![]() The for-loop to reformat the timestamps collectively can be written as such: | inputlookup mylogofmanytimestamps For this to work, assume that each timestamp field is named so that its suffix is "_timestamp" - so three timestamp fields, for example, are created_timestamp, sleep_timestamp, and destroyed_timestamp. We want to change the format of the timestamps from one ("%d-%m-%Y") to another ("%m/%d/%Y"). Take for example a lookup file, mylogofmanytimestamps, containing 20 timestamp fields (for whatever reason). Instead of applying such techniques one by one, using for-loops quickly takes care of each one without writing repetitive steps. Sometimes I deal with 5-10+ timestamp fields that are subject to the same data massaging techniques. It's not uncommon when examing large datasets of logs to encounter many timestamps. | stats count(food_freshness = "VERY FRESH" AND food_type = "FRUIT") as very_fresh_fruits_count, count(food_freshness = "FRESH" AND food_type = "FRUIT") as fresh_fruits_count, count(food_freshness = "SPOILED" AND food_type = "FRUIT") as spoiled_fruits_count | table food_name very_fresh_fruits fresh_fruits spoiled_fruits | stats count(very_fresh_fruits) as very_fresh_fruits_count, count(fresh_fruits) as fresh_fruits_count, count(spoiled_fruits) as spoiled_fruits_count | eval spoiled_fruits = food_freshness = "SPOILED" AND food_type = "FRUIT" | eval fresh_fruits = food_freshness = "FRESH" AND food_type = "FRUIT" ![]() | eval very_fresh_fruits = food_freshness = "VERY FRESH" AND food_type = "FRUIT" In SPL, the top search can be re-written as the bottom search to get your desired results more succinctly: | inputlookup myfoods Now we want to organize the dataset to get simple statistics about these three attributes. Assume the inventory is actually a large dataset and contains many attributes, but for the sake of this example, we are only interested in these attributes: food name, foodtype (our only values are "FRUIT" and "VEGETABLE"), and food_freshness (our only values are "VERY FRESH," "FRESH," and "SPOILED"). Take for example a lookup file, myfoods, containing an inventory of foods in my refridgerator. When outputting data with the stats command, instead of using two lines of SPL to enumerate data ( eval piped to a count), you can combine them as nested functions. With large datasets, succintly counting values against a condition can be a useful trick. Below is a snippet of how it is used (for this example, assume the macro takes one argument, "attribute9," as input). To use the macro in you searches, call the name of the macro enclosed with a single backtick on either side of it. validation expressions, error messages, etc.). When defining your macro, you can set additional behaviors if applicable (i.e. To define a macro, you can navigate to Settings > Advanced search > Search macros, and click New Search Macro. You can even specify if the macro requires an input (arguments). In Splunk, macros behave like modular functions. ![]() When dealing with repetitive searches, it may be better to utilize macros. This command is ideal for expensive searches. The difference is that the loadjob command does not re-run the report and instead loads cached results from a previously scheduled run of the report. The loadjob command performs similarly to the savedsearch. To solve my aforementioned issue, I found that saving the original (long) query as something like a base report and leveraging it in my "children" searches/reports allowed for more elegant re-use. The savedsearch command allows you to re-run a report in a new search. I also didn't want to copy over the long query because doing so would decrease legibility. I was essentially looking for a command that would perform a "jump" (similar to a jump statement would work in assembly) back to the start of the long query. | table attribute1 attribute2 attribute3 attribute4 attribute5 attribute6 attribute7 attribute8īefore I discovered this trick, I had ran into a problem where I had created a very long query and wanted to reuse its results a second time to append the secondary results to the first set of results. ![]() ``` this will only output eight attributes from the lookup ``` Below, you can find the comment, "this will only output eight attributes from the lookup," enclosed with backticks. In Splunk, and as of this post's publication date, you designate the start and end of a comment block with three backticks. The most useful and empathetic language feature is the comment. For full documentation/reference of Splunk search commands, visit this page. I use Splunk/SPL (Splunk Processing Language) nearly daily in my job and thought I'd provide a quick summary of the commands, functions, & features I use regularly to perform my searches.
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