Used to compute multiple aggregate functions over the input.
Hide omitted argument names for this function
Omitted Argument NamesThe argument name for
function
can be omitted; the following forms of this function are equivalent:logscale Syntaxstats("value")
and:
logscale Syntaxstats(function="value")
These examples show basic structure only.
The stats()
function is implicitly present in a fair
number of places where a list of subaggregators is given - for example,
groupBy(x, function=[min(y), max(y)])
is
equivalent to groupBy(x, function=stats([min(y),
max(y)]))
. This is how aggregator results are combined when using
those other functions.
The output of stats()
is:
The output combination is checked for fieldname collisions - and it is an error if a field is present in multiple outputs with conflicting values.
In case all subaggregators yield at most one row of output (this includes most numerical aggregators), the result will be one combined row.
When one or more of the subaggregators of
stats()
emit more than one result row, the total output is the Cartesian product of all of the subaggregators' outputs, except if any of the subaggregators outputs zero rows, it is taken as it is outputting a single empty row.
The stats()
is also available as a shorthand syntax
by writing a list of aggregators in square brackets:
...
| stats(function=[min(), max()])
Is equivalent to:
...
| [min(),max()]
This produces one row of data that contains both min and max results.
The following query is equivalent to just count()
:
stats(function=count())
stats()
Examples
Click
next to an example below to get the full details.Annotate Events With Aggregation - Example 1
Annotate events using stats()
function and aggregation
Query
kvparse()
| stats([
avg(x),
table([x])
])
Introduction
The stats()
function can be used to compute
multiple aggregate functions over the input. In this example, the
stats()
function is used with aggregation on
the field x.
Example incoming data might look like this:
x=1
x=2
x=9
x=10
Step-by-Step
Starting with the source repository events.
- logscale
kvparse()
Parses the string into key value pairs.
- logscale
| stats([ avg(x), table([x]) ])
Computes the aggregate functions
avg()
andtable()
over the field x, and returns the results in a field named _avg and a field named x. Note that thetable()
function returns more rows as output, whereas theavg()
function only returns 1 row. Event Result set.
Summary and Results
The query is used to compute multiple aggregate functions over an input.
Sample output from the incoming example data:
"_avg","x"
"5.5","1"
"5.5","2"
"5.5","9"
"5.5","10"
Annotate Events With Aggregation - Example 2
Annotate events using stats()
function and aggregation
Query
kvparse()
stats([
sum(x, as=sumX),
avg(y, as=avgY),
table([x, y])
])
Introduction
The stats()
function can be used to compute
multiple aggregate functions over the input. In this example, the
stats()
function is used with aggregation on
the field x where one of the subaggregators
(avg(y)
) outputs zero rows.
The example shows what happens, when a subaggregator
avg(y)
does not produce an output.
Example incoming data might look like this:
"x=1 y=N/A"
"x=2 y=N/A"
Step-by-Step
Starting with the source repository events.
- logscale
kvparse()
Parses the string into key value pairs.
- logscale
stats([ sum(x, as=sumX), avg(y, as=avgY), table([x, y]) ])
Computes the aggregate functions
sum()
,avg()
andtable()
over the fields x and y, and returns the results in a field named sumX, a field named x, and a field named y. Event Result set.
Summary and Results
The query is used to compute multiple aggregate functions over an input.
Sample output from the incoming example data:
"sumX","x","y"
"3","1","N/A"
"3","2","N/A"
Annotate Events With Aggregation - Example 3
Annotate events using stats()
function and aggregation
Query
kvparse()
| stats([
table([x,y]),
table([z])
])
Introduction
The stats()
function can be used to compute
multiple aggregate functions over the input. In this example, the
stats()
function is used with aggregation on
the fields x, y, and
z, where all of the subaggregators output
rows.
The example shows a Cartesian product where the output is all combinations of all results of the subaggregators
Example incoming data might look like this:
"x=1 y=10 z=100"
"x=2 y=20 z=200"
Step-by-Step
Starting with the source repository events.
- logscale
kvparse()
Parses the string into key value pairs.
- logscale
| stats([ table([x,y]), table([z]) ])
Computes the aggregate function
table()
over the fields x, y, and z, and returns the results - a combination of all outputs, also called the Cartesian product - in a field named x, a field named y, and a field named z. Note that since both subaggregators output multiple rows, the returned result is the Cartesian product, containing all combinations of the results from the subaggregators. Event Result set.
Summary and Results
The query is used to compute multiple aggregate functions over an input.
Sample output from the incoming example data:
"x","y","z"
"1","10","100"
"1","10","200"
"2","20","100"
"2","20","200"