streamstats
Description
Adds cumulative summary statistics to all search results in a streaming manner. The streamstats
command calculates statistics for each event at the time the event is seen. For example, you can calculate the running total for a particular field. The total is calculated by using the values in the specified field for every event that has been processed, up to the current event.
As the streamstats
command processes each event, it adds a field to that event or result that represents the accumulation of all of the events before it in the time window. The value of that field changes per event or result as the composition of events in the window or result set changes. In other words, the streamstats
command produces a running total that is applied to each event, or the result of another transforming search, as they stream in. The streamstats
command operates on whatever search output it receives and is the accumulation of the average, sum, count or so on, of one the following two elements:
- All of the events in the search window that have been collected up to that point, if a window is applied. If you don't set the
time_window
or thewindow
arguments, the default of 10,000 events set by themax_stream_window
in the limits.conf file applies to yourstreamstats
searches. See Optional arguments.
- The results returned by a transforming command, such as the
stats
,chart
, ortimechart
command, as each result is received and the running total of the events preceding that result is applied to it.
Syntax
The required syntax is in bold.
- streamstats
- [reset_on_change=<bool>]
- [reset_before="("<eval-expression>")"]
- [reset_after="("<eval-expression>")"]
- [current=<bool>]
- [window=<int>]
- [time_window=<span-length>]
- [global=<bool>]
- [allnum=<bool>]
- <stats-agg-term>...
- [<by-clause>]
Required arguments
- stats-agg-term
- Syntax: <stats-func>( <evaled-field> | <wc-field> ) [AS <wc-field>]
- Description: A statistical aggregation function. See Stats function options. The function can be applied to an eval expression, or to a field or set of fields. Use the AS clause to place the result into a new field with a name that you specify. You can use wild card characters in field names. For more information on eval expressions, see Types of eval expressions in the Search Manual.
Optional arguments
- allnum
- Syntax: allnum=<boolean>
- Description: If true, computes numerical statistics on each field only if all of the values in that field are numerical.
- Default: false
- by-clause
- Syntax: BY <field-list>
- Description: The name of one or more fields to group by.
- current
- Syntax: current=<boolean>
- Description: If true, the search includes the given, or current, event in the summary calculations. If false, the search uses the field value from the previous event.
- Default: true
- global
- Syntax: global=<boolean>
- Description: Used only when the
window
argument is set. Defines whether to use a single window,global=true
, or to use separate windows based on theby clause
. Ifglobal=false
andwindow
is set to a non-zero value, a separate window is used for each group of values of the field specified in theby clause
. - Default: true
- reset_after
- Syntax: reset_after="("<eval-expression>")"
- Description: After the streamstats calculations are produced for an event,
reset_after
specifies that all of the accumulated statistics are reset if theeval-expression
returnstrue
. Theeval-expression
must evaluate to true or false. Theeval-expression
can reference fields that are returned by thestreamstats
command. When thereset_after
argument is combined with thewindow
argument, the window is also reset when the accumulated statistics are reset. - Default: false
- reset_before
- Syntax: reset_before="("<eval-expression>")"
- Description: Before the
streamstats
calculations are produced for an event,reset_before
specifies that all of the accumulated statistics are reset when theeval-expression
returnstrue
. Theeval-expression
must evaluate to true or false. When thereset_before
argument is combined with thewindow
argument, the window is also reset when the accumulated statistics are reset. - Default: false
- reset_on_change
- Syntax: reset_on_change=<bool>
- Description: Specifies that all of the accumulated statistics are reset when the group by fields change. The reset is as if no previous events have been seen. Only events that have all of the group by fields can trigger a reset. Events that have only some of the group by fields are ignored. When the
reset_on_change
argument is combined with thewindow
argument, the window is also reset when the accumulated statistics are reset. See the Usage section. - Default: false
- time_window
- Syntax: time_window=<span-length>
- Description: Specifies the window size for the
streamstats
calculations, based on time. After each time window passes, thestreamstats
calculations are reset.
- The
time_window
argument is limited by range of values in the_time
field in the events. To use thetime_window
argument, the events must be sorted in either ascending or descending time order. You can use thewindow
argument with thetime_window
argument to specify the maximum number of events in a window. To specify five minutes for the span length, usetime_window=5m
. To specify 2 days, usetime_window=2d
.
- The following table shows additional time ranges and valid values that you can set for the span length.
