{"id":21675,"date":"2026-09-25T06:50:10","date_gmt":"2026-09-25T06:50:10","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=21675"},"modified":"2026-09-25T06:50:10","modified_gmt":"2026-09-25T06:50:10","slug":"splunk-splk-5002-practice-test-questions-and-exam-dumps-part-8-q141-160","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/splunk-splk-5002-practice-test-questions-and-exam-dumps-part-8-q141-160\/","title":{"rendered":"Splunk SPLK-5002 Practice Test Questions and Exam Dumps Part 8 Q141-160"},"content":{"rendered":"

View Full <\/b>Splunk SPLK-5002 Exam Dumps<\/b><\/a> and Practice Test Dumps<\/b><\/h2>\n

 <\/p>\n

Question 141: Which SPL command can calculate the total number of events for each <\/b>sourcetype<\/b>?<\/b><\/p>\n

    \n
  1. <\/b> count sourcetype<\/span><\/li>\n
  2. <\/b> stats count by sourcetype<\/span><\/li>\n
  3. <\/b> stats total(sourcetype)<\/span><\/li>\n
  4. <\/b> eventstats sourcetype count<\/span><\/li>\n<\/ol>\n

    Correct Answer: 2. <\/b>stats count by sourcetype<\/b><\/p>\n

    Explanation :-<\/b><\/p>\n

    The <\/span>stats count by sourcetype<\/span> command counts matching events and groups the results according to the <\/span>sourcetype<\/span> field. This is useful for understanding the distribution of data sources in a Splunk environment. Each distinct sourcetype receives its own result row with an associated event count. The other choices either use invalid syntax or attempt to aggregate the field itself rather than count events. <\/span>stats<\/span> is commonly used for summary reporting, and the <\/span>by<\/span> clause determines how the events are grouped before the statistical calculation is performed.<\/span><\/p>\n

    Question 142: Which SPL command can filter events where <\/b>status<\/b> is not equal to 200?<\/b><\/p>\n

      \n
    1. <\/b> where status != 200<\/span><\/li>\n
    2. <\/b> filter status <> 200<\/span><\/li>\n
    3. <\/b> search status NOT 200<\/span><\/li>\n
    4. <\/b> exclude status=200<\/span><\/li>\n<\/ol>\n

      Correct Answer: 1. <\/b>where status != 200<\/b><\/p>\n

      Explanation :-<\/b><\/p>\n

      The <\/span>where<\/span> command evaluates expressions and retains events that satisfy the specified condition. <\/span>where status != 200<\/span> keeps events whose <\/span>status<\/span> value is not 200. This can be useful when investigating errors, redirects, or other responses that differ from a successful HTTP status. The <\/span>!=<\/span> comparison operator expresses inequality in SPL expressions. The other choices do not use the standard SPL syntax for this comparison. When filtering text values, appropriate quoting and field-value handling should also be considered depending on the data type.<\/span><\/p>\n

      Question 143: Which SPL command can calculate the number of unique <\/b>source_ip<\/b> values for each <\/b>destination_port<\/b>?<\/b><\/p>\n

        \n
      1. <\/b> stats count(source_ip) by destination_port<\/span><\/li>\n
      2. <\/b> stats dc(source_ip) by destination_port<\/span><\/li>\n
      3. <\/b> stats unique(source_ip) by destination_port<\/span><\/li>\n
      4. <\/b> stats distinct(source_ip) destination_port<\/span><\/li>\n<\/ol>\n

        Correct Answer: 2. <\/b>stats dc(source_ip) by destination_port<\/b><\/p>\n

        Explanation :-<\/b><\/p>\n

        The <\/span>dc()<\/span> function calculates a distinct count. Therefore, <\/span>stats dc(source_ip) by destination_port<\/span> returns the number of unique source IP addresses associated with each destination port. This is useful in security analysis when determining how many different systems are communicating with a particular service. A normal <\/span>count(source_ip)<\/span> would count events rather than unique IP addresses, so repeated connections from the same IP could inflate the result. The other choices use functions that are not the standard SPL approach for calculating a distinct count.<\/span><\/p>\n

