View Full Splunk SPLK-5002 Exam Dumps and Practice Test Dumps

 

Question 361. An analyst wants to inspect the fields, field types, distinct values, and other summary information available in a set of events. Which SPL command is designed for this type of field-level overview?

1. metadata
2. fieldsummary
3. fields
4. table

Correct Answer: 2. fieldsummary

Explanation :-

The fieldsummary command provides summary information about fields in the current result set. It can help an analyst understand field characteristics, including counts and information about distinct values. metadata provides metadata about indexed data sources, hosts, sources, or sourcetypes rather than detailed field-level statistics for the current events. fields controls which fields are included or excluded, while table formats selected fields into a tabular result. fieldsummary is therefore useful during data exploration when an analyst needs a quick overview of the fields available in the current search results.

Question 362. An administrator wants to obtain metadata about hosts that have reported data to Splunk, including information useful for understanding host activity. Which command is appropriate?

1. fieldsummary
2. metadata
3. stats
4. tstats

Correct Answer: 2. metadata

Explanation :-

The metadata command provides information about indexed data, including metadata associated with hosts, sources, and sourcetypes. It can be useful for quickly examining data activity without retrieving the full event contents. fieldsummary focuses on fields in the current result set, while stats performs statistical aggregation on events. tstats is a separate high-performance statistical command with specific requirements and use cases. When an administrator needs information about data sources and their activity at the metadata level, metadata is the appropriate command.

Question 363. A search needs to determine the earliest and latest event timestamps for each host while also preserving the individual events for additional calculations. Which command should be used?

1. stats earliest(_time) latest(_time) by host
2. eventstats earliest(_time) latest(_time) by host
3. timechart earliest(_time) latest(_time) by host
4. streamstats earliest(_time) latest(_time) by host

Correct Answer: 2. eventstats earliest(_time) latest(_time) by host

Explanation :-

The eventstats command calculates aggregate statistics and adds the results back to the individual events. Therefore, eventstats earliest(_time) latest(_time) by host allows every event to retain its original fields while also receiving the earliest and latest timestamps for its host. stats would collapse the events into grouped summary rows. timechart is intended for time-based statistical reporting, while streamstats calculates running statistics according to event order. eventstats is useful when group-level context needs to be compared with each individual event.

Question 364. An analyst needs to calculate a running average of response_time separately for each application as events are processed in sequence. Which command is most appropriate?

1. eventstats avg(response_time) by application
2. stats avg(response_time) by application
3. streamstats avg(response_time) by application
4. timechart avg(response_time) by application

Correct Answer: 3. streamstats avg(response_time) by application

Explanation :-

The streamstats command calculates statistics incrementally as events pass through the search pipeline. Using streamstats avg(response_time) by application creates a running average for each application based on the events processed up to that point. stats calculates a final aggregate and does not preserve the sequential running calculation. eventstats calculates group-level statistics and adds them to events, while timechart organizes statistics into time buckets. Running statistics are useful for monitoring how a metric evolves as additional events are processed.

Question 365. A search contains a multivalue field roles, and the analyst needs to find whether any value contains the word admin using a regular expression. Which function is appropriate?

1. mvcount()
2. mvfind()
3. mvindex()
4. mvjoin()

Correct Answer: 2. mvfind()

Explanation :-

The mvfind() function searches a multivalue field for a value that matches a specified regular expression. It returns the index of the matching value when a match is found, making it useful for determining whether a multivalue field contains a value matching a particular pattern. mvcount() returns the number of values, mvindex() retrieves values by position, and mvjoin() combines values into a single string. mvfind() is therefore appropriate when an analyst needs to locate a matching element within a multivalue field without expanding the values into separate events.

Question 366. An analyst needs to apply the same calculation to every value in a multivalue field and produce a new multivalue result. Which SPL function is designed for this purpose?

1. mvmap()
2. mvexpand
3. mvzip()
4. mvcount()

Correct Answer: 1. mvmap()

Explanation :-

The mvmap() function applies an expression to each value in a multivalue field and returns the resulting values as a multivalue field. It is useful when each element requires the same transformation, such as arithmetic, string manipulation, or another supported expression. mvexpand instead creates separate events for multivalue elements. mvzip() combines corresponding elements from two multivalue fields, while mvcount() returns the number of elements. mvmap() is particularly valuable when the analyst wants to transform multivalue data while keeping the results within the same event.

Question 367. Two multivalue fields contain corresponding values that need to remain paired during processing. Which SPL function can combine the fields element by element?

1. mvexpand()
2. mvjoin()
3. mvzip()
4. mvmap()

Correct Answer: 3. mvzip()

Explanation :-

The mvzip() function combines two multivalue fields by pairing values according to their positions. This allows related information from separate multivalue fields to remain associated. For example, a multivalue field containing users can be paired with another containing their corresponding roles. mvexpand() creates separate events, mvjoin() combines values into a single string, and mvmap() applies an expression to each value of a multivalue field. mvzip() is therefore useful when positional relationships between two multivalue fields need to be preserved during subsequent SPL processing.

