* metricsql: add support of using keep_metric_names for binary operations
This should help to avoid confusion with queries like one in the issue #3710.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* wip
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@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
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>
* 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>
- 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
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
* Document changes_prometheus(), increase_prometheus() and delta_prometheus() functions.
* Simplify their implementation
* Mention these functions in docs/CHANGELOG.md