Time range Valid values seconds 1s, 2s, ... minutes 1m, 2m, … hours 1h,2h, … days 1d, 2d, ... weeks 1w, 2w, ... months 1mon, 2mon, 3mon, 4mon, 6mon, 12mon quarters 1q, 2q, 4q years 1y, 2y, ...
- Default: None. However, the value of the
max_stream_window
attribute in thelimits.conf
file applies. The default value is 10000 events.
- window
- Syntax: window=<integer>
- Description: Specifies the number of events to use when computing the statistics.
- Default: 0, which means that all previous and current events are used.
Stats function options
- stats-func
- Syntax: The syntax depends on the function that you use. Refer to the table below.
- Description: Statistical and charting functions that you can use with the
streamstats
command. Each time you invoke thestreamstats
command, you can use one or more functions. However, you can only use oneBY
clause. See Usage.
- The following table lists the supported functions by type of function. Use the links in the table to see descriptions and examples for each function. For an overview about using functions with commands, see Statistical and charting functions.
Type of function Supported functions and syntax Aggregate functions avg()
count()
distinct_count()
estdc()
estdc_error()
exactperc<int>()
max()
median()
min()
mode()
perc<int>()
range()
stdev()
stdevp()
sum()
sumsq()
upperperc<int>()
var()
varp()
Event order functions earliest()
first()
last()
latest()
Multivalue stats and chart functions list(X)
values(X)
Usage
The streamstats
command is a centralized streaming command. See Command types.
The streamstats
command is similar to the eventstats
command except that it uses events before the current event to compute the aggregate statistics that are applied to each event. If you want to include the current event in the statistical calculations, use current=true
, which is the default.
The streamstats
command is also similar to the stats
command in that streamstats
calculates summary statistics on search results. Unlike stats
, which works on the group of results as a whole, streamstats
calculates statistics for each event at the time the event is seen.
Statistical functions that are not applied to specific fields
With the exception of the count
function, when you pair the streamstats
command with functions that are not applied to specific fields or eval
expressions that resolve into fields, the search head processes it as if it were applied to a wildcard for all fields. In other words, when you have | streamstats avg
in a search, it returns results for | stats avg(*)
.
This "implicit wildcard" syntax is officially deprecated, however. Make the wildcard explicit. Write | streamstats <function>(*)
when you want a function to apply to all possible fields.
Escaping string values
If your <eval-expression> contains a value instead of a field name, you must escape the quotation marks around the value.
The following example is a simple way to see this. Start by using the makeresults
command to create 3 events. Use the streamstats
command to produce a cumulative count of the events. Then use the eval
command to create a simple test. If the value of the count
field is equal to 2, display yes
in the test
field. Otherwise display no
in the test
field.
| makeresults count=3 | streamstats count | eval test=if(count==2,"yes","no")
The results appear something like this:
_time | count | test |
---|---|---|
2017-01-11 11:32:43 | 1 | no |
2017-01-11 11:32:43 | 2 | yes |
2017-01-11 11:32:43 | 3 | no |
Use the streamstats
command to reset the count when the match is true. You must escape the quotation marks around the word yes
. The following example shows the complete search.
| makeresults count=3 | streamstats count | eval test=if(count==2,"yes","no") | streamstats count as testCount reset_after="("match(test,\"yes\")")"
Here is another example.
You want to look for the value session is closed
in the description field. Because the value is a string, you must enclose it in quotation marks. You then need to escape those quotation marks.
... | streamstats reset_after="("description==\"session is closed\"")"
The reset_on_change
argument
You have a dataset with the field "shift" that contains either the value DAY or the value NIGHT. You run this search:
...| streamstats count BY shift reset_on_change=true
If the dataset is:
- shift
- DAY
- DAY
- NIGHT
- NIGHT
- NIGHT
- NIGHT
- DAY
- NIGHT
Running the command with reset_on_change=true
produces the following streamstats results:
- shift, count
- DAY, 1
- DAY, 2
- NIGHT, 1
- NIGHT, 2
- NIGHT, 3
- NIGHT, 4
- DAY, 1
- NIGHT, 1
Memory and maximum results
The streamstats
search processor uses two limits.conf
settings to determine the maximum number of results that it can store in memory for the purpose of computing statistics.
The maxresultrows
setting specifies a top limit for the window
argument. This sets the number of result rows that the streamstats
command processor can store in memory. The max_mem_usage_mb
setting limits how much memory the streamstats
command uses to keep track of information.
When the max_mem_usage_mb
limit is reached, the streamstats
command processor stops adding the requested fields to the search results.
