quantile() function
quantile()
returns rows from each input table with values that fall within a
specified quantile or returns the row with the value that represents the
specified quantile.
quantile()
supports columns with float values.
Function behavior
quantile()
acts as an aggregate or selector transformation depending on the
specified method
.
- Aggregate: When using the
estimate_tdigest
orexact_mean
methods,quantile()
acts as an aggregate transformation and outputs the average of non-null records with values that fall within the specified quantile. - Selector: When using the
exact_selector
method,quantile()
acts as a selector selector transformation and outputs the non-null record with the value that represents the specified quantile.
Function type signature
(
<-tables: stream[A],
q: float,
?column: string,
?compression: float,
?method: string,
) => stream[A] where A: Record
Parameters
column
Column to use to compute the quantile. Default is _value
.
q
(Required)
Quantile to compute. Must be between 0.0
and 1.0
.
method
Computation method. Default is estimate_tdigest
.
Available methods:
- estimate_tdigest: Aggregate method that uses a t-digest data structure to compute an accurate quantile estimate on large data sources.
- exact_mean: Aggregate method that takes the average of the two points closest to the quantile value.
- exact_selector: Selector method that returns the row with the value
for which at least
q
points are less than.
compression
Number of centroids to use when compressing the dataset.
Default is 1000.0
.
A larger number produces a more accurate result at the cost of increased memory requirements.
tables
Input data. Default is piped-forward data (<-
).
Examples
Quantile as an aggregate
import "sampledata"
sampledata.float()
|> quantile(q: 0.99, method: "estimate_tdigest")
Quantile as a selector
import "sampledata"
sampledata.float()
|> quantile(q: 0.5, method: "exact_selector")
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