Question 368. A search needs to retrieve only events where the status field is either 200 or 201. Which search expression is appropriate?

1. status=200 AND status=201
2. status IN (200,201)
3. status=200 OR status=201
4. status!=200 OR status!=201

Correct Answer: 3. status=200 OR status=201

Explanation :-

The Boolean OR operator allows a search to match either of two conditions. Therefore, status=200 OR status=201 returns events where the status field has either value. Using AND would require both mutually exclusive values to be true for the same field, which is not the intended condition. A negated expression such as status!=200 OR status!=201 would not correctly express the requirement and can produce overly broad results. Explicit Boolean conditions are useful when filtering a field against a small set of permitted values.

Question 369. An analyst wants to filter events where bytes_out is greater than 10000 and status is equal to 200. Which Boolean expression should be used?

1. bytes_out > 10000 OR status=200
2. bytes_out > 10000 AND status=200
3. bytes_out < 10000 AND status!=200
4. bytes_out=10000 OR status!=200

Correct Answer: 2. bytes_out > 10000 AND status=200

Explanation :-

The AND operator requires both conditions to be true for an event to match. Therefore, bytes_out > 10000 AND status=200 retains only events where the outgoing byte count exceeds 10,000 and the status is exactly 200. Using OR would include events satisfying either condition and therefore produce a broader result set. The other expressions represent different conditions entirely. Boolean operators are fundamental to SPL filtering because they allow analysts to combine multiple requirements into a single search expression.

Question 370. A search needs to return events from the web index where the host field begins with web-prod. Which search expression is appropriate?

1. index=web host=”web-prod”
2. index=web host=web-prod*
3. index=web host=*web-prod
4. index=web host=”*web-prod”

Correct Answer: 2. index=web host=web-prod*

Explanation :-

The wildcard * can be used in field-value search expressions to represent additional characters. host=web-prod* matches host values beginning with web-prod, while index=web restricts the search to the specified index. A wildcard placed at the beginning, such as *web-prod, would instead match values ending with that pattern. Quoting a wildcard expression can change how it is interpreted and is not necessary for this straightforward field search. Wildcard searches are useful when hostnames, source names, or other field values follow a predictable naming convention.

Question 371. An analyst needs to search for events where the user field exists, regardless of its specific value. Which SPL search expression is appropriate?

1. user=*
2. user!=*
3. user=””
4. user=NULL

Correct Answer: 1. user=*

Explanation :-

The expression user=* is commonly used in Splunk search syntax to match events where the specified field exists. It does not require a particular value, so events can contain any value in the user field. user!=* does not express the desired existence condition. An empty-string comparison checks for a particular value rather than general field existence, and NULL is not the standard wildcard syntax for this purpose. Field-existence searches are useful when analysts need to restrict results to events that contain a required field before performing additional processing.

Question 372. A search needs to remove duplicate events based on session_id, but the analyst wants to retain the most recent event for each session. What should be done before dedup session_id?

1. sort _time
2. sort -_time
3. reverse
4. tail

Correct Answer: 2. sort -_time

Explanation :-

The dedup command retains the first result encountered for each unique combination of the specified fields. Therefore, if the most recent event must be retained, the results should first be sorted with the newest timestamps first using sort -_time. After that, dedup session_id encounters the newest event first and removes subsequent duplicates for that session. Sorting in ascending order would instead place the oldest event first. reverse only reverses the current order and tail limits results. Understanding result order is essential when using dedup to retain a specific occurrence.

Question 373. An analyst wants to calculate the percentage of events with status=404 out of all events in the result set. Which stats expression is appropriate?

1. stats count(eval(status=404)) as errors count as total
2. stats avg(status=404) as errors
3. stats values(status=404) as errors
4. stats dc(status=404) as errors

Correct Answer: 1. stats count(eval(status=404)) as errors count as total

Explanation :-

The count(eval(…)) pattern allows stats to count only events satisfying a specified condition. count(eval(status=404)) as errors counts events with status 404, while count as total counts all events. The analyst can then use eval to calculate the percentage as errors/total*100. avg() is not the appropriate mechanism for counting conditional events, and values() and dc() provide distinct values or distinct counts rather than the desired conditional event count. This pattern is useful for calculating error rates, success percentages, and other conditional proportions.

Question 374. A search needs to calculate the average response time for each host and then return only hosts whose average is greater than 500 milliseconds. Which SPL pipeline is appropriate?

1. stats avg(response_time) as avg_time by host | where avg_time > 500
2. stats avg(response_time) as avg_time by host | search response_time > 500
3. eventstats avg(response_time) by host | head avg_time > 500
4. stats response_time by host | where avg_time > 500

Correct Answer: 1. stats avg(response_time) as avg_time by host | where avg_time > 500

Explanation :-

The first command calculates the average response time for each host and names the resulting field avg_time. The following where command evaluates that calculated field and keeps only rows where the average exceeds 500 milliseconds. Searching on the original response_time field after aggregation would not correctly test the calculated average. eventstats would preserve individual events and is unnecessary when only grouped results are required. This pattern is a standard way to filter aggregate results based on a threshold derived from a statistical calculation.

