Practice Free SPLK-1002 Exam Online Questions
Question #1
Which type of workflow action sends field values to an external resource (e.g. a ticketing system)?
- A . POST
- B . Search
- C . GET
- D . Format
Correct Answer: A
A
Explanation:
The type of workflow action that sends field values to an external resource (e.g. a ticketing system) is POST. A POST workflow action allows you to send a POST request to a URI location with field values or static values as arguments. For example, you can use a POST workflow action to create a ticket in an external system with information from an event.
A
Explanation:
The type of workflow action that sends field values to an external resource (e.g. a ticketing system) is POST. A POST workflow action allows you to send a POST request to a URI location with field values or static values as arguments. For example, you can use a POST workflow action to create a ticket in an external system with information from an event.
Question #2
This function of the stats command allows you to identify the number of values a field has.
- A . max
- B . distinct_count
- C . fields
- D . count
Correct Answer: D
Question #3
What is the Splunk Common Information Model (CIM)?
- A . The CIM is a prerequisite that any data source must meet to be successfully onboarded into Splunk.
- B . The CIM provides a methodology to normalize data from different sources and source types.
- C . The CIM defines an ecosystem of apps that can be fully supported by Splunk.
- D . The CIM is a data exchange initiative between software vendors.
Correct Answer: B
B
Explanation:
The Splunk Common Information Model (CIM) provides a methodology to normalize data from different sources and source types. The CIM defines a common set of fields and tags for different types of data, such as web, network, email, etc. This allows you to search and analyze data from different sources in a consistent way.
B
Explanation:
The Splunk Common Information Model (CIM) provides a methodology to normalize data from different sources and source types. The CIM defines a common set of fields and tags for different types of data, such as web, network, email, etc. This allows you to search and analyze data from different sources in a consistent way.
Question #4
When creating an event type, which is allowed in the search string?
- A . Tags
- B . Joins
- C . Subsearches
- D . Pipes
Correct Answer: C
C
Explanation:
When creating an event type in Splunk, subsearches are allowed in the search string. Subsearches enable users to perform a secondary search whose results are used as input for the main search. This functionality is useful for more complex event type definitions that require additional filtering or criteria based on another search.
Reference: Splunk Docs: About subsearches
Splunk Docs: Event type creation
Splunk Answers: Using subsearches in event types
C
Explanation:
When creating an event type in Splunk, subsearches are allowed in the search string. Subsearches enable users to perform a secondary search whose results are used as input for the main search. This functionality is useful for more complex event type definitions that require additional filtering or criteria based on another search.
Reference: Splunk Docs: About subsearches
Splunk Docs: Event type creation
Splunk Answers: Using subsearches in event types
Question #5
Which of the following eval commands will provide a new value for host from src if it exists?
- A . | eval host = if (isnu11 (src), src, host)
- B . | eval host = if (NOT src = host, src, host)
- C . | eval host = if (src = host, src, host)
- D . | eval host = if (isnotnull (src), src, host)
Correct Answer: D
D
Explanation:
The eval command is a Splunk command that allows you to create or modify fields using expressions .
The if function is an expression that evaluates a condition and returns a value based on whether the condition is true or false. The syntax of the if function is if(X,Y,Z), where X is the condition, Y is the value to return if X is true, and Z is the value to return if X is false.
The isnotnull function is an expression that returns true if the argument is not null, and false otherwise. The syntax of the isnotnull function is isnotnull(X), where X is the argument to check. Therefore, the expression if (isnotnull (src), src, host) returns the value of src if it is not null, and the value of host otherwise. This means that it will provide a new value for host from src if it exists, and keep the original value of host otherwise.
D
Explanation:
The eval command is a Splunk command that allows you to create or modify fields using expressions .
The if function is an expression that evaluates a condition and returns a value based on whether the condition is true or false. The syntax of the if function is if(X,Y,Z), where X is the condition, Y is the value to return if X is true, and Z is the value to return if X is false.
The isnotnull function is an expression that returns true if the argument is not null, and false otherwise. The syntax of the isnotnull function is isnotnull(X), where X is the argument to check. Therefore, the expression if (isnotnull (src), src, host) returns the value of src if it is not null, and the value of host otherwise. This means that it will provide a new value for host from src if it exists, and keep the original value of host otherwise.
Question #6
What are the expected results for a search that contains the command | where A=B?
- A . Events that contain the string value where A=B.