        Question 144: Which SPL command can add the average <\/b>response_time<\/b> for each host to every event from that host?<\/b><\/p>\n

          \n
        1. <\/b> stats avg(response_time) by host<\/span><\/li>\n
        2. <\/b> streamstats avg(response_time) by host<\/span><\/li>\n
        3. <\/b> eventstats avg(response_time) as host_avg by host<\/span><\/li>\n
        4. <\/b> eval host_avg=avg(response_time)<\/span><\/li>\n<\/ol>\n

          Correct Answer: 3. <\/b>eventstats avg(response_time) as host_avg by host<\/b><\/p>\n

          Explanation :-<\/b><\/p>\n

          The <\/span>eventstats<\/span> command calculates an aggregate and adds the resulting value back to the events used in the calculation. <\/span>eventstats avg(response_time) as host_avg by host<\/span> calculates an average for each host and places that value in the <\/span>host_avg<\/span> field on the corresponding events. This allows individual events to be compared against their host-level average while preserving the original events. <\/span>stats<\/span> would instead transform the results into summary rows. <\/span>streamstats<\/span> calculates running statistics based on event order, which is different from a complete group-level average.<\/span><\/p>\n

          Question 145: Which SPL command can group events into five-minute time intervals by modifying the <\/b>_time<\/b> field?<\/b><\/p>\n

            \n
          1. <\/b> bucket _time span=5m<\/span><\/li>\n
          2. <\/b> group _time interval=5m<\/span><\/li>\n
          3. <\/b> timebucket _time 5m<\/span><\/li>\n
          4. <\/b> binning _time span=5m<\/span><\/li>\n<\/ol>\n

            Correct Answer: 1. <\/b>bucket _time span=5m<\/b><\/p>\n

            Explanation :-<\/b><\/p>\n

            The <\/span>bucket<\/span> command discretizes values into groups. When applied to <\/span>_time<\/span>, <\/span>bucket _time span=5m<\/span> groups event timestamps into five-minute intervals. This is useful when a search needs explicit time buckets before applying another statistical command, such as <\/span>stats count by _time<\/span>. The <\/span>timechart<\/span> command can also perform time bucketing automatically, but <\/span>bucket<\/span> provides direct control over the <\/span>_time<\/span> field. The other choices are not standard SPL syntax. Time bucketing is commonly used when building custom time-based summaries or comparisons.<\/span><\/p>\n

            Question 146: Which SPL command can return the top 10 users based on event frequency?<\/b><\/p>\n

              \n
            1. <\/b> top limit=10 user<\/span><\/li>\n
            2. <\/b> stats top=10 user<\/span><\/li>\n
            3. <\/b> head user limit=10<\/span><\/li>\n
            4. <\/b> rank user 10<\/span><\/li>\n<\/ol>\n

              Correct Answer: 1. <\/b>top limit=10 user<\/b><\/p>\n

              Explanation :-<\/b><\/p>\n

              The <\/span>top<\/span> command identifies the most frequent values of a specified field. <\/span>top limit=10 user<\/span> returns the ten users with the highest frequency in the matching events. The command provides frequency-related information that can be used to understand dominant activity patterns. <\/span>head<\/span> only limits the number of existing results and does not rank values by frequency. The other choices do not use valid SPL syntax for this operation. <\/span>top<\/span> is particularly useful for quickly identifying frequently occurring users, source IP addresses, URLs, or other categorical fields.<\/span><\/p>\n

              Question 147: Which SPL command can combine two fields into a new field containing both values?<\/b><\/p>\n

                \n
              1. <\/b> eval combined=host + user<\/span><\/li>\n
              2. <\/b> stats combined=host.user<\/span><\/li>\n
              3. <\/b> merge combined=host,user<\/span><\/li>\n
              4. <\/b> combine host,user as combined<\/span><\/li>\n<\/ol>\n

