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
Previously empty series (e.g. series with all NaN samples) were passed to aggregate functions.
Such series must be ingored by all the aggregate functions.
So it is better from consistency PoV filtering out empty series before applying aggregate functions.
* app/vmselect: ignore empty series for `limit_offset`
VictoriaMetrics doesn't return empty series (with all NaN values) to
the user. But such series are filtered after transform functions.
It means `limit_offset` will account for empty series as well.
For example, let's consider following data set:
```
time series:
foo{label="1"} NaN, NaN, NaN, NaN // empty series
foo{label="2"} 1, 2, 3, 4
foo{label="3"} 4, 3, 2, 1
```
When user requests all series for metric `foo` the empty series
will be filtered out:
```
/query=foo:
foo{label="v2"} 1, 2, 3, 4
foo{label="v3"} 4, 3, 2, 1
```
But `limit_offset(1, 1, foo)` is applied to original series, not filtered yet.
So it will return `foo{label="v2"}` (skips the first in list)
```
/query=limit_offset(1, 1, foo):
foo{label="v2"} 1, 2, 3, 4
```
Expected result would be to apply `limit_offset` to already filtered list,
so in result we receive `foo{label="v3"}`:
```
/query=limit_offset(1, 1, foo):
foo{label="v3"} 4, 3, 2, 1
```
The change does exactly that - filters empty series before applying `limit_offset`.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* app/vmselect: ignore empty series for `limit_offset`
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Signed-off-by: hagen1778 <roman@victoriametrics.com>
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>
* vmselect/promql: add alphanumeric sort by label (sort_by_label_numeric)
* vmselect/promql: fix tests, add documentation
* vmselect/promql: update test
* vmselect/promql: update for alphanumeric sorting, fix tests
* vmselect/promql: remove comments
* vmselect/promql: cleanup
* vmselect/promql: avoid memory allocations, update functions descriptions
* vmselect/promql: make linter happy (remove ineffectual assigment)
* vmselect/promql: add test case, fix behavior when strings are equal
* vendor: update github.com/VictoriaMetrics/metricsql from v0.44.1 to v0.45.0
this adds support for sort_by_label_numeric and sort_by_label_numeric_desc functions
* wip
* lib/promscrape: read response body into memory in stream parsing mode before parsing it
This reduces scrape duration for targets returning big responses.
The response body was already read into memory in stream parsing mode before this change,
so this commit shouldn't increase memory usage.
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Note that the parallel execution of `union()` args may take more memory and CPU time
than the sequential execution if args contain heavy queries, which may load all the available CPU,
disk and memory resources and vmselect and vmstorage levels.
- Use getScalar() function for obtaining the expected scalar from phi arg
- Reduce the error message returned to the user when incorrect phi is passed to histogram_quantiles
- Improve the description of this bugfix in the docs/CHANGELOG.md
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3026
The ioutil.{Read|Write}File is deprecated since Go1.16 -
see https://tip.golang.org/doc/go1.16#ioutil
VictoriaMetrics needs at least Go1.18, so it is safe to remove ioutil usage
from source code.
This is a follow-up for 02ca2342ab
* Explicitly store a pointer to UserReadableError in the error interface.
Previously Go automatically converted the value to a pointer before storing in the error interface.
* Add Unwrap() method to UserReadableError, so it can be used transparently with the other code,
which calls errors.Is() and errors.As().
* Document the change in docs/CHANGELOG.md
When read query fails, VM returns rich error message with
all the details. While these details might be useful
for debugging specific cases, they're usually too verbose
for users.
Introducing a new error type `UserReadableError` is supposed
to allow to return to user only the most important parts
of the error trace. This supposed to improve error readability
in web interfaces such as VMUI or Grafana.
The full error trace is still logged with the full context
and can be found in vmselect logs.
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>
- show dates in human-readable format, e.g. 2022-05-07, instead of a numeric value
- limit the maximum length of queries and filters shown in trace messages
This should prevent from `duplicate time series` errors when executing the following query:
kube_pod_container_resource_requests{resource="cpu"} * on (namespace,pod) group_left() (kube_pod_status_phase{phase=~"Pending|Running"}==1)
where `kube_pod_status_phase{phase=~"Pending|Running"}==1` filters out diplicate time series
Previously bytesutil.Resize() was copying the original byte slice contents to a newly allocated slice.
This wasted CPU cycles and memory bandwidth in some places, where the original slice contents wasn't needed
after slize resizing. Switch such places to bytesutil.ResizeNoCopy().
Rename the original bytesutil.Resize() function to bytesutil.ResizeWithCopy() for the sake of improved readability.
Additionally, allocate new slice with `make()` instead of `append()`. This guarantees that the capacity of the allocated slice
exactly matches the requested size. The `append()` could return a slice with bigger capacity as an optimization for further `append()` calls.
This could result in excess memory usage when the returned byte slice was cached (for instance, in lib/blockcache).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2007
* Document changes_prometheus(), increase_prometheus() and delta_prometheus() functions.
* Simplify their implementation
* Mention these functions in docs/CHANGELOG.md
Sort series by a hash calculated from the series labels. This should guarantee "random" selection of the returned time series.
Previously the selection could be biased, since time series were sorted alphabetically by label names and label values.
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.
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>
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>
* 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>
This option allows reducing CPU usage a bit when VictoriaMetrics is used
for collecting and processing non-Prometheus data. For example, InfluxDB line protocol, Graphite, OpenTSDB, CSV, etc.
This reverts commit 94dfcb6747a3b29a11d14e71bea21a2312bb6346.
It is better to remove staleness marks (decimal.StaleNaN) before calling rollupConfig.Do, e.g. in preFunc
Prometheus stalenss marks shouldn't be changed in removeCounterResets. Otherwise they will be converted to an ordinary NaN values,
which couldn't be removed in dropStaleNaNs() function later. This may result in incorrect calculations for rollup functions.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1526
- 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])
Due to staleness handling, increase_pure were using incorrect previous value
during calculation in cases where series disappears for period longer
than staleness period and then returns back. The fix suppose to account
for a real datapoint value before staleness takes place. The fix should
remove unexpected spikes while using `increase_pure` for staled series.
