Commit 40f51855 authored by Björn Rabenstein's avatar Björn Rabenstein Committed by GitHub

Merge pull request #487 from brian-brazil/quantile

Document quantile and quantile_over_time
parents 84a438a3 188e2a75
...@@ -325,6 +325,7 @@ over time and return an instant vector with per-series aggregation results: ...@@ -325,6 +325,7 @@ over time and return an instant vector with per-series aggregation results:
* `max_over_time(range-vector)`: the maximum value of all points in the specified interval. * `max_over_time(range-vector)`: the maximum value of all points in the specified interval.
* `sum_over_time(range-vector)`: the sum of all values in the specified interval. * `sum_over_time(range-vector)`: the sum of all values in the specified interval.
* `count_over_time(range-vector)`: the count of all values in the specified interval. * `count_over_time(range-vector)`: the count of all values in the specified interval.
* `quantile_over_time(scalar, range-vector)`: the φ-quantile (0 ≤ φ ≤ 1) of the values in the specified interval.
Note that all values in the specified interval have the same weight in the Note that all values in the specified interval have the same weight in the
aggregation even if the values are not equally spaced throughout the interval. aggregation even if the values are not equally spaced throughout the interval.
...@@ -189,19 +189,20 @@ vector of fewer elements with aggregated values: ...@@ -189,19 +189,20 @@ vector of fewer elements with aggregated values:
* `count_values` (count number of elements with the same value) * `count_values` (count number of elements with the same value)
* `bottomk` (smallest k elements by sample value) * `bottomk` (smallest k elements by sample value)
* `topk` (largest k elements by sample value) * `topk` (largest k elements by sample value)
* `quantile` (calculate φ-quantile (0 ≤ φ ≤ 1) over dimensions)
These operators can either be used to aggregate over **all** label dimensions These operators can either be used to aggregate over **all** label dimensions
or preserve distinct dimensions by including a `without` or `by` clause. or preserve distinct dimensions by including a `without` or `by` clause.
<aggr-op>([parameter,] <vector expression>) [without|by (<label list>)] [keep_common] <aggr-op>([parameter,] <vector expression>) [without|by (<label list>)] [keep_common]
`parameter` is only required for `count_values`,`topk` and `bottomk`. `without` `parameter` is only required for `count_values`, `quantile`, `topk` and
removes the listed labels from the result vector, while all other labels are `bottomk`. `without` removes the listed labels from the result vector, while
preserved the output. `by` does the opposite and drops labels that are not all other labels are preserved the output. `by` does the opposite and drops
listed in the `by` clause, even if their label values are identical between all labels that are not listed in the `by` clause, even if their label values are
elements of the vector. The `keep_common` clause allows keeping those extra identical between all elements of the vector. The `keep_common` clause allows
labels (labels that are identical between elements, but not in the `by` keeping those extra labels (labels that are identical between elements, but not
clause). in the `by` clause).
`count_values` outputs one time series per unique sample value. Each series has `count_values` outputs one time series per unique sample value. Each series has
an additional label. The name of that label is given by the aggregation an additional label. The name of that label is given by the aggregation
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