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

 

Question 321. An analyst needs to return the top 10 values of a field based on their frequency and include the percentage of the total represented by each value. Which command is most appropriate?

1. stats
2. top
3. eventstats
4. chart

Correct Answer: 2. top

Explanation :-

The top command identifies the most frequently occurring values for one or more fields. It can also provide supporting information such as counts and percentages, making it useful for quickly identifying dominant values in a dataset. The number of returned values can be controlled with options such as limit. stats is a general aggregation command and requires the analyst to construct the desired calculations manually. eventstats adds aggregate information back to events, while chart creates statistical tables. For a straightforward frequency-based ranking of field values, top is designed specifically for this purpose.

Question 322. A search produces a large number of events, but the analyst wants to keep only the first 25 results after all preceding search commands have executed. Which command should be used?

1. head 25
2. tail 25
3. dedup 25
4. limit 25

Correct Answer: 1. head 25

Explanation :-

The head command returns the first events from the current result set. Using head 25 limits the output to the first 25 results after the preceding pipeline has produced its results. tail 25 instead returns the final 25 results, while dedup removes duplicate values rather than simply limiting the number of results. limit is not the standard SPL command for this purpose. Analysts often use head during testing or when only a small sample of results is required. The ordering of the results should be considered because head operates on the result order it receives.

Question 323. A search needs to return only the last 10 results from the current result set. Which SPL command should be used?

1. head 10
2. tail 10
3. reverse 10
4. last 10

Correct Answer: 2. tail 10

Explanation :-

The tail command returns the final events from the current result set. Therefore, tail 10 keeps the last ten results. head 10 performs the opposite operation by returning the first ten results. reverse changes result ordering but does not itself provide a numeric limit in this manner, and last is not the equivalent command for limiting search results. The result ordering should be understood before using tail, because the meaning of “last” depends on how the preceding search has ordered its results. This makes tail useful when examining the most recent or final portion of an ordered result set.

Question 324. An analyst wants to sort results by bytes_out from the largest value to the smallest value and then keep only the first five results. Which SPL pipeline is appropriate?

1. | sort bytes_out | head 5
2. | sort -bytes_out | head 5
3. | sort +bytes_out | tail 5
4. | sort -count | tail 5

Correct Answer: 2. | sort -bytes_out | head 5

Explanation :-

In SPL, a minus sign before a field in the sort command specifies descending order. Therefore, sort -bytes_out places the largest bytes_out values first. Applying head 5 afterward retains the five largest results. Using sort bytes_out produces ascending order, while sort +bytes_out explicitly indicates ascending order. tail would select the final results and therefore would not provide the intended top-five values after descending sorting. This pattern is commonly used when an analyst needs to identify the largest values for bandwidth, response size, transaction volume, or similar numeric metrics.

Question 325. A search returns results sorted by _time, but the analyst wants the newest events displayed first. Which command can explicitly sort the results in descending timestamp order?

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

Correct Answer: 2. sort -_time

Explanation :-

The sort command can explicitly order results using a specified field. Prefixing _time with a minus sign requests descending order, so sort -_time places the newest timestamps first. sort _time sorts in ascending order. reverse changes the order of the existing result set rather than explicitly sorting by _time, while head limits results rather than sorting them. Explicit sorting is useful when the desired ordering must be guaranteed regardless of how earlier commands produced the results. It is particularly helpful before applying commands such as head, delta, or other order-sensitive operations.

Question 326. An analyst wants to remove duplicate events based on the combination of user and host, keeping only the first occurrence of each unique combination. Which SPL command is appropriate?

1. dedup user host
2. stats values(user) by host
3. uniq user host
4. distinct user host

Correct Answer: 1. dedup user host

Explanation :-

The dedup command removes duplicate results based on the specified fields. Using dedup user host keeps one result for each unique combination of user and host. The result that is retained depends on the ordering of the events entering the dedup command, so analysts should sort the results first when a particular occurrence needs to be preserved. stats values() produces aggregated results rather than simply removing duplicate events. uniq and distinct are not equivalent SPL commands for this task. dedup is therefore the direct choice for retaining one event per unique field combination.

Question 327. A search needs to calculate both the minimum and maximum response_time for each application. Which SPL command provides both values in one aggregation?

1. eventstats min(response_time) max(response_time) by application
2. stats min(response_time) max(response_time) by application
3. chart response_time by application
4. timechart min(response_time) max(response_time)

Correct Answer: 2. stats min(response_time) max(response_time) by application

Explanation :-

The stats command can calculate multiple statistical aggregations in a single command. stats min(response_time) max(response_time) by application produces one row for each application with both the minimum and maximum response times. eventstats would calculate the values and add them back to the individual events, which is not required when only grouped summary results are needed. chart and timechart provide other table and time-series structures and are not the most direct choice for this requirement. Combining multiple aggregations in stats is efficient when the analyst needs a grouped summary containing several statistics.