Do not set max_mem_usage_mb=0
as this removes the bounds to the amount of memory the streamstats
command processor can use. This can lead to search failures.
Prerequisites
- Only users with file system access, such as system administrators, can increase the
maxresultrows
andmax_mem_usage_mb
settings using configuration files. - Review the steps in How to edit a configuration file in the Splunk Enterprise Admin Manual.
- You can have configuration files with the same name in your default, local, and app directories. Read Where you can place (or find) your modified configuration files in the Splunk Enterprise Admin Manual.
Never change or copy the configuration files in the default directory. The files in the default directory must remain intact and in their original location. Make changes to the files in the local directory.
If you have Splunk Cloud Platform and want to change these limits, file a Support ticket.
Basic examples
1. Compute the average of a field over the last 5 events
For each event, compute the average of the foo
field over the last 5 events, including the current event.
... | streamstats avg(foo) window=5
This is similar to using the trendline
command to compute a simple moving average (SMA), such as trendline sma5(foo)
.
2. Compute the average of a field, with a by clause, over the last 5 events
For each event, compute the average value of foo for each value of bar including only 5 events, specified by the window size, with that value of bar.
... | streamstats avg(foo) by bar window=5 global=f
3. For each event, add a count of the number of events processed
This example adds to each event a count field that represents the number of events seen so far, including that event. For example, it adds 1 for the first event, 2 for the second event, and so on.
... | streamstats count
If you did not want to include the current event, you would specify:
... | streamstats count current=f
4. Apply a time-based window to streamstats
Assume that the max_stream_window
argument in the limits.conf
file is the default value of 10000 events.
The following search counts the events, using a time window of five minutes.
... | streamstats count time_window=5m
This search adds a count field to each event.
- If the events are in descending time order (most recent to oldest), the value in the count field represents the number of events in the next 5 minutes.
- If the events are in ascending time order (oldest to most recent), the count field represents the number of events in the previous 5 minutes.
If there are more events in the time-based window than the value for the max_stream_window
argument, the max_stream_window
argument takes precedence. The count will never be greater than 10000, even if there are actually more than 10,000 events in any 5 minute period.
Extended examples
1. Create events for testing
You can use the streamstats
command with the makeresults
command to create a series events. This technique is often used for testing search syntax. The eval
command is used to create events with different hours. You use 3600, the number of seconds in an hour, in the eval
command.
| makeresults count=5
| streamstats count
| eval _time=_time-(count*3600)
The makeresults
command is used to create the count
field. The streamstats
command calculates a cumulative count for each event, at the time the event is processed.
The results look something like this:
_time | count |
---|---|
2020-01-09 15:35:14 | 1 |
2020-01-09 14:35:14 | 2 |
2020-01-09 13:35:14 | 3 |
2020-01-09 12:35:14 | 4 |
2020-01-09 11:35:14 | 5 |
Notice that the hours in the timestamp are 1 hour apart.
You can create additional fields by using the eval
command.
| makeresults count=5
| streamstats count
| eval _time=_time-(count*3600)
| eval age = case(count=1, 25, count=2, 39, count=3, 31, count=4, 27, count=5, null())
| eval city = case(count=1 OR count=3, "San Francisco", count=2 OR count=4, "Seattle",count=5, "Los Angeles")
- The
eval
command is used to create two new fields,age
andcity
. Theeval
command uses the value in the count field. - The
case
function takes pairs of arguments, such ascount=1, 25
. The first argument is a Boolean expression. When that expression is TRUE, the corresponding second argument is returned.
The results of the search look like this:
_time | age | city | count |
---|---|---|---|
2020-01-09 15:35:14 | 25 | San Francisco | 1 |
2020-01-09 14:35:14 | 39 | Seattle | 2 |
2020-01-09 13:35:14 | 31 | San Francisco | 3 |
2020-01-09 12:35:14 | 27 | Seattle | 4 |
2020-01-09 11:35:14 | Los Angeles | 5 |
2. Calculate a snapshot of summary statistics
This example uses the sample data from the Search Tutorial but should work with any format of Apache web access log. To try this example on your own Splunk instance, you must download the sample data and follow the instructions to get the tutorial data into Splunk. Use the time range All time when you run the search. |
You want to determine the number of the bytes used over a set period of time. The following search uses the first 5 events. Because search results typically display the most recent event first, the sort
command is used to sort the 5 events in ascending order to see the oldest event first and the most recent event last. Ascending order enables the streamstats
command to calculate statistics over time.
sourcetype=access_combined* | head 5 | sort _time
Add the streamstats
command to the search to generate a running total of the bytes over the 5 events and organize the results by clientip
.
sourcetype=access_combined* | head 5 |sort _time | streamstats sum(bytes) AS ASimpleSumOfBytes BY clientip
When you click on the ASimpleSumOfBytes
field in the list of Interesting fields, an information window shows the cumulative sum of the bytes, as shown in this image:
The streamstats
command aggregates the statistics to the original data, which means that all of the original data is accessible for further calculations.
