![]() Description: The name of one or more fields to group by.Description: Specifies how the values in the list() or values() aggregation are delimited.Description: If true, computes numerical statistics on each field if and only if all of the values of that field are numerical.You can use wildcard characters in the field name. Use the AS clause to place the result into a new field with a name that you specify. Description: sparkline aggregation function.You can use wildcard characters in field names. The function can be applied to an eval expression, or to a field or set of fields. Description: statistical aggregation function.The stats command calculates statistics based on the fields in your events.Īccelerate Your career with splunk Training and become expertise in splunk Enroll For Free Splunk Training Demo! If you use a by clause one row is returned for each distinct value specified in the by clause. If stats are used without a by clause only one row is returned, which is the aggregation over the entire incoming result set. When searching events based on time, the first and last functions do not produce accurate results,įor more information about these functions, see Time functions.Calculates aggregate statistics over the results set, such as average, count, and sum. To locate the last value based on time order, use the latest function.To locate the first value based on time order, use the earliest function.When you use the stats and eventstats commands to order events based on time, use the earliest and latest functions. The estdc function can result in significantly lower memory usage and run times. If you are using the distinct_count function without a BY clause field or with a low-cardinality field in the BY clause, consider replacing the distinct_count function with the estdc function (estimated distinct count). When to use the estimated distinct count function You can avoid running into memory issues by filtering out events before you use the eventstats command in your search. The values and list functions also can consume a lot of memory.The distinct_count function requires far more memory than the count function.Some functions are inherently more expensive, from a memory standpoint, than other functions. You can avoid reaching these limit by filtering out events before you use the eventstats command in your search. There is default limit for the number of results returned from a search.If the eventstats command reaches this limit, the command stops adding the requested fields to the search results. There is default limit to the amount of memory that the eventstats command can use to keep track of information when processing a search.There are several default search limitations that might impact using the eventstats command: A new field is added all 4events and the aggregation is added to that field in every event. The aggregation is added to every event, even events that were not used to generate the aggregation.įor example, you have 4 events and 3 of the events have the field you want to aggregate on, the eventstats command generates the aggregation based on the data in the 3 events. The command creates a new field in every event and places the aggregation in that field. ![]() The eventstats command looks for events that contain the field that you want to use to generate the aggregation. You can use the fields in your events in subsequent commands in your search, because the events have not been transformed You can only use the fields in your aggregated results in subsequent commands in the search ![]() The differences between these commands are described in the following table:Įvents are transformed into a table of aggregated search resultsĪggregations are placed into a new field that is added to each of the events in your output You can use both commands to generate aggregations like average, sum, and maximum. The eventstats command is similar to the stats command. The following sections contain information to help you understand and use the eventstats command.
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