Question 375. An analyst wants to count events by action and then display the most frequent actions first. Which SPL pipeline is appropriate?

1. stats count by action | sort count
2. stats count by action | sort -count
3. stats count by action | reverse count
4. stats count by action | sort action

Correct Answer: 2. stats count by action | sort -count

Explanation :-

The stats count by action command creates one result for each action with its corresponding event count. Prefixing count with a minus sign in sort -count orders those results from the largest count to the smallest. sort count would order them in ascending order. Sorting by action would arrange them alphabetically rather than by frequency, and reverse is not the appropriate way to specify a numeric field sort. This pattern is useful when identifying the most common actions, events, errors, requests, or other categorical values.

Question 376. A search needs to calculate the total number of bytes transferred by each user using both bytes_in and bytes_out values. Which SPL approach is appropriate?

1. stats sum(bytes_in + bytes_out) by user
2. eval total_bytes=bytes_in+bytes_out | stats sum(total_bytes) by user
3. stats avg(bytes_in,bytes_out) by user
4. eventstats bytes_in+bytes_out by user

Correct Answer: 2. eval total_bytes=bytes_in+bytes_out | stats sum(total_bytes) by user

Explanation :-

The calculation first needs to occur at the event level because each event has separate bytes_in and bytes_out fields. eval total_bytes=bytes_in+bytes_out creates the combined byte count for each event. The following stats sum(total_bytes) by user then adds those event-level totals for each user. This approach clearly separates row-level calculation from group-level aggregation. It is useful when a metric is composed of multiple fields before being summed across a grouping such as user, host, application, or session.

Question 377. A search needs to calculate the number of unique destination ports contacted by each source IP address. Which SPL expression is appropriate?

1. stats count(destination_port) by source_ip
2. stats values(destination_port) by source_ip
3. stats dc(destination_port) by source_ip
4. stats list(destination_port) by source_ip

Correct Answer: 3. stats dc(destination_port) by source_ip

Explanation :-

The dc() function calculates the distinct count of a field. Therefore, stats dc(destination_port) by source_ip returns the number of unique destination ports associated with each source IP. count() counts occurrences and can include repeated ports. values() returns the distinct port values themselves, while list() collects values and can retain duplicates. Distinct counting is useful in security analysis for identifying hosts contacting many different ports, users accessing numerous resources, or other patterns where the number of unique entities is more important than total event volume.

Question 378. A search needs to calculate the first and last observed values of status according to the current result order for each user. Which statistical functions should be used?

1. earliest(status) and latest(status)
2. min(status) and max(status)
3. first(status) and last(status)
4. start(status) and end(status)

Correct Answer: 3. first(status) and last(status)

Explanation :-

The first() and last() statistical functions return the first and last values according to the order of the results entering the aggregation. This differs from earliest() and latest(), which are designed to identify values associated with chronological extremities based on time. min() and max() identify the smallest and largest values according to their data ordering, which is not necessarily the first and last observed values. When the requirement explicitly refers to result order, first() and last() are the appropriate functions. Analysts should ensure that the search results are ordered correctly before using them.

Question 379. An analyst wants to calculate a cumulative sum of bytes_out separately for each user as events are processed. Which SPL command is appropriate?

1. stats sum(bytes_out) by user
2. eventstats sum(bytes_out) by user
3. streamstats sum(bytes_out) by user
4. timechart sum(bytes_out) by user

Correct Answer: 3. streamstats sum(bytes_out) by user

Explanation :-

The streamstats command calculates running statistics as events are processed. Using streamstats sum(bytes_out) by user produces a cumulative byte total for each user, with the total increasing as additional events are encountered. stats sum() calculates only a final grouped total and does not provide a running value on each event. eventstats adds a final aggregate back to events, while timechart creates time-based statistical results. Running cumulative values are useful when analyzing progressive usage, transfer volume, counters, or other measurements where the sequence of events matters.

Question 380. A search contains an extracted field ticket_id that is embedded inside raw event text. The analyst needs to extract the identifier using a named regular-expression capture group. Which SPL command should be used?

1. regex
2. rex
3. spath
4. replace

Correct Answer: 2. rex

Explanation :-

The rex command supports regular-expression extraction using named capture groups. An analyst can apply a pattern to _raw or another field and assign the captured value to a new field such as ticket_id. The regex command is primarily used to filter events based on whether a field matches a pattern. spath is designed for structured data such as JSON, while replace changes string values. Named captures make rex particularly useful for extracting identifiers, usernames, domains, ticket numbers, and other structured elements embedded in unstructured log messages.