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tstats

Description

Use the tstats command to perform statistical queries on indexed fields in tsidx files. The indexed fields can be from normal index data, tscollect data, or accelerated data models.

Syntax

| tstats [prestats=<bool>] [local=<bool>] [append=<bool>] [summariesonly=<bool>] [allow_old_summaries=<bool>] [chunk_size=<unsigned int>] <stats-func>... [FROM ( <namespace> | sid=<tscollect-job-id> | datamodel=<data_model-name> )] [WHERE <search-query>] [BY <field-list> [span=<timespan>] ]

Required arguments

<stats-func>...
Syntax: count(<field>) | ( avg | dc | earliest | estdc | exactperc | first | last | latest | median | max | min | mode | perc | p | range | stdev | stdevp | sum | sumsq | upperperc | values | var | varp )(<field>) [AS <string>]
Description: Either perform a basic count of a field or perform a function on a field. You can provide any number of aggregates to perform. You can also rename the result using 'AS', unless you are in prestats mode. For the complete list of functions with examples, see Statistical and charting functions.

Optional arguments

append
Syntax: append=<bool>
Description: When in prestats mode (prestats=t), enables append=t where the prestats results append to existing results, instead of generating them.
Default: false
allow_old_summaries
Syntax: allow_old_summaries=true | false
Description: Only applies when selecting from an accelerated data model. To return results from summary directories only when those directories are up-to-date, set this parameter to false. If the data model definition has changed, summary directories that are older than the new definition are not used when producing output from tstats. This default ensures that the output from tstats will always reflect your current configuration. When set to true, tstats will use both current summary data and summary data that was generated prior to the definition change. Essentially this is an advanced performance feature for cases where you know that the old summaries are "good enough".
Default: false
chunk_size
Syntax: chunk_size=<unsigned_int>
Description: Advanced option. This argument controls how many events are retrieved at a time within a single TSIDX file when answering queries. Only consider supplying a lower value for this if you find a particular query is using too much memory. The case that could cause this would be an excessively high cardinality split-by, such as grouping by several fields that have a very large amount of distinct values. Setting this value too low can negatively impact the overall run time of your query.
Default: 10000000 (10 million)
datamodel
Syntax: datamodel=<data_model-name>
Description: The name of an accelerated data model.
<field-list>
Syntax: <field>, ...
Description: Specify one or more fields to group results.
local
Syntax: local=true | false
Description: If true, forces the processor to be run only on the search head.
Default: false
namespace
Syntax: <string>
Description: Define a location for the tsidx file with $SPLUNK_DB/tsidxstats. If you have Splunk Enterprise, you can configure this location by editing indexes.conf and setting the tsidxStatsHomePath attribute.
prestats
Syntax: prestats=true | false
Description: Specifies whether to use the prestats format. The prestats format is a Splunk internal format that is designed to be consumed by commands that generate aggregate calculations. When using the prestats format you can pipe the data into the chart, stats, or timechart commands, which are designed to accept the prestats format. When prestats=true, AS instructions are not relevant. The field names for the aggregates are determined by the command that consumes the prestats format and produces the aggregate output.
Default: false
sid
Syntax: sid=<tscollect-job-id>
Description: The job ID string of a tscollect search (that generated tsidx files).
summariesonly
Syntax: summariesonly=<bool>
Description: Only applies when selecting from an accelerated data model. When false, generates results from both summarized data and data that is not summarized. For data not summarized as TSIDX data, the full search behavior will be used against the original index data. If set to true, 'tstats' will only generate results from the TSIDX data that has been automatically generated by the acceleration and non-summarized data will not be provided.
Default: false
span
Syntax: span=<int><timespan>
Description: The span of each time bin. If you use the BY clause to group by _time, use the span argument to group the time buckets. You can specify timespans such as ...BY _time span=1h or BY _time span=5d. If you do not specify a <timespan>, the default is auto, which means that the number of time buckets adjusts to produce a reasonable number of results. For example if initially seconds are used for the <timespan> and too many results are being returned, the <timespan> is changed to a longer value, such as minutes, to return fewer time buckets.
Default: auto
<timescale>
Syntax: <sec> | <min> | <hr> | <day> | <month>
Description: Time scale units. For the tstats command, the <timescale> does not support subseconds.
Default: sec
Time scale Syntax Description
<sec> s | sec | secs | second | seconds Time scale in seconds.
<min> m | min | mins | minute | minutes Time scale in minutes.
<hr> h | hr | hrs | hour | hours Time scale in hours.
<day> d | day | days Time scale in days.
<month> mon | month | months Time scale in months.

