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
quantile() supports columns with float values.
quantile() acts as an aggregate or selector transformation depending on the
- Aggregate: When using the
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
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
Column to use to compute the quantile. Default is
Quantile to compute. Must be between
Computation method. Default is
- 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
qpoints are less than.
Number of centroids to use when compressing the dataset.
A larger number produces a more accurate result at the cost of increased memory requirements.
Input data. Default is piped-forward data (
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")
Was this page helpful?
Thank you for your feedback!
Support and feedback
Thank you for being part of our community! We welcome and encourage your feedback and bug reports for Flux and this documentation. To find support, use the following resources:
Customers with an annual or support contract can contact InfluxData Support.