                Correct Answer: 1. <\/b>eval combined=host + user<\/b><\/p>\n

                Explanation :-<\/b><\/p>\n

                The <\/span>eval<\/span> command can create a new field from existing fields using expressions. When working with string fields, concatenation can be performed using the appropriate SPL expression and functions. For example, <\/span>eval combined=host . “-” . user<\/span> can create a combined value such as <\/span>server01-admin<\/span>. The important point is that <\/span>eval<\/span> is the command used to derive a new field from existing values. <\/span>stats<\/span> is intended for aggregation, while the other choices are not standard SPL commands for creating a combined field.<\/span><\/p>\n

                Question 148: Which SPL command can filter events using a regular expression against the <\/b>user<\/b> field?<\/b><\/p>\n

                  \n
                1. <\/b> rex user=”^admin”<\/span><\/li>\n
                2. <\/b> regex user=”^admin”<\/span><\/li>\n
                3. <\/b> regexp user=”^admin”<\/span><\/li>\n
                4. <\/b> search regex(user,”^admin”)<\/span><\/li>\n<\/ol>\n

                  Correct Answer: 2. <\/b>regex user=”^admin”<\/b><\/p>\n

                  Explanation :-<\/b><\/p>\n

                  The <\/span>regex<\/span> command filters events using a regular expression applied to a specified field. <\/span>regex user=”^admin”<\/span> keeps events where the <\/span>user<\/span> field matches the pattern beginning with <\/span>admin<\/span>. The <\/span>rex<\/span> command has a different primary purpose: extracting or transforming data with regular expressions. This distinction is important because <\/span>regex<\/span> controls which events remain in the result set, while <\/span>rex<\/span> can create extracted fields. The other choices do not represent the standard SPL syntax for regular-expression filtering. Regular expressions are useful for matching structured naming patterns and other textual conditions.<\/span><\/p>\n

                  Question 149: Which SPL command can calculate the median value of <\/b>response_time<\/b> for each application?<\/b><\/p>\n

                    \n
                  1. <\/b> stats median(response_time) by application<\/span><\/li>\n
                  2. <\/b> stats middle(response_time) by application<\/span><\/li>\n
                  3. <\/b> stats med(response_time) by application<\/span><\/li>\n
                  4. <\/b> stats center(response_time) by application<\/span><\/li>\n<\/ol>\n

                    Correct Answer: 1. <\/b>stats median(response_time) by application<\/b><\/p>\n

                    Explanation :-<\/b><\/p>\n

                    The <\/span>median()<\/span> statistical function calculates the middle value of a set of numeric observations. <\/span>stats median(response_time) by application<\/span> calculates the median response time separately for each application. Median values can be useful when response-time data contains outliers because the median is less influenced by extremely high or low values than the average. The other choices use function names that are not the standard SPL syntax for this calculation. Combining median with other statistics such as average, minimum, maximum, or percentiles can provide a more complete view of application performance.<\/span><\/p>\n

                    Question 150: Which SPL command can retain only events whose <\/b>severity<\/b> field is greater than or equal to 4?<\/b><\/p>\n

                      \n
                    1. <\/b> where severity >= 4<\/span><\/li>\n
                    2. <\/b> stats severity >= 4<\/span><\/li>\n
                    3. <\/b> filter severity >= 4<\/span><\/li>\n
                    4. <\/b> search severity greater 4<\/span><\/li>\n<\/ol>\n

                      Correct Answer: 1. <\/b>where severity >= 4<\/b><\/p>\n

                      Explanation :-<\/b><\/p>\n

                      The <\/span>where<\/span> command evaluates Boolean expressions and keeps results that meet the specified condition. <\/span>where severity >= 4<\/span> therefore retains events where the numeric <\/span>severity<\/span> value is four or higher. This is useful for focusing investigations on high-severity events. Depending on the search structure, an equivalent field comparison can sometimes be placed directly in the initial search. The other choices either use invalid syntax or commands that are not standard SPL filtering commands. Numeric comparisons should be used carefully when field values may contain nonnumeric strings.<\/span><\/p>\n