- B . Events that contain the string value A=B.
- C . Events where values of field are equal to values of field B.
- D . Events where field A contains the string value B.
Correct Answer: C
C
Explanation:
The correct answer is C. Events where values of field A are equal to values of field B.
The where command is used to filter the search results based on an expression that evaluates to true or false. The where command can compare two fields, two values, or a field and a value. The where command can also use functions, operators, and wildcards to create complex expressions1.
The syntax for the where command is:
| where <expression>
The expression can be a comparison, a calculation, a logical operation, or a combination of these.
The expression must evaluate to true or false for each event.
To compare two fields with the where command, you need to use the field names without any quotation marks. For example, if you want to find events where the values for the field A match the values for the field B, you can use the following syntax: | where A=B
This will return only the events where the two fields have the same value.
The other options are not correct because they use different syntax or fields that are not related to the where command.
These options are:
A) Events that contain the string value where A=B: This option uses the string value where A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “where A=B” in them.
B) Events that contain the string value A=B: This option uses the string value A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “A=B” in them.
D) Events where field A contains the string value B: This option uses quotation marks around the value B, which is not valid syntax for comparing fields with the where command. Quotation marks are used to enclose phrases or exact matches in a search2. This option will return events where the field A contains the string value “B”.
Reference: where command usage Search command cheatsheet
C
Explanation:
The correct answer is C. Events where values of field A are equal to values of field B.
The where command is used to filter the search results based on an expression that evaluates to true or false. The where command can compare two fields, two values, or a field and a value. The where command can also use functions, operators, and wildcards to create complex expressions1.
The syntax for the where command is:
| where <expression>
The expression can be a comparison, a calculation, a logical operation, or a combination of these.
The expression must evaluate to true or false for each event.
To compare two fields with the where command, you need to use the field names without any quotation marks. For example, if you want to find events where the values for the field A match the values for the field B, you can use the following syntax: | where A=B
This will return only the events where the two fields have the same value.
The other options are not correct because they use different syntax or fields that are not related to the where command.
These options are:
A) Events that contain the string value where A=B: This option uses the string value where A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “where A=B” in them.
B) Events that contain the string value A=B: This option uses the string value A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “A=B” in them.
D) Events where field A contains the string value B: This option uses quotation marks around the value B, which is not valid syntax for comparing fields with the where command. Quotation marks are used to enclose phrases or exact matches in a search2. This option will return events where the field A contains the string value “B”.
Reference: where command usage Search command cheatsheet
Question #7
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
Correct Answer: B
B
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 events23
1: Splunk Core Certified Power User Track, page 9. 2: Splunk Documentation, transaction command. 3: Splunk Documentation, stats command.
B
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 events23
1: Splunk Core Certified Power User Track, page 9. 2: Splunk Documentation, transaction command. 3: Splunk Documentation, stats command.
Question #8
Which of the following describes the I transaction command?
- A . It is an SPL command that groups at least two events together based on shared values in selected fields.
- B . It allows an exchange of data from one Splunk index to another Splunk index.
- C . It is an SPL command that groups events together with shared values in selected fields.
- D . It allows an exchange of data from one Splunk system to another Splunk system.
Correct Answer: C
C
Explanation:
The transaction command is a Splunk command that finds transactions based on events that meet various constraints.
Transactions are made up of the raw text (the _raw field) of each member, the time and date fields of the earliest member, as well as the union of all other fields of each member.
The transaction command groups events together by matching one or more fields that have the same value across the events. For example, | transaction clientip will group events that have the same value in the clientip field.
C
Explanation:
The transaction command is a Splunk command that finds transactions based on events that meet various constraints.
Transactions are made up of the raw text (the _raw field) of each member, the time and date fields of the earliest member, as well as the union of all other fields of each member.
The transaction command groups events together by matching one or more fields that have the same value across the events. For example, | transaction clientip will group events that have the same value in the clientip field.
Question #9
Which of the following transforming commands can be used with transactions?
chart, timechart, stats, eventstats
chart, timechart, stats, diff
chart, timeehart, datamodel, pivot
chart, timecha:t, stats, pivot
Correct Answer: A
Explanation:
The correct answer is A. chart, timechart, stats, eventstats.
Transforming commands are commands that change the format of the search results into a table or a chart. They can be used to perform statistical calculations, create visualizations, or manipulate data in various ways1.
