quantile() function
The quantile()
function returns records from an input table with _value
s that fall within
a specified quantile or it returns the record with the _value
that represents the specified quantile.
Which it returns depends on the method used.
quantile()
supports columns with float values.
quantile()
behaves like an aggregate function
or a selector function depending on
the method
used.
quantile(
column: "_value",
q: 0.99,
method: "estimate_tdigest",
compression: 1000.0,
)
When using the estimate_tdigest
or exact_mean
methods, it outputs non-null
records with values that fall within the specified quantile.
When using the exact_selector
method, it outputs the non-null record with the
value that represents the specified quantile.
Parameters
column
Column to use to compute the quantile.
Default is "_value"
.
q
(Required) Value between 0 and 1 indicating the desired quantile.
method
Computation method.
Default is estimate_tdigest
.
The available options are:
estimate_tdigest
An aggregate method that uses a t-digest data structure to compute an accurate quantile estimate on large data sources.
exact_mean
An aggregate method that takes the average of the two points closest to the quantile value.
exact_selector
A selector method that returns the data point for which at least q
points are less than.
compression
Number of centroids to use when compressing the dataset.
A larger number produces a more accurate result at the cost of increased memory requirements.
Default is 1000.0
.
tables
Input data.
Default is piped-forward data (<-
).
Examples
The following examples use data provided by the sampledata
package
to show how quantile()
transforms data.
Quantile as an aggregate
import "sampledata"
sampledata.float()
|> quantile(q: 0.99, method: "estimate_tdigest", compression: 1000.0)
Quantile as a selector
import "sampledata"
sampledata.float()
|> quantile(q: 0.5, method: "exact_selector")
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