`median_over_time` is handled by predefined WITH template in MetricsQL library which translates it to `quantile_over_time(0.5)`
This makes it impossble to use `median_over_time` as a usual rollup function for `aggr_over_time`.
See: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5034
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* metricsql: support optional 2nd argument for rollup functions
Support optional 2nd argument `min`, `max` or `avg` for rollup functions:
* rollup
* rollup_delta
* rollup_deriv
* rollup_increase
* rollup_rate
* rollup_scrape_interval
If second argument is passed, then rollup function will return only the selected aggregation type.
This change can be useful for situations where only one type of rollup calculation is needed.
For example, `rollup_rate(requests_total[5m], "max")`.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Previously too short lookbehind window d for rate(m[d]) could be automatically extended
if it didn't cover at least two raw samples. This was needed in order to guarantee
non-empty results from rate(m[d]) on short time ranges.
Now the lookbehind window isn't extended if it is set explicitly,
since it is expected that the user knows what he is doing.
The lookbehind window continues to be extended when needed if it isn't set explicitly.
For example, in the case of rate(m).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3483
The workaround was introduced to fix https://github.com/VictoriaMetrics/VictoriaMetrics/issues/962.
However, it didn't prove itself useful. Instead, it is recommended using `increase_pure` function.
Removing the workaround makes VM to produce accurate results when calculating
`delta` or `increase` functions over slow-changing counters with vary intervals
between data points.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The change allows to specify default value for `getScrapeInterval`
function when actual interval can't be calculated.
Before the change, function were returning `maxSilenceInterval` (5m)
in such cases, which may be not correct for instant queries processing.
The specific scenario where using `maxSilenceInterval` caused issues
is the following:
1. Series becomes stale;
2. Client (in this case vmalert) continues to request series every 15s;
3. Database returns empty results as expected;
4. But at some specific moment of time database returns datapoints from `now()-5m`,
because lookback window was extended to `maxSilenceInterval`.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* Document changes_prometheus(), increase_prometheus() and delta_prometheus() functions.
* Simplify their implementation
* Mention these functions in docs/CHANGELOG.md
The list of functions, which can adjust lookbehind window is more limited than the rest of functions,
so it is better from maintainability and readability PoV using the allowlist instead of blocklist.
It is expected that the `deriv(m[d])` returns non-empty value if the lookbehind window `d`
contains less than 2 samples in the same way as `rate()` does.
This is a follow-up after 3e084be06b .
Previously, `predict_linear` returned slightly different results comparing
to Prometheus. The change makes linear regression algorithm compatible
with Prometheus.
`deriv` was excluded from the list of functions which can adjust the time
window for the same reasons.
Adjustment results into discrepancy between Prometheus and VM on time windows
smaller than scrape interval.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The fix will always return zero if received set of items consists of one
element only, which also means no deviation.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The change affects `count/stddev/stdvar_over_time` funcs and makes
them to return NaN instead of zero when there is no datapoints
in a time window.
This is needed for improving compatibility with Prometheus.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The removed fast path optimisations weren't consistent with
`quantile` function behavior and results into discrepancy.
Specifically, results didn't match in cases when:
* 0 < phi > 1;
* values contain only one element.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* app/vmselect: `quantile` func compatiblity with Prometheus
The `quantile` func was previously calculated by https://github.com/valyala/histogram
package. The result of such calculation was always the closest real value to
requested quantile. While in Prometheus implementation interpolation is used.
Such difference may result into discrepancy in output between Prometheus and
VictoriaMetrics.
This commit adds a Prometheus-like `quantile` function. It also used by other
functions which depend on it, such as `quantiles`, `quantile_over_time`, `median` etc.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1625
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* app/vmselect: `quantile` review fixes
* quantile functions were split into multiple to provide
different API for already sorted data;
* float64sPool is used for reducing allocations. Items in pool may have
different sizes, but defining a new pool was complicates due to name collisions;
Signed-off-by: hagen1778 <roman@victoriametrics.com>