Transactions are groups of events that share some common values and are related in some way. Transactions can be defined by using the transaction command or by creating a transaction type in the transactiontypes.conf file2.
Some transforming commands can be used with transactions to create tables or charts based on the transaction fields.
These commands include:
chart: This command creates a table or a chart that shows the relationship between two or more fields. It can be used to aggregate values, count occurrences, or calculate statistics3.
timechart: This command creates a table or a chart that shows how a field changes over time. It can be used to plot trends, patterns, or outliers4.
stats: This command calculates summary statistics on the fields in the search results, such as count,
sum, average, etc. It can be used to group and aggregate data by one or more fields5.
eventstats: This command calculates summary statistics on the fields in the search results, similar to
stats, but it also adds the results to each event as new fields. It can be used to compare events with
the overall statistics.
These commands can be applied to transactions by using the transaction fields as arguments. For example, if you have a transaction type named “login” that groups events based on the user field and has fields such as duration and eventcount, you can use the following commands with transactions: | chart count by user: This command creates a table or a chart that shows how many transactions each user has.
| timechart span=1h avg(duration) by user: This command creates a table or a chart that shows the average duration of transactions for each user per hour.
| stats sum(eventcount) as total_events by user: This command creates a table that shows the total number of events for each user across all transactions.
| eventstats avg(duration) as avg_duration: This command adds a new field named avg_duration to each transaction that shows the average duration of all transactions.
The other options are not valid because they include commands that are not transforming commands or cannot be used with transactions. These commands are:
diff: This command compares two search results and shows the differences between them. It is not a transforming command and it does not work with transactions.
datamodel: This command retrieves data from a data model, which is a way to organize and categorize data in Splunk. It is not a transforming command and it does not work with transactions. pivot: This command creates a pivot report, which is a way to analyze data from a data model using a graphical interface. It is not a transforming command and it does not work with transactions.
Reference: About transforming commands
About transactions
chart command overview
timechart command overview
stats command overview
[eventstats command overview]
[diff command overview]
[datamodel command overview]
[pivot command overview]
Explanation:
The correct answer is A. chart, timechart, stats, eventstats.
Transforming commands are commands that change the format of the search results into a table or a chart. They can be used to perform statistical calculations, create visualizations, or manipulate data in various ways1.
Transactions are groups of events that share some common values and are related in some way. Transactions can be defined by using the transaction command or by creating a transaction type in the transactiontypes.conf file2.
Some transforming commands can be used with transactions to create tables or charts based on the transaction fields.
These commands include:
chart: This command creates a table or a chart that shows the relationship between two or more fields. It can be used to aggregate values, count occurrences, or calculate statistics3.
timechart: This command creates a table or a chart that shows how a field changes over time. It can be used to plot trends, patterns, or outliers4.
stats: This command calculates summary statistics on the fields in the search results, such as count,
sum, average, etc. It can be used to group and aggregate data by one or more fields5.
eventstats: This command calculates summary statistics on the fields in the search results, similar to
stats, but it also adds the results to each event as new fields. It can be used to compare events with
the overall statistics.
These commands can be applied to transactions by using the transaction fields as arguments. For example, if you have a transaction type named “login” that groups events based on the user field and has fields such as duration and eventcount, you can use the following commands with transactions: | chart count by user: This command creates a table or a chart that shows how many transactions each user has.
| timechart span=1h avg(duration) by user: This command creates a table or a chart that shows the average duration of transactions for each user per hour.
| stats sum(eventcount) as total_events by user: This command creates a table that shows the total number of events for each user across all transactions.
| eventstats avg(duration) as avg_duration: This command adds a new field named avg_duration to each transaction that shows the average duration of all transactions.
The other options are not valid because they include commands that are not transforming commands or cannot be used with transactions. These commands are:
diff: This command compares two search results and shows the differences between them. It is not a transforming command and it does not work with transactions.
datamodel: This command retrieves data from a data model, which is a way to organize and categorize data in Splunk. It is not a transforming command and it does not work with transactions. pivot: This command creates a pivot report, which is a way to analyze data from a data model using a graphical interface. It is not a transforming command and it does not work with transactions.
Reference: About transforming commands
About transactions
chart command overview
timechart command overview
stats command overview
[eventstats command overview]
[diff command overview]
[datamodel command overview]
[pivot command overview]
Question #10
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
Explanation:
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.
A
Explanation:
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.