Question 328. A search needs to calculate the average bytes_out for each host while also preserving the original events so the average can be compared with each event’s value. Which command should be used?

1. stats avg(bytes_out) by host
2. eventstats avg(bytes_out) by host
3. chart avg(bytes_out) by host
4. timechart avg(bytes_out) by host

Correct Answer: 2. eventstats avg(bytes_out) by host

Explanation :-

The eventstats command calculates aggregate statistics while retaining the original events. Using eventstats avg(bytes_out) by host adds the average value for each host to every corresponding event. This allows the analyst to compare an individual event’s bytes_out with its host-level average. In contrast, stats avg(bytes_out) by host transforms the results into an aggregated table and does not preserve the original events. chart and timechart create other summary structures. eventstats is particularly useful when an aggregate benchmark needs to be used in subsequent event-level calculations or filtering.

Question 329. A security analyst needs to count distinct users associated with each source IP address. Which SPL expression is appropriate?

1. stats count(user) by source_ip
2. stats values(user) by source_ip
3. stats dc(user) by source_ip
4. stats distinct(user) by source_ip

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

Explanation :-

The dc() statistical function calculates the distinct count of a field. Therefore, stats dc(user) by source_ip returns the number of unique users associated with each source IP address. count(user) counts field occurrences and may count the same user multiple times. values(user) returns the distinct values themselves rather than their count. distinct() is not the standard statistical function for this requirement. Distinct counting is useful in security analytics when measuring how many unique users, hosts, IP addresses, or other entities are associated with a particular event attribute.

Question 330. An analyst wants to return all distinct values of the category field for each department. Which statistical function should be used?

1. list(category)
2. values(category)
3. dc(category)
4. count(category)

Correct Answer: 2. values(category)

Explanation :-

The values() statistical function returns the distinct values of a field. Using stats values(category) by department produces the unique categories associated with each department. dc(category) returns only the number of distinct categories, not the actual values. count(category) counts occurrences, which can include repeated values. list(category) preserves the individual values in their result order and can include duplicates. When the requirement is specifically to obtain the unique set of category values for each group, values() is the appropriate function.

Question 331. A search needs to preserve duplicate values and retain their original result order when collecting all status values for each host. Which statistical function is most appropriate?

1. values(status)
2. dc(status)
3. list(status)
4. count(status)

Correct Answer: 3. list(status)

Explanation :-

The list() statistical function collects field values while retaining duplicates and their order as represented in the results. This makes it different from values(), which returns distinct values. dc() provides only a distinct count, and count() returns the number of matching values rather than the actual sequence. list() is useful when the sequence or repeated occurrences of values matter, such as examining a series of statuses, actions, or states associated with a particular host. Analysts should consider the ordering of the input results when interpreting a collected list.

Question 332. An analyst wants to find the number of events in each combination of host and status. Which SPL command is appropriate?

1. stats count by host status
2. stats values(host) by status
3. eventstats count(host) by status
4. chart host status

Correct Answer: 1. stats count by host status

Explanation :-

The stats command can group results by multiple fields. Using stats count by host status creates one row for each unique combination of host and status and calculates the number of events in that group. values(host) by status produces unique host values for each status rather than counts for every host-status combination. eventstats adds statistics back to individual events rather than producing only grouped results. chart has different syntax and output behavior. Grouping by multiple dimensions with stats is a fundamental technique for analyzing event distributions across combinations of fields.

Question 333. A search needs to filter aggregated results so that only hosts with more than 100 events are returned. Which SPL pattern should be used?

1. stats count by host | where count > 100
2. stats count by host | search host > 100
3. stats count by host | filter count > 100
4. stats count by host | dedup count > 100

Correct Answer: 1. stats count by host | where count > 100

Explanation :-

After stats count by host, the resulting dataset contains a field named count representing the number of events for each host. The where command can then evaluate that calculated field and retain only rows where count > 100. A normal search expression is not the appropriate choice for evaluating this type of numeric comparison against an aggregated field. filter is not the equivalent standard SPL command, and dedup removes duplicate values rather than applying numeric conditions. This two-stage pattern is commonly used when filtering results based on calculated statistics.

Question 334. An analyst needs to classify events based on a numeric severity score: scores of 8 or higher should be Critical, scores from 5 through 7 should be High, and lower scores should be Normal. Which SPL function is best suited for this classification?

