Splunk SPLK-1002 Online Practice Questions and Exam Preparation

Splunk SPLK-1002 Online Questions & Answers

• Question 141:

  Which of the following statements describes field aliases?

  A. Field alias names replace the original field name.
  B. Field aliases can be used in lookup file definitions.
  C. Field aliases only normalize data across sources and sourcetypes.
  D. Field alias names are not case sensitive when used as part of a search.
  B. Field aliases can be used in lookup file definitions.

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  Explanation/Reference:

  Field aliases are alternative names for fields in Splunk. Field aliases can be used to normalize data across different sources and sourcetypes that have different field names for the same concept. For example, you can create a field alias for src_ip that maps to clientip, source_address, or any other field name that represents the source IP address in different sourcetypes. Field aliases can also be used in lookup file definitions to map fields in your data to fields in the lookup file. For example, you can use a field alias for src_ip to map it to ip_address in a lookup file that contains geolocation information for IP addresses. Field alias names do not replace the original field name, but rather create a copy of the field with a different name. Field alias names are case sensitive when used as part of a search, meaning that src_ip and SRC_IP are different fields.

• Question 142:

  When should the regular expression mode of Field Extractor (FX) be used? (select all that apply)

  A. For data cleanly separated by a space, a comma, or a pipe character.
  B. For data in a CSV (comma-separated value) file.
  C. For data with multiple, different characters separating fields.
  D. For unstructured data.
  C. For data with multiple, different characters separating fields.
  D. For unstructured data.

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  Explanation/Reference:

  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.ReferencesSee Build field extractions with the field extractor - Splunk Documentation and Field Extractor: Select Method step - Splunk Documentation.

• Question 143:

  What do events in a transaction have in common?

  A. All events in a transaction must have the same timestamp.
  B. All events in a transaction must have the same sourcetype.
  C. All events in a transaction must have the exact same set of fields.
  D. All events in a transaction must be related by one or more fields.
  D. All events in a transaction must be related by one or more fields.

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  Explanation/Reference:

  Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Abouttransacti ons

  A transaction is a group of events that share some common characteristics, such as fields, time, or both. A transaction can be created by using the transaction command or by defining an event type with transactiontype=true in props.conf. Events in a transaction have one or more fields in common that relate them to each other. For example, you can create a transaction based on JSESSIONID, which is a unique identifier for each user session in web logs. Events in a transaction do not have to have the same timestamp, sourcetype, or exact same set of fields. They only have to share one or more fields that define the transaction.

• Question 144:

  Which workflow action method can be used the action type is set to link?

  A. GET
  B. PUT
  C. Search
  D. UPDATE
  A. GET

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  Explanation/Reference:

  https://docs.splunk.com/Documentation/Splunk/8.0.2/Knowledge/SetupaGETworkflowaction

  Define a GET workflow action

  Steps

  Navigate to Settings > Fields > Workflow Actions.

  Click New to open up a new workflow action form.

  Define a Label for the action.

  The Label field enables you to define the text that is displayed in either the field or event workflow menu. Labels can be static or include the value of relevant fields. Determine whether the workflow action applies to specific fields or event

  types in your data.

  Use Apply only to the following fields to identify one or more fields. When you identify fields, the workflow action only appears for events that have those fields, either in their event menu or field menus. If you leave it blank or enter an asterisk

  the action appears in menus for all fields.

  Use Apply only to the following event types to identify one or more event types. If you identify an event type, the workflow action only appears in the event menus for events that belong to the event type.

  For Show action in determine whether you want the action to appear in the Event menu, the Fields menus, or Both.

  Set Action type to link.

  In URI provide a URI for the location of the external resource that you want to send your field values to.

  Similar to the Label setting, when you declare the value of a field, you use the name of the field enclosed by dollar signs.

  Variables passed in GET actions via URIs are automatically URL encoded during transmission. This means you can include values that have spaces between words or punctuation characters. Under Open link in, determine whether the

  workflow action displays in the current window or if it opens the link in a new window.

  Set the Link method to get.

  Click Save to save your workflow action definition.

• Question 145:

  By default search results are not returned in ________ order.

