![]() ![]() If you’re a Splunk user, hopefully the first half of this tutorial was helpful for seeing the impact of wildcards on your searches. Splunk Docs: Use CASE() and TERM() to match phrases.If you want to read more about this, here are some references from the Splunk documentation to consider: Essentially, you end up having to look at everything in the list in order to see if it’s a match. I guarantee that it’ll take you longer than just looking for admin, and the same thing happens for Splunk. Try doing the same thing, by looking at the list for *dmin. Instead of quickly finding what I’m looking for in the list, I now need to look at every single line and compare it to see if it is a match. Things are significantly different when a leading wildcard is in use. If I’m searching for adm*, I’ll first find everything that starts with adm, and then only look at those results to see if any need to be discarded. With a trailing wildcard, the behavior isn’t much different from what happens when an absolute term is defined. Now, consider the impact of using wildcards with this list. Let’s say I’m searching for “admin.” I can quickly find it in this sorted list. nf is the config file that controls this behavior. These segments are controlled by breakers, which are considered to be either major or minor. In general, most special characters or spaces dictate how segmentation happens Splunk actually examines the segments created by these characters when a search is run. The existence of segments is what allows for various terms to be searched by Splunk. When Splunk ingests data, it breaks events into searchable segments, which are stored in files that Splunk accesses when a search is run (this is the TSIDX file, or the 35% of disk space that represents the search factor when making a disk space calculation). Please note that the actual behavior is a bit more complex than described here. I’ll attempt to explain this in the simplest way possible to avoid confusion. This behavior is related to how Splunk handles data processing under the hood. Why do leading wildcards impact search performance? The next section covers why this occurs in more technical detail–but I’ll warn you, it’s a bit complicated. If you simply want to improve your search performance, you can stop here. A trailing wildcard (e.g., Acc*) yields similar performance in this example to a search without any wildcards, whereas using a leading wildcard (e.g., *ccept) quadruples the execution time of the search. ![]() As you can see in this video, the search performance varies significantly based on how wildcards are used.
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