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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Using Transforming Commands for Visualizations | 5% | - Use the chart command - Use the timechart command |
| Topic 2: Filtering and Formatting Results | 10% | - Use the search and where commands to filter results - The eval command - The fillnull command |
| Topic 3: Creating and Using Workflow Actions | 10% | - Create a POST workflow action - Describe the function of GET, POST, and Search workflow actions - Create a Search workflow action - Create a GET workflow action |
| Topic 4: Creating and Managing Fields | 10% | - Perform delimiter field extractions using the FX - Perform regex field extractions using the Field Extractor (FX) |
| Topic 5: Using the Common Information Model (CIM) Add-On | 10% | - Describe the use of the CIM Add-On - Describe the Splunk CIM |
| Topic 6: Creating and Using Macros | 10% | - Define arguments and variables for a macro - Describe macros - Add and use arguments with a macro - Create and use a basic macro |
| Topic 7: Creating Field Aliases and Calculated Fields | 10% | - Describe, create, and use calculated fields - Describe, create, and use field aliases |
| Topic 8: Creating Data Models | 10% | - Describe the relationship between data models and pivot - Identify data model attributes - Create a data model |
| Topic 9: Creating Tags and Event Types | 10% | - Create an event type - Describe event types and their uses - Create and use tags |
| Topic 10: Correlating Events | 15% | - Group events using fields - Report on transactions - Search with transactions - Determine when to use transactions vs. stats - Group events using fields and time - Identify transactions |
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NEW QUESTION # 43
When would a user select delimited field extractions using the Field Extractor (FX)?
Answer: A
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 # 44
Which of the following is the correct way to use the data model command to search field in the data model within the web dataset?
Answer: D
Explanation:
Explanation
The data model command allows you to run searches on data models that have been accelerated1. The syntax for using the data model command is | datamodel <model_name> <dataset_name> [search <search_string>]1.
Therefore, option A is the correct way to use the data model command to search fields in the data model within the web dataset. Options B and C are incorrect because they do not follow the syntax for the data model command. Option D is incorrect because it does not use the data model command at all.
NEW QUESTION # 45
Which of the following can be saved as an event type?
Answer: C
Explanation:
Event types in Splunk are saved searches that categorize data, making it easier to search for specific patterns or criteria within your data. When saving an event type, the search must essentially filter events based on criteria without performing operations that transform or aggregate the data. Here's a breakdown of the options:
A: The search index-server_472 sourcetype-BETA_494 code-488 | stats count by code performs an aggregation operation (stats count by code), which makes it unsuitable for saving as an event type. Event types are meant to categorize data without aggregating or transforming it.
B: The search index=server_472 sourcetype=BETA_494 code=488 [ | inputlookup append=t servercode.csv] includes a subsearch and input lookup, which is typically used to enrich or filter events based on external data. This complexity goes beyond simple event categorization.
C: The search index=server_472 sourcetype=BETA_494 code=488 | stats where code > 200 includes a filtering condition within a transforming command (stats), which again, is not suitable for defining an event type due to the transformation of data.
D: The search index=server_472 sourcetype=BETA_494 code-488 is the correct answer as it purely filters events based on index, sourcetype, and a code field condition without transforming or aggregating the data.
This is what makes it suitable for saving as an event type, as it categorizes data based on specific criteria without altering the event structure or content.
NEW QUESTION # 46
To identify all of the contributing events within a transaction that contain at least one REJECTevent, which syntax is correct?
Answer: B
NEW QUESTION # 47
Which of the following statements describes this search?
sourcetype=access_combined I transaction JSESSIONID | timechart avg (duration)
Answer: C
NEW QUESTION # 48
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