* 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>
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.
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>
- 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 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>
- Use binary search instead of linear scan when locating the run of smallest timestamps
in blocks with intersected time ranges. This should improve performance
when merging blocks with big number of samples
- Skip samples with duplicate timestamps. This should increase query performance
in cluster version of VictoriaMetrics with the enabled replication.
- 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
Production experience shows that 100k is too big for /api/v1/series .
It leads to increased CPU usage when Grafana queries /api/v1/series over VictoriaMetrics
with big number of time series during auto-completion and when modifying template variables.
Previously SearchMetricNames was returning unmarshaled metric names.
This wasn't great for vmstorage, which should spend additional CPU time
for marshaling the metric names before sending them to vmselect.
While at it, remove possible duplicate metric names, which could occur when
multiple samples for new time series are ingested via concurrent requests.
Also sort the metric names before returning them to the client.
This simplifies debugging of the returned metric names across repeated requests to /api/v1/series