Usage

The tstats command is a generating command. Generating commands use a leading pipe character. The tstats command must be the first command in a search pipeline, except when (append=true).

Wildcard characters

The tstats command does not support wildcard characters in field values in aggregate functions or BY clauses.

For example, you cannot specify | tstats avg(foo*) or | tstats count WHERE host=x BY source*.

Samples of aggregate functions include avg(), count(), max(), min(), and sum().

Any results returned where the aggregate function or BY clause includes a wildcard character are only the most recent few minutes of data that has not been summarized. Include the summariesonly=t argument with your tstats command to return only summarized data.

Functions and memory usage

Some functions are inherently more expensive, from a memory standpoint, than other functions. For example, the distinct_count function requires far more memory than the count function. The values and list functions also can consume a lot of memory.

If you are using the distinct_count function without a split-by field or with a low-cardinality split-by by field, consider replacing the distinct_count function with the the estdc function (estimated distinct count). The estdc function might result in significantly lower memory usage and run times.

Complex aggregate functions

The tstats command does not support complex aggregate functions such as ...count(eval('Authentication.action'=="failure")).

Consider the following query. This query will not return accurate results because complex aggregate functions are not supported by the tstats command.

| tstats summariesonly=false values(Authentication.tag) as tag, values(Authentication.app) as app, count(eval('Authentication.action'=="failure")) as failure, count(eval('Authentication.action'=="success")) as success from datamodel=Authentication by Authentication.src | search success>0 | where failure > 5 | `settags("access")` | `drop_dm_object_name("Authentication")`

Instead, separate out the aggregate functions from the eval functions, as shown in the following search.

| tstats `summariesonly` values(Authentication.app) as app, count from datamodel=Authentication.Authentication by Authentication.action, Authentication.src | `drop_dm_object_name("Authentication")` | eval success=if(action="success",count,0), failure=if(action="failure",count,0) | stats values(app) as app, sum(failure) as failure, sum(success) as success by src

Selecting data

Use the tstats command to perform statistical queries on indexed fields in tsidx files. You can select the data for the indexed fields in several ways.

Normal index data
Use a FROM clause to specify a namespace, search job ID, or data model. If you do not specify a FROM clause, the Splunk software selects from index data in the same way as the search command. You are restricted to selecting data from your allowed indexes by user role. You control exactly which indexes you select data from by using the WHERE clause. If no indexes are mentioned in the WHERE clause, the Splunk software uses the default indexes. By default, role-based search filters are applied, but can be turned off in the limits.conf file.
Data manually collected with the tscollect command
You can select data from your namespace by specifying FROM <namespace>. If you did not specify a namespace with the tscollect command, the data is collected into the dispatch directory of that job. If the data is in the dispatch directory, you select the data by specifying FROM sid=<tscollect-job-id>.
An accelerated data model
You can select data from a high-performance analytics store, which is a collection of .tsidx data summaries, for an accelerated data model. You can select data from this accelerated data model by using FROM datamodel=<data_model_name>.

Search filters cannot be applied to accelerated data models. This includes both role-based and user-based search filters.

An accelerated data model dataset
When you select data within an accelerated data model, you can further constrain your search by indicating a dataset within that data model that you want to select data from. You do this by using a where clause to indicate the nodename of the data model dataset. The nodename value indicates where the dataset is in a data model hierarchy.
When you use nodename in a search, you always use the following construction: FROM datamodel=<data_model_name> where nodename=<root_dataset_name>.<parent_dataset_name>.<...>.<target_dataset_name>.
For example, say you want to search on a dataset named scheduled_reports in your internal_server data model. In that data model, the scheduled_reports dataset is a child of the scheduler dataset, which in turn is a child of the server root event dataset. This means that you should represent the scheduled_report dataset in your search as nodename=server.scheduler.scheduled_reports.
If you run that search and decide you want to search on the contents of the scheduler data model dataset instead, you would use nodename=server.scheduler in your new search.

