Splunk SPLK-1002 Practice Test - Questions Answers, Page 27

The fillnull command in Splunk is used to handle missing data within search results. It plays a crucial role in data normalization and preparation, especially before performing statistical analyses or visualizations.

A . Replace empty values with a specified value: This is the correct answer. The fillnull command is specifically designed to replace null values (empty values) with a specified default value. This is particularly useful in ensuring consistency within your data, especially when performing operations that require numerical values or when you want to distinguish between genuinely missing data and zeroes, for instance.

Example Usage: ... | fillnull value=0 This command would replace all null values in the search results with 0.

When using the Field Extractor (FX) in Splunk for regex field extraction, it's important to select the context in which you want to perform the extraction. The context is essentially the subset of data you're focusing on for your field extraction task.

D . Sourcetype or source: This is the correct option. In the initial steps of using the Field Extractor tool, you're prompted to choose a data type for your field extraction. The options available are typically based on the nature of your data and how it's organized in Splunk. 'Sourcetype' refers to the kind of data you're dealing with, a categorization that helps Splunk apply specific processing rules. 'Source' refers to the origin of the data, like a specific log file or data input. By selecting either a sourcetype or source, you're narrowing down the dataset on which you'll perform the regex extraction, making it more manageable and relevant.

The correct command to show the total bytes for each unique combination of page and server isindex=web | stats sum (bytes) BY page server. In Splunk, thestatscommand is used to calculate aggregate statistics over the dataset, such as count, sum, avg, etc. When using theBYclause, it groups the results by the specified fields. The correct syntax does not include commas or the word 'AND' between the field names. Instead, it simply lists the field names separated by spaces within theBYclause.

Reference: The usage of thestatscommand with theBYclause is confirmed by examples in the Splunk Community, where it's explained thatstatswith aby foo barwill output one row for every unique combination of thebyfields1.

When performing an outer join in Splunk using the| join employeeNumber type=outercommand, it combines the rows from both tables based on theemployeeNumberfield. An outer join returns all rows from both tables, with matching rows from both sides where available. If there is no match, the result isNULLon the side of the join where there is no match.

In the provided tables, there are five rows in the first table and three in the second. Since it's an outer join, all rows from both tables will be returned. This means the new table will have a total of eight rows, combining the matched rows and the unmatched rows from both tables.

Splunk Documentation on thejoincommand.

Splunk Community discussions on the usage ofjoinand types of joins.

When using the transaction command in Splunk, the default maximum span between events is set to unlimited. This is indicated by the default value of maxspan=-1, which corresponds to an ''all time'' time range.

The appendcols command in Splunk is used to connect an additional table of data directly to the right side of the existing table. It appends the results of a subsearch as new fields to the current results, effectively adding columns to the existing table.

In Splunk, the NOT operator is used to exclude events from your search results. The searchindex=network NOT StatusCode=200will return all events in the 'network' index where the StatusCode is not 200. This includes events where the StatusCode field is present and has a value other than 200, as well as events where the StatusCode field is not present at all.

Reference: The use of the NOT operator in SPL (Search Processing Language) is consistent with the information provided in the Splunk documentation and resources, which describe how to generate efficient searches and make the most of Splunk's capabilities

The Splunk Common Information Model (CIM) Add-on is a foundational component for many Splunk apps, providing a common framework for data normalization and field extraction. This add-on includes a set of pre-configured data models that are essential for consistent reporting, searching, and correlation across various types of data. These data models help standardize field names and event structures, ensuring that data from disparate sources can be queried in a uniform way. While the CIM Add-on facilitates the use of standardized sourcetypes and supports data validation, the primary feature it offers is the set of pre-configured data models which are crucial for maintaining consistency across different datasets.

A calculated field in Splunk is designed to automatically add fields at search time using an eval expression. This feature allows users to define new fields based on existing data without needing to manually include an eval command in every search. Calculated fields simplify repeated search tasks by embedding the eval logic directly into the field configuration.

Splunk Docs: Calculated fields

Splunk Answers: Purpose of calculated fields