Splunk Splunk Certifications SPLK-1002 Questions & Answers

• Question 211:

  Which of the following file formats can be extracted using a delimiter field extraction?

  A. CSV

  B. PDF

  C. XML

  D. JSON

  Correct Answer: A

  A delimiter field extraction is a method of extracting fields from data that uses a character or a string to separate fields in each event. A delimiter field extraction can be performed by using the Field Extractor (FX) tool or by editing the props.conf file. A delimiter field extraction can be applied to any file format that uses a delimiter to separate fields, such as CSV, TSV, PSV, etc. A CSV file is a comma-separated values file that uses commas as delimiters. Therefore, a CSV file can be extracted using a delimiter field extraction.

• Question 212:

  What are the two parts of a root event dataset?

  A. Fields and variables.

  B. Fields and attributes.

  C. Constraints and fields.

  D. Constraints and lookups.

  Correct Answer: C

  Reference: https://docs.splunk.com/Documentation/SplunkLight/7.3.5/GettingStarted/Designdatamodel objects

  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.

• Question 213:

  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.

  Correct Answer: B

  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 214:

  What does the transaction command do?

  A. Groups a set of transactions based on time.

  B. Creates a single event from a group of events.

  C. Separates two events based on one or more values.

  D. Returns the number of credit card transactions found in the event logs.

  Correct Answer: B

  The transaction command is a search command that creates a single event from a group of events that share some common characteristics. The transaction command can group events based on fields, time, or both. The transaction command can also create some additional fields for each transaction, such as duration, eventcount, startime, etc. The transaction command does not group a set of transactions based on time, but rather groups a set of events into a transaction based on time. The transaction command does not separate two events based on one or more values, but rather joins multiple events based on one or more values. The transaction command does not return the number of credit card transactions found in the event logs, but rather creates transactions from the events that match the search criteria.

• Question 215:

  Data model fields can be added using the Auto-Extracted method. Which of the following statements describe Auto-Extracted fields? (select all that apply)

  A. Auto-Extracted fields can be hidden in Pivot.

  B. Auto-Extracted fields can have their data type changed.

  C. Auto-Extracted fields can be given a friendly name for use in Pivot.

  D. Auto-Extracted fields can be added if they already exist in the dataset with constraints.

  Correct Answer: ACD

  Auto-Extracted fields in Splunk Data Models are derived directly from the indexed data based on the existing fields within the events. These fields are identified and extracted by Splunk automatically, without the need for explicit field extractions configured by the user. Understanding the characteristics of Auto-Extracted fields is crucial for effectively managing Data Models and utilizing them in Pivot tables for analysis. A. Auto-Extracted fields can be hidden in Pivot. This is true. When building a Data Model, you have the option to hide certain fields from appearing in Pivot, making the Pivot table cleaner and more focused on the fields that are most relevant for analysis. This helps in reducing clutter and focusing on the data that matters most to the users. B. Auto-Extracted fields can have their data type changed. This statement is not typically accurate for Auto-Extracted fields. The data type of an Auto-Extracted field is determined by Splunk based on the field's content in the indexed data. While you can assign a type to a field when you manually create a field in a data model, the inherent data type of Auto-Extracted fields is not something that is changed within the Data Model itself. C. Auto-Extracted fields can be given a friendly name for use in Pivot. This is correct. Within Data Models, you can assign a more user-friendly, descriptive name to an Auto- Extracted field. This feature is particularly useful in making Data Models more intuitive and easier to use for those who may not be familiar with the original field names or when the original field names are not descriptive or user-friendly. D. Auto-Extracted fields can be added if they already exist in the dataset with constraints. This is true. Auto-Extracted fields are based on fields that already exist in the data. When you define a dataset within a Data Model, you can apply constraints to narrow down the events that the dataset includes. The Auto-Extracted fields are then identified from this constrained dataset. This means that the fields must already be present in the data that meets the dataset's constraints to be available for auto-extraction. In summary, Auto-Extracted fields in Splunk Data Models offer a flexible and efficient way to utilize existing data fields within Pivot tables, with options to rename them for clarity and hide unnecessary fields to streamline data analysis.

• Question 216:

  Which of the following statements describe the Common Information Model (CIM)? (select all that apply)

  A. CIM is a methodology for normalizing data.

  B. CIM can correlate data from different sources.

  C. The Knowledge Manager uses the CIM to create knowledge objects.

  D. CIM is an app that can coexist with other apps on a single Splunk deployment.

  Correct Answer: ABC

  Reference: https://docs.splunk.com/Documentation/CIM/4.15.0/User/Overview

  The Common Information Model (CIM) is a methodology for normalizing data from different sources and making it easier to analyze and report on it3. The CIM defines a common set of fields and tags for various domains such as Alerts, Email, Database, Network Traffic, Web and more3. One of the statements that describe the CIM is that it is a methodology for normalizing data, which means that it provides a standard way to name and structure data from different sources so that they can be compared and correlated3. Therefore, option A is correct. Another statement that describes the CIM is that it can correlate data from different sources, which means that it enables you to run searches and reports across data from different sources that share common fields and tags3. Therefore, option B is correct. Another statement that describes the CIM is that the Knowledge Manager uses the CIM to create knowledge objects, which means that the person who is responsible for creating and managing knowledge objects such as data models, field aliases, tags and event types can use the CIM as a guide to make their knowledge objects consistent and compatible with other apps and add-ons3. Therefore, option C is correct. Option D is incorrect because it does not describe the CIM but rather one of its components.

• Question 217:

  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 a search needs to be added to other users' dashboards.

  C. When the search string needs to be used in future searches.

  D. When formatting needs to be included with the search string.

  Correct Answer: C

  Reference: https://answers.splunk.com/answers/4993/eventtype-vs-saved-search.html

  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.

• Question 218:

  Which of the following actions can the eval command perform?

  A. Remove fields from results.

  B. Create or replace an existing field.

  C. Group transactions by one or more fields.

  D. Save SPL commands to be reused in other searches.

  Correct Answer: B

  The eval command is used to create new fields or modify existing fields based on an expression2. The eval command can perform various actions such as calculations, conversions, string manipulations and more2. One of the actions that the eval command can perform is to create or replace an existing field with a new value based on an expression2. For example, | eval status=if(status="200","OK","ERROR") will create or replace the status field with either OK or ERROR depending on the original value of status2. Therefore, option B is correct, while options A, C and D are incorrect because they are not actions that the eval command can perform.

• Question 219:

  What is required for a macro to accept three arguments?

  A. The macro's name ends with (3).

  B. The macro's name starts with (3).

  C. The macro's argument count setting is 3 or more.

  D. Nothing, all macros can accept any number of arguments.

  Correct Answer: A

  To create a macro that accepts arguments, you must include the number of arguments in parentheses at the end of the macro name1. For example, my_macro(3) is a macro that accepts three arguments. The number of arguments in the macro name must match the number of arguments in the definition1. Therefore, option A is correct, while options B, C and D are incorrect.

• Question 220:

  How does a user display a chart in stack mode?

  A. By using the stack command.

  B. By turning on the Use Trellis Layout option.

  C. By changing Stack Mode in the Format menu.

  D. You cannot display a chart in stack mode, only a timechart.

  Correct Answer: C

  A chart is a graphical representation of your search results that shows the relationship between two or more fields2. You can display a chart in stack mode by changing the Stack Mode option in the Format menu2. Stack mode allows you to stack multiple series on top of each other in a chart to show the cumulative values of each series2. Therefore, option C is correct, while options A, B and D are incorrect because they are not ways to display a chart in stack mode.