Search filters cannot be applied to accelerated data model datasets. This includes both role-based and user-based search filters.

You might see a count mismatch in the events retrieved when searching tsidx files. It is not possible to distinguish between indexed field tokens and raw tokens in tsidx files. On the other hand, it is more explicit to run the tstats on accelerated data models or from a tscollect, where only the fields and values are stored and not the raw tokens.

Filtering with where

You can provide any number of aggregates (aggregate-opt) to perform and also have the option of providing a filtering query using the WHERE keyword. This query looks like a normal query you would use in the search processor. This supports all the same time arguments as search, such as earliest=-1y.

Grouping by _time

You can provide any number of GROUPBY fields. If you are grouping by _time, supply a timespan with span for grouping the time buckets, for example ...BY _time span=1h or ...BY _time span=3d.

Examples

Example 1: Gets the count of all events in the mydata namespace.

| tstats count FROM mydata

Example 2: Returns the average of the field foo in mydata, specifically where bar is value2 and the value of baz is greater than 5.

| tstats avg(foo) FROM mydata WHERE bar=value2 baz>5

Example 3: Gives the count by source for events with host=x.

| tstats count WHERE host=x BY source

Example 4: Gives a timechart of all the data in your default indexes with a day granularity.

| tstats prestats=t count BY _time span=1d | timechart span=1d count

Example 5: Use prestats mode in conjunction with append to compute the median values of foo and bar, which are in different namespaces.

| tstats prestats=t median(foo) FROM mydata | tstats prestats=t append=t median(bar) FROM otherdata | stats median(foo) median(bar)

Example 6: Uses the summariesonly argument to get the time range of the summary for an accelerated data model named mydm.

| tstats summariesonly=t min(_time) AS min, max(_time) AS max FROM datamodel=mydm | eval prettymin=strftime(min, "%c") | eval prettymax=strftime(max, "%c")

Example 7: Uses summariesonly in conjunction with timechart to reveal what data has been summarized over the past hour for an accelerated data model titled mydm.

| tstats summariesonly=t prestats=t count FROM datamodel=mydm BY _time span=1h | timechart span=1h count

Example 8: Uses the values statistical function to provide lists of values for each field returned by the "Splunk's Internal Server Logs" data model.

| tstats values FROM datamodel=internal_server.server

Example 9: Uses the values statistical function to provide lists of values for each field returned by the Alerts dataset within the "Splunk's Internal Server Logs" data model.

| tstats values FROM datamodel=internal_server where nodename=server.scheduler.alerts

See also

stats, tscollect

Answers

Have questions? Visit Splunk Answers and see what questions and answers the Splunk community has using the tstats command.

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This documentation applies to the following versions of Splunk® Enterprise: 6.5.0, 6.5.1, 6.5.1612 (Splunk Cloud only), 6.5.2, 6.5.3, 6.5.4, 6.5.5, 6.6.0, 6.6.1, 6.6.2, 6.6.3, 7.0.0


Comments

Woodamsclark
Thank you for pointing this out! The "span" argument was mentioned under Usage but not under Syntax. I added "span" to the Optional Arguments section.

Lstewart splunk, Splunker
May 22, 2017

span should be listed under the optional arguments or at least make mention that it's default setting is "auto" if left unspecified

Woodamsclark
May 19, 2017

@vskoryk Thanks for pointing that out. I'll get some examples up in this topic to show how you can construct searches to see field values within data models as well as specific data model datasets.

Mness, Splunker
May 15, 2017

there is a bit of a hidden gem functionality with use of functions such as "values" and "list". ie

| tstats values FROM datamodel=Network_Traffic.All_Traffic

above will table all the fields and values within the DM as a table; this is extremely useful for "exploring" data. Someone goes against the point about "wildcard" characters, as this implies that values(*) works.

Vskoryk splunk, Splunker
May 2, 2017

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