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.
The fix makes the binary comparison func to check for NaNs
before executing the actual comparison. This prevents VM
to return values for non-existing samples for expressions
which contain bool comparisons. Please see added test
for example.
It appeared, that `testRowsEqual` NaN comparison was incorrect.
The fix caused some tests to fail. Please see the change and
tests updated.
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>
* app/vmselect: make sorting for query result similar to Prometheus
Updated sorting allows to get the order of series in result similar or equal
to what Prometheus returns.
The change is needed for compatibility reasons.
* Update app/vmselect/promql/exec_test.go
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
- Support durations anywhere in MetricsQL queries. E.g. sum_over_time(m[1h])/1h is equivalent to sum_over_time(m[1h])/3600
- Support durations without suffix. E.g. rate(m[300]) is equivalent to rate(m[5m])
The first and the last buckets are usually `[0 ... leMin]` and `(leMax ... +Inf)`. If they are merged with adjancent buckets,
then the resulting accuracy can suffer.
This should prevent from double counting for time series at the time when it changes label.
The most common case is in K8S, which changes pod uid label with each new deployment.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/748
This reverts commit bb61a4769b.
Reason for revert: the previous behavior for VictoriaMetrics is easier to understand and use by users -
functions, which don't change the meaning of the time series shouldn't drop metric name.
Now the following functions do not drop metric name:
* clamp_min
* clamp_max
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/674
This reverts commit e5202a4eae.
Reason for revert: the previous behavior for VictoriaMetrics is easier to understand and use by users -
functions, which don't change the meaning of the time series shouldn't drop metric name.
Now the following functions do not drop metric name:
* max_over_time
* min_over_time
* avg_over_time
* quantile_over_time
* geomean_over_time
* mode_over_time
* holt_winters
* predict_linear
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/674
These functions returns the number of raw samples that don't exceed `le` or are bigger than `gt`.
These functions are complement to already existing `share_le_over_time(m[d], le)` and `share_gt_over_time(m[d], gt)`.