                      Question 151: Which SPL command can calculate a count and average response time for each <\/b>host<\/b>?<\/b><\/p>\n

                        \n
                      1. <\/b> stats count, avg(response_time) by host<\/span><\/li>\n
                      2. <\/b> stats host count average(response_time)<\/span><\/li>\n
                      3. <\/b> eventstats count avg(response_time) host<\/span><\/li>\n
                      4. <\/b> count avg(response_time) by host<\/span><\/li>\n<\/ol>\n

                        Correct Answer: 1. <\/b>stats count, avg(response_time) by host<\/b><\/p>\n

                        Explanation :-<\/b><\/p>\n

                        The <\/span>stats<\/span> command supports multiple aggregation functions in one search. <\/span>stats count, avg(response_time) by host<\/span> produces one row for each host and includes both the number of matching events and the average response time. This combination is useful when comparing workload volume and performance across systems. The <\/span>by host<\/span> clause applies the calculations separately to each host. The other choices use invalid or incomplete syntax. Additional statistical functions, such as <\/span>max()<\/span> or <\/span>p95()<\/span>, can also be added when more detailed performance information is required.<\/span><\/p>\n

                        Question 152: Which SPL command can extract a username from raw text such as <\/b>user=alice<\/b>?<\/b><\/p>\n

                          \n
                        1. <\/b> regex field=_raw “user=(?<username>\\w+)”<\/span><\/li>\n
                        2. <\/b> rex field=_raw “user=(?<username>\\w+)”<\/span><\/li>\n
                        3. <\/b> search field=_raw “user=(?<username>\\w+)”<\/span><\/li>\n
                        4. <\/b> extract field=_raw username<\/span><\/li>\n<\/ol>\n

                          Correct Answer: 2. <\/b>rex field=_raw “user=(?<username>\\w+)”<\/b><\/p>\n

                          Explanation :-<\/b><\/p>\n

                          The <\/span>rex<\/span> command uses regular expressions to extract information from a field. The named capture group <\/span>(?<username>\\w+)<\/span> creates a new field called <\/span>username<\/span> containing the characters matched after <\/span>user=<\/span>. This is useful when structured information exists only inside raw event text. The <\/span>regex<\/span> command would instead filter events based on whether the pattern matches. The other choices do not provide the appropriate syntax for named-field extraction. <\/span>rex<\/span> can be used against <\/span>_raw<\/span> or another specified field depending on where the desired information is stored.<\/span><\/p>\n

                          Question 153: Which SPL command can display the first 25 results from the current result set?<\/b><\/p>\n

                            \n
                          1. <\/b> limit 25<\/span><\/li>\n
                          2. <\/b> head 25<\/span><\/li>\n
                          3. <\/b> first 25<\/span><\/li>\n
                          4. <\/b> top 25<\/span><\/li>\n<\/ol>\n

                            Correct Answer: 2. <\/b>head 25<\/b><\/p>\n

                            Explanation :-<\/b><\/p>\n

                            The <\/span>head<\/span> command limits the search results to the first specified number of events. Therefore, <\/span>head 25<\/span> returns the first 25 results according to the current result order. It is useful for quickly inspecting a sample of events or limiting the amount of data processed by subsequent commands. <\/span>top<\/span> has a different purpose: it identifies the most frequent values of a field. The other choices are not the standard SPL commands for limiting results to the first 25 events. The ordering of the results determines which events are considered the first results.<\/span><\/p>\n

                            Question 154: Which SPL command can return the last 10 results from the current result set?<\/b><\/p>\n

                              \n
                            1. <\/b> head -10<\/span><\/li>\n
                            2. <\/b> tail 10<\/span><\/li>\n
                            3. <\/b> last 10<\/span><\/li>\n
                            4. <\/b> recent 10<\/span><\/li>\n<\/ol>\n

