* vmselect/promql: check for deadline in `count_values` fn
`count_values` could be very slow during the data processing.
Checking for deadline between iterations supposed to reduce
probability of exceeding `search.maxQueryDuration`.
The change also adds a new trace record, which captures the time
spent in aggregation function. Before that, the trace for aggr funcs
could be confusing since it doesn't account for all the places where
time was spent.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
---------
Signed-off-by: hagen1778 <roman@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>
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>
