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Splunk Core Certified Power User Exam Sample Questions (Q75-Q80):

NEW QUESTION # 75
When would a user select delimited field extractions using the Field Extractor (FX)?

A. With structured files such as JSON or XML.
B. When a log file has values that are separated by the same character, for example, commas.
C. When a log file contains empty lines or comments.
D. When the file has a header that might provide information about its structure or format.

Answer: B

Explanation:
The correct answer is A. When a log file has values that are separated by the same character, for example, commas.
The Field Extractor (FX) is a utility in Splunk Web that allows you to create new fields from your events by using either regular expressions or delimiters. The FX provides a graphical interface that guides you through the steps of defining and testing your field extractions1.
The FX supports two field extraction methods: regular expression and delimited. The regular expression method works best with unstructured event data, such as logs or messages, that do not have a consistent format or structure. You select a sample event and highlight one or more fields to extract from that event, and the FX generates a regular expression that matches similar events in your data set and extracts the fields from them1.
The delimited method is designed for structured event data: data from files with headers, where all of the fields in the events are separated by a common delimiter, such as a comma, a tab, or a space. You select a sample event, identify the delimiter, and then rename the fields that the FX finds1.
Therefore, you would select the delimited field extraction method when you have a log file that has values that are separated by the same character, for example, commas. This method will allow you to easily extract the fields based on the delimiter without writing complex regular expressions.
The other options are not correct because they are not suitable for the delimited field extraction method. These options are:
* B. When a log file contains empty lines or comments: This option does not indicate that the log file has a structured format or a common delimiter. The delimited method might not work well with this type of data, as it might miss some fields or include some unwanted values.
* C. With structured files such as JSON or XML: This option does not require the delimited method, as Splunk can automatically extract fields from JSON or XML files by using indexed extractions or search-time extractions2. The delimited method might not work well with this type of data, as it might not recognize the nested structure or the special characters.
* D. When the file has a header that might provide information about its structure or format: This option does not indicate that the file has a common delimiter between the fields. The delimited method might not work well with this type of data, as it might not be able to identify the fields based on the header information.
References:
* Build field extractions with the field extractor
* Configure indexed field extraction

NEW QUESTION # 76
Pivot editor enables users to quickly reports but they must use the pivot command.'

A. False
B. True

Answer: A

NEW QUESTION # 77
When can a pipe follow a macro?

A. Only when sharing is set to global for the macro.
B. A pipe may always follow a macro.
C. The current user must own the macro.
D. The macro must be defined in the current app.

Answer: B

Explanation:
A macro is a way to save a segment of a search string as a variable and reuse it in other searches2. A macro can be followed by a pipe, which is a symbol that separates commands in a search pipeline2. A pipe may always follow a macro, regardless of who owns the macro, where the macro is defined or how the macro is shared2. For example, if you have a macro called us_sales that returns events from the US region, you can use it in a search like this: us_sales | stats sum(price) by product2. This search will use the macro to filter the events and then calculate the total price for each product2. Therefore, option A is correct, while options B, C and D are incorrect because they are not conditions that affect whether a pipe can follow a macro.

NEW QUESTION # 78
What functionality does the Splunk Common Information Model (CIM) rely on to normalize fields with different names?

A. Macros.
B. CIM does not work with different names for the same field.
C. The rename command.
D. Field aliases.

Answer: D

Explanation:
The Splunk Common Information Model (CIM) add-on helps you normalize your data from different sources and make it easier to analyze and report on it3. One of the functionalities that the CIM add-on relies on to normalize fields with different names is field aliases3. Field aliases allow you to assign an alternative name to an existing field without changing the original field name or value2. By using field aliases, you can map different field names from different sources or sourcetypes to a common field name that conforms to the CIM standard3. Therefore, option B is correct, while options A, C and D are incorrect.

NEW QUESTION # 79
Consider the the following search run over a time range of last 7 days:
index=web sourcetype=access_conbined | timechart avg(bytes) by product_nane Which option is used to change the default time span so that results are grouped into 12 hour intervals?

A. timespan=12
B. span=12
C. span=12h
D. timespan=12h

Answer: C

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.

NEW QUESTION # 80
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