indicates the field value that will be used to replace the variable in the URL link.

Explanation:
https://docs.splunk.com/Documentation/Splunk/8.1.0/SearchReference/ConversionFunctio ns#tostring.28X.2CY.29
The tostring function in the eval command converts a numeric value to a string value. It can take an optional second argument that specifies the format of the string value. Some of the possible formats are:
hex: converts the numeric value to a hexadecimal string.
commas: adds commas to separate thousands in the numeric value.
duration: converts the numeric value to a human-readable duration string, such as “2h 3m 4s”.
Therefore, the formats A, B, and D can be used with the tostring function.

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 asindex=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.

Explanation: The transaction command is used to group events into transactions based on some common characteristics, such as fields, time, or both. The transaction command can also specify start and end constraints for the transactions, such as a field value that indicates the beginning or the end of a transaction. The stats command is used to calculate summary statistics on the events, such as count, sum, average, etc. The stats command cannot group events based on start and end constraints, but only on fields or time buckets. Therefore, the transaction command should be used instead of the stats command when you need to group events based on start and end constraints.

The Field Extractor (FX) is a tool that helps you extract fields from your data using delimiters or regular expressions. Delimiters are characters or strings that separate fields in your data. The FX can detect some common delimiters automatically, such as pipes (|), spaces ( ), commas (,), semicolons (;), etc.The FX cannot detect tabs (\t) as delimiters automatically, but you can specify them manually in the FX interface.