Add the table
command to the search to display the only the values in the _time
, clientip
, bytes
, and ASimpleSumOfBytes
fields.
sourcetype=access_combined* | head 5 |sort _time | streamstats sum(bytes) as ASimpleSumOfBytes by clientip | table _time, clientip, bytes, ASimpleSumOfBytes
Each event shows the timestamp for the event, the clientip, and the number of bytes
used. The ASimpleSumOfBytes
field shows a cumulative summary of the bytes for each clientip
.
3. Calculate the running total of distinct users over time
Each day you track unique users, and you would like to track the cumulative count of distinct users. This example calculates the running total of distinct users over time.
eventtype="download" | bin _time span=1d as day | stats values(clientip) as ips dc(clientip) by day | streamstats dc(ips) as "Cumulative total"
The bin
command breaks the time into days. The stats
command calculates the distinct users (clientip) and user count per day. The streamstats
command finds the running distinct count of users.
This search returns a table that includes: day
, ips
, dc(clientip)
, and Cumulative total
.
4. Calculate hourly cumulative totals
This example uses streamstats
to produce hourly cumulative totals.
... | timechart span=1h sum(bytes) as SumOfBytes | streamstats global=f sum(*) as accu_total_*
This search returns 3 columns: _time, SumOfBytes, and accu_total_SumOfBytes.
The timechart
command buckets the events into spans of 1 hour and counts the total values for each category. The timechart
command also fills NULL values, so that there are no missing values. Then, the streamstats
command is used to calculate the accumulated total.
This example uses streamstats
to produce hourly cumulative totals for category values.
... | timechart span=1h sum(value) as total by category | streamstats global=f | addtotals | accum Total | rename Total as accu_total
5. Calculate when a DHCP IP lease address changed for a specific MAC address
This example uses streamstats
to figure out when a DHCP IP lease address changed for a MAC address, 54:00:00:00:00:00.
source=dhcp MAC=54:00:00:00:00:00 | head 10 | streamstats current=f last(DHCP_IP) as new_dhcp_ip last(_time) as time_of_change by MAC
You can also clean up the presentation to display a table of the DHCP IP address changes and the times the occurred.
source=dhcp MAC=54:00:00:00:00:00 | head 10 | streamstats current=f last(DHCP_IP) as new_dhcp_ip last(_time) as time_of_change by MAC | where DHCP_IP!=new_dhcp_ip | convert ctime(time_of_change) as time_of_change | rename DHCP_IP as old_dhcp_ip | table time_of_change, MAC, old_dhcp_ip, new_dhcp_ip
For more details, refer to the Splunk Blogs post for this example.
6. Compare a number with itself over a few months
Say a community needs to find out how their vaccination booster campaign is going. They want to check the gap after their citizens get the second booster shot, which should keep up with their target of about 6 months between the second and third doses. The following search is across the daily number of people by number of doses.
... | sort _time
| streamstats time_window=153d earliest(two_doses) as two_doses_5mon
| streamstats time_window=183d earliest(two_doses) as two_doses_6mon
| streamstats time_window=214d earliest(two_doses) as two_doses_7mon
| foreach two_doses_* [ eval booster_gap_<<MATCHSTR>> = <<FIELD>> - three_doses ]
| timechart span=1d max(booster_gap_*) as booster_gap_*
The search results return a graph that looks something like this, with 3 lines for the second booster showing the gap at 5 months, 6 months, and 7 months, which shows that the community is almost keeping up with a 6-month booster gap:
See also
- Commands
- accum
- autoregress
- delta
- fillnull
- eventstats
- makeresults
- trendline
strcat | table |
This documentation applies to the following versions of Splunk Cloud Platform™: 9.2.2406, 8.2.2201, 8.2.2202, 8.2.2203, 9.0.2205, 9.0.2208, 9.0.2209, 9.0.2303, 9.0.2305, 9.1.2308, 9.1.2312, 9.2.2403 (latest FedRAMP release), 8.2.2112
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