  A. Chronological
  B. Reverser chronological
  C. ASCIE
  D. Alphabetical
  A. Chronological
  D. Alphabetical

• Question 146:

  There are several ways to access the field extractor. Which option automatically identifies data type, source type, and sample event?

  A. Event Actions > Extract Fields
  B. Fields sidebar > Extract New Field
  C. Settings > Field Extractions > New Field Extraction
  D. Settings > Field Extractions > Open Field Extraction
  B. Fields sidebar > Extract New Field

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  Explanation/Reference:

  There are several ways to access the field extractor. The option that automatically identifies data type, source type, and sample event is Fields sidebar > Extract New Field. The field extractor is a tool that helps you extract fields from your

  data using delimiters or regular expressions. The field extractor can generate a regex for you based on your selection of sample values or you can enter your own regex in the field extractor. The field extractor can be accessed by using

  various methods, such as:

  Fields sidebar > Extract New Field: This is the easiest way to access the field extractor. The fields sidebar is a panel that shows all available fields for your data and their values. When you click on Extract New Field in the fields sidebar,

  Splunk will automatically identify the data type, source type, and sample event for your data based on your current search criteria. You can then use the field extractor to select sample values and generate a regex for your new field. Event

  Actions > Extract Fields: This is another way to access the field extractor. Event actions are actions that you can perform on individual events in your search results, such as viewing event details, adding to report, adding to dashboard, etc.

  When you click on Extract Fields in the event actions menu, Splunk will use the current event as the sample event for your data and ask you to select the source type and data type for your data. You can then use the field extractor to select

  sample values and generate a regex for your new field. Settings > Field Extractions > New Field Extraction: This is a more advanced way to access the field extractor. Settings is a menu that allows you to configure various aspects of Splunk,

  such as indexes, inputs, outputs, users, roles, apps, etc. When you click on New Field Extraction in the Settings menu, Splunk will ask you to enter all the details for your new field extraction manually, such as app context, name, source type,

  data type, sample event, regex, etc. You can then use the field extractor to verify or modify your regex for your new field.

• Question 147:

  A calculated field may be based on which of the following?

  A. Lookup tables
  B. Extracted fields
  C. Regular expressions
  D. Fields generated within a search string
  B. Extracted fields

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  Explanation/Reference:

  As mentioned before, a calculated field is a field that you create based on the value of another field or fields. A calculated field can be based on extracted fields, which are fields that are extracted from your raw data using various methods such as regular expressions, delimiters or key-value pairs. Therefore, option B is correct, while options A, C and D are incorrect because they are not types of fields that a calculated field can be based on.

• Question 148:

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

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

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  Explanation/Reference:

  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 extractions. 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 them. 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 finds. 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 extractions. 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 betweenthe 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

• Question 149:

  What commands can be used to group events from one or more data sources?

  A. eval, coalesce
  B. transaction, stats
  C. stats, format
  D. top, rare
  B. transaction, stats

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  Explanation/Reference:

  The transaction and stats commands are two ways to group events from one or more data sources based on common fields or time ranges. The transaction command creates a single event out of a group of related events, while the stats command calculates summary statistics over a group of events. The eval and coalesce commands are used to create or combine fields, not to group events. The format command is used to format the results of a subsearch, not to group events. The top and rare commands are used to rank the most or least common values of a field, not to group events

  1: SplunkCore Certified Power User Track, page 9.

  2: Splunk Documentation, transaction command.

  3: Splunk Documentation, stats command.

• Question 150:

  After manually editing; a regular expression (regex), which of the following statements is true?

  A. Changes made manually can be reverted in the Field Extractor (FX) UI.
  B. It is no longer possible to edit the field extraction in the Field Extractor (FX) UI.
  C. It is not possible to manually edit a regular expression (regex) that was created using the Field Extractor (FX) UI.
  D. The Field Extractor (FX) UI keeps its own version of the field extraction in addition to the one that was manually edited.
  A. Changes made manually can be reverted in the Field Extractor (FX) UI.
  B. It is no longer possible to edit the field extraction in the Field Extractor (FX) UI.
  C. It is not possible to manually edit a regular expression (regex) that was created using the Field Extractor (FX) UI.