This is also the main reason I choose very short (usually one-letter) node names since it can become very annoying to write server. Name and current_size_kb aren't one of the 4 default DM fields, so it must be server.name and server. So you this won't work: | tstats count from datamodel=internal_server by name current_size_kb Except the default 4 fields in the DM: _time, host, source, sourcetype. The name, once again, comes from the "Object ID", not the pretty name label (ie use summaryindexing, not "Summary Indexing Searches").Īlso note that every field you want to reference in the DM, must be prefixed by the node name Object ID server. Which happens to be the same as | tstats count from datamodel=internal_server where nodename=server.schedulerīecause this DM has a child node under the the Root Event. For example: | tstats count from datamodel=internal_server where source=*scheduler.log Note that tstats is like stats but more "SQL-like".
On a big DM (like from a large Splunk Enterprise Security environment), this could take hours or days depending on how much data needs to be accelerated and how busy the servers are. And if you forgot to add a field in the DM then you must stop/delete the DM acceleration, modify the DM, then re-accelerate. Disks are cheap CPUs are not.Īs mentioned before, another drawback of tstats is that you can only access either the default index-time fields or custom index-time fields created by DM acceleration.
That's why the DM status in the UI tells you how much disk space the DM acceleration takes up. And in this case, you'll trading disk space to gain faster search. If you don't see a big difference then either try increasing the time range/acceleration window or create your own DM on a much chattier data source/index. Once the DM is finished accelerating to 100%, then try running this: | tstats count where index=_internal by sourcetype sourceĪnd note how much faster this is compared to index=_internal | stats count by sourcetype source Pick a window big enough like 7 days and search the last 24 hours for testing. Now accelerate the internal_server DM if you haven't already. You tell tstats which DM to use with the from datamodel=internal_server clause. If you wanna "see" what's inside these tsidx files then you can do something like. If the data model is accelerated then the new *.tsidx indexed files are created on the indexers at $SPLUNK_DB$//datamodel_summary/_//DM_. Don't do "Last X minutes" since the time range will be different when you run the search ad-hoc. Make sure you use the same fixed time range (ie from X to Y). You can verify that you'll get the exact same count from both the tstats and normal search. The translation is defined by the base search of the DM (under "Constraints"). If the DM isn't accelerated then tstats will translate to a normal search command, so the above command will run: index=_internal source=*scheduler.log* OR source=*metrics.log* OR source=*splunkd.log* OR source=*license_usage.log* OR source=*splunkd_access.log* | stats count Note that I use the DM filename internal_server (ie Object ID), not the "pretty" name. įirst, run a simple tstats on the DM (doesn't have to be accelerated) to make sure it's working and you get some result: | tstats count from datamodel=internal_server Since this seems to be an popular answer, I'll get in even more details:įor our example, let's use the out-of-the-box data model called "Splunk's Internal Server Logs - SAMPLE" at. Generally, I recommend using accelerated data models. INDEXED_EXTRACTIONS in nf for structured data like CSV.Index-time fields manually via nf, nf, and nf.A namespace created by the tscollect search command.Tstats can run on the index-time fields from the following methods: Since status and username are not index-time fields (they are search-time). You can do this: | tstats count by index sourcetype sourceīut you can't do this: | tstats count where status>200 by username By default, this only includes index-time fields such as sourcetype, host, source, _time, etc. Since tstats can only look at the indexed metadata it can only search fields that are in the metadata. tsidx files in the buckets on the indexers) whereas stats is working off the data (in this case the raw events) before that command. Tstats is faster than stats since tstats only looks at the indexed metadata (the.
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