Max exec: The maximum number of times to apply the Regex to the source field when the global flag is set, or when using _NAME_N and _VALUE_N capturing groups. Source field: Field on which to perform regex field extraction. See Examples below.Īdditional regex: Click Add Regex to chain extra regex conditions. Can contain special _NAME_N and _VALUE_N capturing groups, which extract both the name and value of a field, e.g.: (?+)=(?+). Must contain named capturing groups, e.g.: (?bar).

Defaults to empty.įinal: If toggled to Yes, stops feeding data to the downstream Functions. Defaults to true, meaning it evaluates all events.ĭescription: Simple description of the Function.

Usage įilter: Filter expression (JS) that selects data to feed through the Function. They are ephemeral: they can be used by any Function downstream, but will not be added to events, and will not exit the Pipeline. Fields that start with _ (double underscore) are special in Cribl Stream. (In Splunk, these will be index-time fields). No errors about the string being too long and, when I performed a search, all of the fields in each xferlog message were available to search against.The Regex Extract Function extracts fields using regex named groups. The extraction I’d just created looked like: ^+ + + + + (?P +) (?P +) (?P +) (?P +) (?P +) (?P +) (?P +)Īdding the last six fields was as simple as appending them to the end of the regular expression and pressing save. In the Splunk management interface you can create and edit raw field extractions without the (helpful) overhead of the IFE. I saved the field extraction anyway, providing field names when I saved it. As far as I can tell, there’s a limit on how long your regex can be when using the Interactive Field Extractor. When I tried to enter that into the IFE the form began to act squirrely after the eighth field and wouldn’t let me add anything else. After experimenting with the IFE, I found that Splunk was expecting a regular expression that looked something like: ^ (?P +)(?:* )(?P +) The documentation on doing this using the Interactive Field Extractor is pretty sparse (read: non-existent). The better way is to create a long regular expression that can extract all of the fields that we’re interested at once. (The date is parsed automatically by Splunk, so we’ll leave that one alone). The long way to get those fields would be to write thirteen individual field extractions, one for each field. The xferlog format consists of fourteen fields, all of which we may be interested in searching on at some point. The actual examples would be all one line without the ‘’ characters.)

(I’ve added linebreaks throughout this post to make it more readable. Extracting xferlog fieldsĪs an example, let’s look at an xferlog generated by ProFTP. This allows you to parse an entire log message into its component fields using just one field extraction statement. One feature of field extractions that I just discovered is the ability to extract multiple fields from one field extraction. For a quick overview, check out the Splunk video on using the Interactive Field Extractor (IFE). If our custom logs contain a hostname and an error code, for example, field extractions let me pull those values from the logs and then write searches based on them. That’s where field extractions come in handy.įield extractions allow you to define a regular expression to run against log messages and extract out fields that you define. Our custom application logs, though, need a little massaging before we can put them to use. Splunk does an excellent job of identifying the format of the data we ingest and automatically extracting fields for log types that it knows about. A project I’m on indexes absolutely every log that it generates into Splunk, from firewall logs to system logs to custom application logs. As a SysAdmin, one of the cooler tools that I’ve worked with is Splunk.

Splunk rex field raw example