#SPLUNK TRANSACTION TIME DOWNLOAD#
To try this example on your own Splunk instance, you must download the sample data and follow the instructions to get the tutorial data into Splunk. Transaction search example This example uses the sample data from the Search Tutorial but should work with any format of Apache web access log. To learn more, see Identify and group events into transactions in this manual. For example, an out of memory problem could trigger several database events to be logged, and they can all be grouped together into a transaction. One common use of a transaction search is to group multiple events into a single meta-event that represents a single physical event. Use the transaction command to define a transaction or override transaction options specified in nf.
Any number of data sources can generate transactions over multiple log entries.Ī transaction search is useful for a single observation of any physical event stretching over multiple logged events. A transaction type is a configured transaction, saved as a field and used in conjunction with the transaction command.
#SPLUNK TRANSACTION TIME SERIES#
Then it's a simple stats command that aggregates the events together, collecting start and end time and then the simple duration calculation at the end.A transaction is any group of conceptually-related events that spans time, such as a series of events related to the online reservation of a hotel room by a single customer, or a set of events related to a firewall intrusion incident. I am parsing the start and end time from the EVENT_MESSAGE and then using the date of the event to calculate the time, to allow for wrapping over midnight. In the above almost all apart from the last two lines are setting up your data. There are plenty of memory and timing issues to consider with transaction that can make life difficult. I encourage you to avoid the idea of using transaction as stats will give you fewer headaches. | stats values(start_time) as start_time values(end_time) as end_time by SOURCE sourcetype PLATFORM SERVICE co_id | eval end_time=strptime(date." ".end_time, "%F %T.%Q") | eval start_time=strptime(date." ".start_time, "%F %T.%Q") | rex field=EVENT_MESSAGE "Processing completed for event with correlationId: (?\w+), at: (?\d+:\d+:\d+\.\d+)" | rex field=EVENT_MESSAGE "Processing event with correlationId: (?\w+) at: (?\d+:\d+:\d+\.\d+)" However, the simple math/rex option is the easiest is a working example of your data and using stats to find duration | makeresults stats is generally faster and has fewer issues. If you are using the 'transaction' command, then that has its own set of issues to consider and it's always good to try to avoid using transaction.
This handles the day wrap and the 'event_is_X' construct is simply your way to determine if this is the start or end event. | stats values(start) as start values(end) as end by Id If each event has a common ID then the simplest thing to do is to | eval start=if(event_is_A,millis,null) The question is - how have you established the two events (A and B) as being the ones used to establish the duration. You can convert the values to time integer values with | eval t1=strptime(time1, "%H:%M:%S.%Q")īut that will then give t1 as a representation of 'today' and that time including any time zone relevance, so if you have two times whereĪnother option is to simply rex the field like this | rex field=time_field "(?*):(?*):(?*)\.(?\d+)"
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