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質問 # 23
Which of the following can be used with the eval command tostring function (select all that apply)
- A. ''Decimal''
- B. ''commas''
- C. ''hex''
- D. ''duration''
正解：B、C、D
解説：
Explanation
https://docs.splunk.com/Documentation/Splunk/8.1.0/SearchReference/ConversionFunctions#tostring.28X.2CY.
質問 # 24
A field alias has been created based on an original field. A search without any transforming commands is then executed in Smart Mode. Which field name appears in the results?
- A. Both will appear in the Interesting Fields list, but only if they appear in at least 20 percent of events.
- B. The alias only appears in the All Fields list and the original field only appears in the Interesting Fields list.
- C. The original field only appears in All Fields list and the alias only appears in the Interesting Fields list.
- D. Both will appear in the All Fields list, but only if the alias is specified in the search.
正解：A
解説：
Explanation
A field alias is a way to assign an alternative name to an existing field without changing the original field name or value2. You can use field aliases to make your field names more consistent or descriptive across different sources or sourcetypes2. When you run a search without any transforming commands in Smart Mode, Splunk automatically identifies and displays interesting fields in your results2. Interesting fields are fields that appear in at least 20 percent of events or have high variability among values2. If you have created a field alias based on an original field, both the original field name and the alias name will appear in the Interesting Fields list if they meet these criteria2. However, only one of them will appear in each event depending on which one you have specified in your search string2. Therefore, option B is correct, while options A, C and D are incorrect.
質問 # 25
Which of the following statements about tags is true? (select all that apply.)
- A. Tags categorize events based on a search.
- B. Tags are based on field/vale pairs.
- C. Tags are designed to make data more understandable.
- D. Tags are case-insensitive.
正解：B、C
解説：
The following statements about tags are true: tags are based on field/value pairs and tags categorize events based on a search. Tags are custom labels that can be applied to fields or field values to provide additional context or meaning for your data. Tags can be used to filter or analyze your data based on common concepts or themes. Tags can be created by using various methods, such as search commands, configuration files, user interfaces, etc. Some of the characteristics of tags are:
Tags are based on field/value pairs: This means that tags are associated with a specific field name and a specific field value. For example, you can create a tag called "alert" for the field name "status" and the field value "critical". This means that only events that have status=critical will have the "alert" tag applied to them.
Tags categorize events based on a search: This means that tags are defined by a search string that matches the events that you want to tag. For example, you can create a tag called "web" for the search string sourcetype=access_combined. This means that only events that match the search string sourcetype=access_combined will have the "web" tag applied to them.
The following statements about tags are false: tags are case-insensitive and tags are designed to make data more understandable. Tags are case-sensitive and tags are designed to make data more searchable. Tags are case-sensitive: This means that tags must match the exact case of the field name and field value that they are associated with. For example, if you create a tag called "alert" for the field name "status" and the field value "critical", it will not apply to events that have status=CRITICAL or Status=critical. Tags are designed to make data more searchable: This means that tags can help you find relevant events or patterns in your data by using common concepts or themes. For example, if you create a tag called "web" for the search string sourcetype=access_combined, you can use tag=web to find all events related to web activity.
質問 # 26
Which of the following statements describes macros?
- A. A macro is a reusable search string that must contain only a portion of the search.
- B. A macro is a reusable search string that must have a fixed time range.
- C. A macro is a reusable search string that may have a flexible time range.
- D. A macro is a reusable search string that must contain the full search.
正解：A
解説：
Explanation
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Definesearchmacros
質問 # 27
Information needed to create a GET workflow action includes which of the following? (Choose all that apply.)
- A. A URI where the user will be directed at search time.
- B. A name for the URI where the user will be directed at search time.
- C. A name for the workflow action.
- D. A label that will appear in the Event Action menu at search time.
正解：A、D
解説：
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/SetupaGETworkflowaction
質問 # 28
Which workflow uses field values to perform a secondary search?
- A. Search
- B. POST
- C. Action
- D. Sub-search
正解：A
解説：
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/CreateworkflowactionsinSplunkWeb
質問 # 29
This search user!=*_________________.
- A. displays only events that do NOT contain a value for user
- B. displays all events
- C. displays only events that contain a value for user
正解：A
質問 # 30
Which delimiters can the Field Extractor (FX) detect? (select all that apply)
- A. Spaces
- B. Tabs
- C. Pipes
- D. Commas
正解：A、C、D
解説：
Reference:
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. The FX can detect some common delimiters automatically, such as pipes (|), spaces ( ), commas (,), semicolons (;), etc. The FX cannot detect tabs (\t) as delimiters automatically, but you can specify them manually in the FX interface.