1. coalesce()
2. case()
3. split()
4. mvindex()

Correct Answer: 2. case()

Explanation :-

The case() evaluation function is useful when multiple conditional rules must be evaluated and different output values returned. An expression can test whether a severity score is greater than or equal to 8, then whether it is greater than or equal to 5, and finally assign Normal to the remaining values. coalesce() selects the first non-null value, while split() and mvindex() operate on string and multivalue data. case() is especially useful for creating classifications, categories, severity labels, and other derived fields based on multiple conditions.

Question 335. A field named duration contains milliseconds, and the analyst wants to create a new field containing the duration in seconds. Which SPL expression is appropriate?

1. eval duration_seconds=duration*1000
2. eval duration_seconds=duration/1000
3. eval duration_seconds=duration+1000
4. eval duration_seconds=duration-1000

Correct Answer: 2. eval duration_seconds=duration/1000

Explanation :-

One second equals 1,000 milliseconds, so converting a duration from milliseconds to seconds requires dividing the value by 1,000. The expression eval duration_seconds=duration/1000 creates a new field containing the converted value. Multiplying by 1,000 would instead convert seconds into milliseconds, while addition or subtraction does not perform a unit conversion. eval is appropriate because it can perform arithmetic operations and create calculated fields. Unit conversion through explicit arithmetic is common in SPL when source data uses different measurement units than the analyst needs for reporting or threshold comparisons.

Question 336. An analyst needs to extract the domain portion from an email address such as user@example.com using a regular expression. Which command is designed for field extraction with regular expressions?

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

Correct Answer: 2. rex

Explanation :-

The rex command performs regular-expression-based field extraction and manipulation. It can use named capture groups to create a new field containing the desired portion of a value, such as the domain from an email address. The regex command is primarily used to filter events based on regular-expression matching rather than create extracted fields. replace changes string values, while spath is intended for structured data such as JSON. When an analyst needs to parse unstructured text using a regular expression and store the captured portion as a field, rex is the appropriate command.

Question 337. A search should keep only events where the user field begins with the prefix admin. Which command is appropriate for applying a regular-expression filter to the field?

1. regex user=”^admin”
2. rex user=”^admin”
3. replace user=”^admin”
4. spath user=”^admin”

Correct Answer: 1. regex user=”^admin”

Explanation :-

The regex command filters events based on a regular expression applied to a specified field. The pattern ^admin anchors the match to the beginning of the field value, so only users whose names start with admin are retained. rex is used primarily for extraction or transformation using regular expressions rather than straightforward event filtering. replace performs substitutions, and spath works with structured data. Regular expressions are useful when simple equality or wildcard matching is insufficient and the analyst needs more precise pattern-based filtering.

Question 338. A search needs to rename src_ip to source_ip and dst_ip to destination_ip without changing the underlying event data. Which command should be used?

1. replace
2. eval
3. rename
4. fields

Correct Answer: 3. rename

Explanation :-

The rename command changes field names in the search results. It can rename multiple fields in the same command, such as rename src_ip AS source_ip dst_ip AS destination_ip. This is useful when normalizing field names across different data sources or preparing results for reporting. replace modifies field values, eval creates or recalculates field values, and fields controls which fields are included or excluded. rename does not change the actual underlying indexed event; it changes how the fields are represented in the current search pipeline.

Question 339. An analyst wants to remove the sensitive password field from the results while retaining all other available fields. Which SPL command should be used?

1. fields password
2. fields – password
3. delete password
4. remove password

Correct Answer: 2. fields – password

Explanation :-

The fields command can explicitly exclude fields by placing a minus sign before the field name. Therefore, fields – password removes the password field from the search results while leaving other fields available. fields password would instead keep only the specified field rather than excluding it. delete and remove are not the standard SPL commands for excluding a field from search results. Excluding unnecessary or sensitive fields can simplify output and reduce the amount of data passed through later stages of a search.

Question 340. A search needs to keep only the fields user, host, status, and _time for the final report. Which SPL command is most appropriate?

1. fields – user host status _time
2. table – user host status _time
3. fields user host status _time
4. rename user host status _time

Correct Answer: 3. fields user host status _time

Explanation :-

The fields command can specify exactly which fields should remain available in the search results. Using fields user host status _time keeps those four fields and excludes other fields from the results at that point in the pipeline. fields – is used for exclusion rather than selection. table can also format results using specified fields, but its primary purpose is to create a tabular presentation of the selected fields. rename changes field names rather than controlling field selection. When the requirement is to retain a specific set of fields for further processing or output, fields is appropriate.