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Splunk SPLK-1002 exam is the certification exam for the Splunk Core Certified Power User. SPLK-1002 exam tests the candidate's ability to use Splunk to perform tasks such as creating advanced reports, dashboards, and alerts, configuring field aliases and calculated fields, and creating and managing lookups. SPLK-1002 exam also covers topics such as data models, pivot, and charting, and Splunk Enterprise Security.
The SPLK-1002 exam is designed for experienced Splunk users who want to demonstrate their proficiency in using Splunk to solve complex data analysis problems. SPLK-1002 Exam covers a wide range of topics, including advanced search and reporting commands, data models, field extractions, lookups, and event types. Candidates are expected to have a deep understanding of how Splunk works, its architecture, and best practices for performance optimization.
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NEW QUESTION # 49
Which field will be used to populate the field if the productName and product:d fields have values for a given event?
| eval productINFO=coalesco(productName,productid)
Answer: A
Explanation:
Explanation
The correct answer is B. The value for the productName field because it appears first.
The coalesce function is an eval function that takes an arbitrary number of arguments and returns the first value that is not null. A null value means that the field has no value at all, while an empty value means that the field has a value, but it is "" or zero-length1.
The coalesce function can be used to combine fields that have different names but represent the same data, such as IP address or user name. The coalesce function can also be used to rename fields for clarity or convenience2.
The syntax for the coalesce function is:
coalesce(<field1>,<field2>,...)
The coalesce function will return the value of the first field that is not null in the argument list. If all fields are null, the coalesce function will return null.
For example, if you have a set of events where the IP address is extracted to either clientip or ipaddress, you can use the coalesce function to define a new field called ip, that takes the value of either clientip or ipaddress, depending on which is not null:
| eval ip=coalesce(clientip,ipaddress)
In your example, you have a set of events where the product name is extracted to either productName or productid, and you use the coalesce function to define a new field called productINFO, that takes the value of either productName or productid, depending on which is not null:
| eval productINFO=coalesce(productName,productid)
If both productName and productid fields have values for a given event, the coalesce function will return the value of the productName field because it appears first in the argument list. The productid field will be ignored by the coalesce function.
Therefore, the value for the productName field will be used to populate the productINFO field if both fields have values for a given event.
References:
Search Command> Coalesce
USAGE OF SPLUNK EVAL FUNCTION : COALESCE
NEW QUESTION # 50
Which of the following is true about data model attributes?
Answer: C
Explanation:
Data model attributes are fields that are added to a dataset from search time field extractions, calculated fields, lookups, or aliases. They can be created within the data model editor or inherited from a parent dataset. They can be edited or removed unless they are required by the data model. They can be added to any type of dataset, not just root search datasets.
Reference
See About data models, [Define data model attributes], and [Edit data model datasets] in the Splunk Documentation.
NEW QUESTION # 51
When performing a regular expression (regex) field extraction using the Field Extractor (FX), what happens when the requireoption is used?
Answer: A
NEW QUESTION # 52
When should you use the transaction command instead of the scats command?
Answer: B
NEW QUESTION # 53
The fields sidebar does not show________. (Select all that apply.)
Answer: B
Explanation:
The fields sidebar is a panel that shows the fields that are present in your search results2. The fields sidebar does not show all extracted fields, which are fields that are extracted from your raw data using various methods such as regular expressions, delimiters or key-value pairs2. The fields sidebar only shows 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. Therefore, option C is correct, while options A and B are incorrect because they are types of fields that the fields sidebar does show.
NEW QUESTION # 54
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