                              Correct Answer: 2. <\/b>tail 10<\/b><\/p>\n

                              Explanation :-<\/b><\/p>\n

                              The <\/span>tail<\/span> command returns the final results from the current search result set. <\/span>tail 10<\/span> therefore returns the last ten results in the current ordering. This can be useful when inspecting the end of an ordered result set or when the newest events appear at the end of the results. <\/span>head<\/span> performs the opposite operation by returning the first results. The other choices are not the standard SPL commands for this task. Always consider how the results have been ordered before interpreting the events returned by <\/span>tail<\/span>.<\/span><\/p>\n

                              Question 155: Which SPL command can count events by <\/b>status<\/b> and then display only statuses with more than 50 events?<\/b><\/p>\n

                                \n
                              1. <\/b> stats count by status | where count > 50<\/span><\/li>\n
                              2. <\/b> count by status | filter count > 50<\/span><\/li>\n
                              3. <\/b> stats status count | having count > 50<\/span><\/li>\n
                              4. <\/b> top status | where status > 50<\/span><\/li>\n<\/ol>\n

                                Correct Answer: 1. <\/b>stats count by status | where count > 50<\/b><\/p>\n

                                Explanation :-<\/b><\/p>\n

                                The search first uses <\/span>stats count by status<\/span> to calculate an event count for each status value. The pipe sends those summary rows to <\/span>where count > 50<\/span>, which filters the aggregated results and retains only statuses whose count exceeds 50. This pattern is useful for threshold-based analysis after aggregation. The <\/span>where<\/span> command can evaluate fields created by previous commands, including statistical fields created by <\/span>stats<\/span>. The other options either use invalid syntax or attempt to compare the wrong field.<\/span><\/p>\n

                                Question 156: Which SPL command can calculate the total bytes transferred by each user?<\/b><\/p>\n

                                  \n
                                1. <\/b> stats sum(bytes) by user<\/span><\/li>\n
                                2. <\/b> stats total(bytes) user<\/span><\/li>\n
                                3. <\/b> sum bytes grouped user<\/span><\/li>\n
                                4. <\/b> eventstats bytes by user<\/span><\/li>\n<\/ol>\n

                                  Correct Answer: 1. <\/b>stats sum(bytes) by user<\/b><\/p>\n

                                  Explanation :-<\/b><\/p>\n

                                  The <\/span>sum()<\/span> statistical function adds numeric values, and the <\/span>by user<\/span> clause groups the calculation by user. Therefore, <\/span>stats sum(bytes) by user<\/span> returns the total number of bytes associated with each user in the matching events. This can be useful for traffic analysis, bandwidth reporting, or identifying users generating large amounts of data transfer. The other choices either use invalid syntax or do not perform the requested aggregation. Additional fields can be included in the grouping when totals need to be broken down by another dimension such as host or application.<\/span><\/p>\n

                                  Question 157: Which SPL command can add a running event count separately for each user?<\/b><\/p>\n

                                    \n
                                  1. <\/b> streamstats count by user<\/span><\/li>\n
                                  2. <\/b> stats count by user<\/span><\/li>\n
                                  3. <\/b> eventstats count by user<\/span><\/li>\n
                                  4. <\/b> runningcount user<\/span><\/li>\n<\/ol>\n

                                    Correct Answer: 1. <\/b>streamstats count by user<\/b><\/p>\n

                                    Explanation :-<\/b><\/p>\n

                                    The <\/span>streamstats<\/span> command can calculate running statistics, and the <\/span>by<\/span> clause allows the calculation to be maintained separately for each group. <\/span>streamstats count by user<\/span> therefore creates a cumulative event count as events are processed for each user. Unlike <\/span>stats count by user<\/span>, which produces a summary row for each user, <\/span>streamstats<\/span> retains individual events and adds the running value to them. This is useful when analyzing the progression of activity over time or within an ordered event sequence. The result depends on the ordering of the events entering the command.<\/span><\/p>\n

