![]() So the pattern for finding incomplete transactions would generally be: … | transaction keepevicted=true | search closed_txn=0 Transactions that fulfill all the requirements are marked as complete by having the field closed_txn set to 1 (rather than 0 for incomplete transactions). Evicted transactions are sets of events that do not match all the transaction parameters.įor example, the time requirements are not met in an evicted transaction. Normally incomplete transactions are not returned, but you can ask for these “evicted” partial transactions by specifying the parameter keepevicted=true. The transaction command creates an internal boolean field named closed_txn to indicate if a given transaction is complete or not. You would like to build a report that shows incomplete transactions-users who have logged in but not logged out. Suppose you are searching for user sessions starting with a login and ending with a logout: … | transaction userid startswith=”login” endswith=”logout” You need to report on incomplete transactions, such as users who have logged in but not logged out. Prepare yourself for the industry by going through Top Splunk Interview Questions and Answers now! Finding Incomplete Transactions | eval field_Z = coalesce(field_A, field_B) You can then build the transaction based on the value of field_Z. If sourcetype A only contains field_A and sourcetype B only contains field_B, create a new field called field_Z which is either field_A or field_B, depending on which is present in an event. Typically, you can join transactions with common fields like: … | transaction usernameīut when the username identifier is called different names (login, name, user, owner, and so on) in different data sources, you need to normalize the field names. You need to build transactions from multiple data sources that use different field names for the same identifier. This search retrieves only the events it needs to and is much more efficient. If all your events have the same IP value, this search should be: sourcetype=x ip=1.2.3.4 | transaction field=ip maxpause=15s Here we are retrieving all events of sourcetype=x, building up transactions, and then throwing away any that don’t have an ip=1.2.3.4. Consider this search: sourcetype=x | transaction field=ip maxpause=15s | search ip=1.2.3.4 No matter what search commands you use, it’s imperative for performance that you make the base search as specific as possible. If instead of an end condition, trade_id values are not reused within 10 minutes, the most viable solution is: … | transaction trade_id maxpause=10m | chart count by durationįinally, a brief word about performance. However, if trade_id values are reused but the last event of each trade is indicated by the text “END”, the only viable solution is: … | transaction trade_id endswith=END | chart count by duration … | stats range(_time) as duration by trade_id Often there is a unique identifier, and stats can be used.įor example, to compute statistics on the duration of trades identified by the unique identifier trade_id, the following searches yield the same answer: … | transaction trade_id
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