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.

Syntax

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.

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 the by clause. If global=false and window is set to a non-zero value, a separate window is used for each group of values of the field specified in the by 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 the eval-expression returns true. The eval-expression must evaluate to true or false. The eval-expression can reference fields that are returned by the streamstats command. When the reset_after argument is combined with the window 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 the eval-expression returns true. The eval-expression must evaluate to true or false. When the reset_before argument is combined with the window 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 the window 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. The time_window argument is limited by range of values in the _time field in the events. To use the time_window argument, the events must be sorted in either ascending or descending time order. You can use the window argument with the time_window argument to specify the maximum number of events in a window. For the <span-length>, to specify five minutes, use time_window=5m. To specify 2 days, use time_window=2d.

Default: None. However, the value of the max_stream_window attribute in the limits.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 the streamstats command, you can use one or more functions.

The following table lists the supported functions by type of function. For descriptions and examples, see Statistical and charting functions.

Type of function	Supported functions and syntax
Aggregate functions	avg() count() distinct_count() estdc() estdc_error()	max() median() min() mode()	perc<int> range() stdev() stdevp()	sum() sumsq() var() varp()
Event order functions	earliest()	first()	last()	latest()
Multivalue stats and chart functions	list(X)	values(X)

Usage

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.

Escaping string values

If your <eval-expression> contains a value instead of a field name, you must escape the quotation marks around the value. For 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\"")" <search> ===The <code>reset_on_change</code> argument=== You have a dataset with the field "shift" that contains either the value DAY or the value NIGHT. You run this search: <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

Basic examples

1. Compute the average of a field over the last 5 events

For each event, compute the average of field foo over the last 5 events, including the current event. Similar to doing trendline sma5(foo)

... | streamstats avg(foo) window=5

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 > 10000, even if there are actually more than 10,000 events in any 5 minute period.

Extended examples

5. 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.

6. Calculate hourly cumulative totals for category values

This example uses streamstats to produce hourly cumulative totals for category values.

... | timechart span=1h sum(value) as total by category | streamstats global=f sum(total) as accu_total

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.

7. 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.

See also

accum, autoregress, delta, fillnull, eventstats, trendline

Answers

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