![]() If you’re ever confused as to how to turn your data model search into a tstats version, one trick is to recreate the equivalent of your search in the Datasets (Pivot) function. Tstats search: | tstats dc(All_st_ip) AS dest_ip from datamodel=Network_Traffic by All_Traffic.src_ip | stats dc(All_st_ip) by All_Traffic.src_ip Standard datamodel search: | datamodel Network_Traffic All_Traffic search ![]() Tstats search: | tstats count where index=os sourcetype=syslog earliest=-5m by splunk_serverĮxample 3: CIM Data Model Search – Count of Destination IPs by Source IP Tstats search: | tstats count where index=* OR index=_* by index, sourcetypeĮxample 2: Indexer Data Distribution over 5 Minutes Syntax (Simplified) | tstats (field) AS renamed-field where by field The following fields are indexed by default and can be searched with tstats:Īdditional metadata fields that can be used but aren’t part of the tsidx are: You’ll want to make sure you specify a WHERE clause with an index to keep the scope of your search as specific as possible. If you’re used to SQL, you can think of it like replacing SELECT with “| tstats” and swapping the order of your WHERE and GROUP BY clauses. The syntax for tstats takes some practice to get right. The tstats command is most commonly employed for accelerated data models and calculating metrics for your event data. This limits the flexibility somewhat, but evals can usually be implemented in another way as a workaround. Aggregation functions don’t support eval statements, unlike the regular stats command.For every dashboard panel, you have to manually create a search that will utilize any clicked values and embed it within the drilldown XML tags. When you use tstats searches in dashboards, creating drilldowns is more difficult.An “accelerated” result is merely pre-computed, but if that lookup result changes then your accelerated results might have stale data. Acceleration isn’t great for data sources with dynamic lookups that change often.That means additional work may be required to create the fastest searches for your data. Tstats is limited to indexed fields and data models.Much like SQL, the data is selected and aggregated in one query. It might be a bit of a stretch to suggest this, but tstats syntax is more like SQL than searching raw data with the standard search command (“| search” is implied with all searches that don’t have a leading search command). ![]() Its syntax is familiar for SQL developers.For data models, it will read the accelerated data and fallback to the raw data if accelerated data isn’t available (by default). Tstats doesn’t read or decompress raw event data, which means it skips the process of data extraction by only reading the fields captured in the tsidx files (more on that below). After all, who wants to rewrite all of their dashboards and reports after already creating them based on raw search? The truth is, tstats is great but it has a few limitations and can’t be leveraged for every use case.įirst, let’s talk about the benefits. SPL is already hard enough, so just the idea of learning tstats syntax can be daunting. Most of us have heard about how fast Splunk’s tstats command can produce fast searches, but there’s not much in the training materials to help us learn how to use it.
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