SPLK-1002 Exam Dumps

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. Some of the delimiters that will work with FX are:
Tabs: horizontal spaces that align text in columns.
Pipes: vertical bars that often indicate logical OR operations.
Spaces: blank characters that separate words or symbols.
Therefore, the delimiters A, B, and D will work with FX.

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. Data models can be composed of one or more of the following datasets:
Events datasets: These are the base datasets that represent raw events in Splunk. Events datasets can be filtered by constraints, such as search terms, sourcetypes, indexes, etc.
Search datasets: These are derived datasets that represent the results of a search on events or other datasets. Search datasets can use any search command, such as stats, eval, rex, etc., to transform the data.
Transaction datasets: These are derived datasets that represent groups of events that are related by fields, time, or both. Transaction datasets can use the transaction command or event types with transactiontype=true to create transactions.

Explanation: In this search, count will appear on the y-axis2. This search uses the chart command to create a chart of the count of events over host for events that have status not equal to 2002. The chart command creates a table with one column for each value of the field after the over clause and one row for each value of the field after the by clause (if any)2. The values in the table are calculated by applying the function before the over clause to the events in each group2. In this case, the chart command creates a table with one column for each host and one row for the count of events for each host. The y-axis of the chart shows the values of the count function applied to each host. Therefore, option C is correct, while options A and B are incorrect because they appear on the x-axis or as labels of the chart.

Explanation: Field aliases in Splunk are alternate names assigned to fields. These can be particularly useful for normalizing data from different sources or simply for making field names more intuitive. Once an alias is created for a field, it can be used across various Splunk knowledge objects, enhancing their flexibility and utility.
A. Calculated fields, lookups, event types, and tags: This is the correct answer. Field aliases can indeed be referenced in calculated fields, lookups, event types, and tags within Splunk. When you create an alias for a field, that alias can then be used in these knowledge objects just like any standard field name.
Calculated fields: These are expressions that can create new field values based on existing data. You can use an alias in a calculated field expression to refer to the original field.
Lookups: These are used to enrich your event data by referencing external data sources. If you've created an alias for a field that matches a field in your lookup table, you can use that alias in your lookup configurations.
Event types: These are classifications for events that meet certain search criteria. You can use field aliases in the search criteria for defining an event type.
Tags: These allow you to assign meaningful labels to data, making it easier to search and report on. You can use field aliases in the search criteria that you tag.

Explanation: When creating an event type in Splunk, subsearches are allowed in the search string. Subsearches enable users to perform a secondary search whose results are used as input for the main search. This functionality is useful for more complex event type definitions that require additional filtering or criteria based on another search.

Explanation: The regular expression mode of Field Extractor (FX) should be used for data with multiple, different characters separating fields or for unstructured data. The regular expression mode allows you to select a sample event and highlight the fields that you want to extract, and the field extractor generates a regular expression that matches similar events and extracts the fields from them. References See Build field extractions with the field extractor - Splunk Documentation and Field Extractor: Select Method step - Splunk Documentation.

Explanation:
The span option is used to specify the time span for the timechart command. The span value can be a number followed by a time unit, such as h for hour, d for day, w for week, etc. The span value determines how the data is grouped into time buckets. For example, span=12h means that the data is grouped into 12-hour intervals. The timespan option is not a valid option for the timechart command2.
1: Splunk Core Certified Power User Track, page 9.
2: Splunk Documentation, timechart command.