                                    Question 158: Which SPL command can remove a field named <\/b>password<\/b> from the output?<\/b><\/p>\n

                                      \n
                                    1. <\/b> fields – password<\/span><\/li>\n
                                    2. <\/b> delete password<\/span><\/li>\n
                                    3. <\/b> remove password<\/span><\/li>\n
                                    4. <\/b> drop password<\/span><\/li>\n<\/ol>\n

                                      Correct Answer: 1. <\/b>fields – password<\/b><\/p>\n

                                      Explanation :-<\/b><\/p>\n

                                      The <\/span>fields<\/span> command can exclude fields from search results by using a minus sign. <\/span>fields – password<\/span> removes the <\/span>password<\/span> field from the resulting output while retaining other fields. This is useful when preparing reports or dashboards and when unnecessary sensitive information should not be displayed. The other commands are not standard SPL syntax for removing a field from the result set. The <\/span>fields<\/span> command can also be used positively to retain only selected fields, making it useful for controlling the final structure of search results.<\/span><\/p>\n

                                      Question 159: Which SPL command can calculate the earliest and latest event for every <\/b>host<\/b>?<\/b><\/p>\n

                                        \n
                                      1. <\/b> stats earliest(_time), latest(_time) by host<\/span><\/li>\n
                                      2. <\/b> timechart earliest latest by host<\/span><\/li>\n
                                      3. <\/b> stats first(_time), last(_time) host<\/span><\/li>\n
                                      4. <\/b> events earliest latest host<\/span><\/li>\n<\/ol>\n

                                        Correct Answer: 1. <\/b>stats earliest(_time), latest(_time) by host<\/b><\/p>\n

                                        Explanation :-<\/b><\/p>\n

                                        The <\/span>stats<\/span> command can calculate both <\/span>earliest(_time)<\/span> and <\/span>latest(_time)<\/span> for each host. The <\/span>by host<\/span> clause ensures that the calculations are performed separately for every host represented in the search results. This can help identify the activity window of individual systems during an investigation. The selected search time range still determines which events are considered. The other choices either use different functions or invalid syntax. Combining earliest and latest timestamps is useful for understanding when a host first and last generated matching activity.<\/span><\/p>\n

                                        Question 160: Which SPL command can present <\/b>user<\/b>, <\/b>host<\/b>, and <\/b>status<\/b> as a final ordered table?<\/b><\/p>\n

                                          \n
                                        1. <\/b> fields user host status<\/span><\/li>\n
                                        2. <\/b> table user host status<\/span><\/li>\n
                                        3. <\/b> select user host status<\/span><\/li>\n
                                        4. <\/b> format user host status<\/span><\/li>\n<\/ol>\n

                                          Correct Answer: 2. <\/b>table user host status<\/b><\/p>\n

                                          Explanation :-<\/b><\/p>\n

                                          The <\/span>table<\/span> command presents specified fields as columns in the order they are listed. <\/span>table user host status<\/span> therefore creates a concise table containing those three fields in that sequence. It is commonly used near the end of a search when the results need to be formatted for reporting or inspection. The <\/span>fields<\/span> command can also control which fields remain, but <\/span>table<\/span> is specifically intended to organize the final output into columns. The other choices are not standard SPL commands for creating this type of final tabular presentation.<\/span><\/p>\n

                                           <\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Splunk SPLK-5002 Exam Dumps and Practice Test Dumps   Question 141: Which SPL command can calculate the total number of events for each sourcetype? count sourcetype stats count by sourcetype stats total(sourcetype) eventstats sourcetype count Correct Answer: 2. stats count by sourcetype Explanation :- The stats count by sourcetype command counts matching events […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1648,1647],"tags":[],"_links":{"self":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/21675"}],"collection":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/comments?post=21675"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/21675\/revisions"}],"predecessor-version":[{"id":21676,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/21675\/revisions\/21676"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=21675"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=21675"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=21675"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}