質問 # 31
What does the Splunk Common Information Model (CIM) add-on include? (select all that apply)
- A. Pre-configured data models
- B. Custom visualizations
- C. Automatic data model acceleration
- D. Fields and event category tags
正解：A、D
解説：
The Splunk Common Information Model (CIM) add-on is a collection of pre-built data models and knowledge
objects that help you normalize your data from different sources and make it easier to analyze and report on
it3. The CIM add-on includes pre-configured data models that cover various domains such as Alerts, Email,
Database, Network Traffic, Web and more3. Therefore, option B is correct. The CIM add-on also includes
fields and event category tags that define the common attributes and labels for the data models3. Therefore,
option C is correct. The CIM add-on does not include custom visualizations or automatic data model
acceleration. Therefore, options A and D are incorrect.
質問 # 32
Which of the following statements describe data model acceleration? (select all that apply)
- A. Private data models cannot be accelerated.
- B. You must have administrative permissions or the accelerate_dacamodel capability to accelerate a data model.
- C. Root events cannot be accelerated.
- D. Accelerated data models cannot be edited.
正解：A、B、D
質問 # 33
which of the following commands are used when creating visualizations(select all that apply.)
- A. Geom
- B. Choropleth
- C. iplocation
- D. Geostats
正解：A、C、D
解説：
The following commands are used when creating visualizations: geom, geostats, and iplocation. Visualizations are graphical representations of data that show trends, patterns, or comparisons. Visualizations can have different types, such as charts, tables, maps, etc. Visualizations can be created by using various commands that transform the data into a suitable format for the visualization type. Some of the commands that are used when creating visualizations are:
geom: This command is used to create choropleth maps that show geographic regions with different colors based on some metric. The geom command takes a KMZ file as an argument that defines the geographic regions and their boundaries. The geom command also takes a field name as an argument that specifies the metric to use for coloring the regions.
geostats: This command is used to create cluster maps that show groups of events with different sizes and colors based on some metric. The geostats command takes a latitude and longitude field as arguments that specify the location of the events. The geostats command also takes a statistical function as an argument that specifies the metric to use for sizing and coloring the clusters.
iplocation: This command is used to create location-based visualizations that show events with different attributes based on their IP addresses. The iplocation command takes an IP address field as an argument and adds some additional fields to the events, such as Country, City, Latitude, Longitude, etc. The iplocation command can be used with other commands such as geom or geostats to create maps based on IP addresses.
質問 # 34
What does the fillnull command replace null values with, it the value argument is not specified?
- A. N/A
- B. NULL
- C. 0
- D. NaN
正解：C
解説：
Reference:https://answers.splunk.com/answers/653427/fillnull-doesnt-work-without-specfying-a-field.html
質問 # 35
__________ datasets can be added to root dataset to narrow down the search
- A. event
- B. child
- C. extracted
- D. parent
正解：B
解説：
Child datasets can be added to root datasets to narrow down the search. Datasets are collections of events that represent your data in a structured and hierarchical way. Datasets can be created by using commands such as datamodel or pivot. Datasets can have different types, such as events, search, transaction, etc. Datasets can also have different levels, such as root or child. Root datasets are base datasets that contain all events from a data model or an index. Child datasets are derived datasets that contain a subset of events from a parent dataset based on some constraints, such as search terms, fields, time range, etc. Child datasets can be added to root datasets to narrow down the search and filter out irrelevant events.
質問 # 36
In which of the following scenarios is an event type more effective than a saved search?
- A. When a search should always include the same time range.
- B. When formatting needs to be included with the search string.
- C. When a search needs to be added to other users' dashboards.
- D. When the search string needs to be used in future searches.
正解：D
解説：
Reference:
An event type is a way to categorize events based on a search string that matches the events2. You can use event types to simplify your searches by replacing long or complex search strings with short and simple event type names2. An event type is more effective than a saved search when the search string needs to be used in future searches because it allows you to reuse the search string without having to remember or type it again2. Therefore, option C is correct, while options A, B and D are incorrect because they are not scenarios where an event type is more effective than a saved search.
質問 # 37
What are the two parts of a root event dataset?
- A. Constraints and lookups.
- B. Fields and variables.
- C. Fields and attributes.
- D. Constraints and fields.
正解：D
解説：
Reference:
A root event dataset is the base dataset for a data model that defines the source or sources of the data and the constraints and fields that apply to the data1. A root event dataset has two parts: constraints and fields1. Constraints are filters that limit the data to a specific index, source, sourcetype, host or search string1. Fields are the attributes that describe the data and can be extracted, calculated or looked up1. Therefore, option C is correct, while options A, B and D are incorrect.
質問 # 38
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