app/vmselect: add -search.minStalenessInterval command-line flag for removing gaps on graphs built from time series with irregular duration between samples

Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/426
This commit is contained in:
Aliaksandr Valialkin 2020-04-20 19:41:59 +03:00
parent fe57d46687
commit 9ebc937685
4 changed files with 17 additions and 1 deletions

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@ -923,6 +923,9 @@ The most interesting metrics are:
If this removes gaps on the graphs, then it is likely data with timestamps older than `-search.cacheTimestampOffset`
is ingested into VictoriaMetrics. Make sure that data sources have synchronized time with VictoriaMetrics.
If the gaps are related to irregular intervals between samples, then try adjusting `-search.minStalenessInterval` command-line flag
to value close to the maximum interval between samples.
### Backfilling
VictoriaMetrics accepts historical data in arbitrary order of time via [any supported ingestion method](#how-to-import-time-series-data).

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@ -33,7 +33,7 @@ var (
"The value is dynamically detected from interval between time series datapoints if not set. It can be overridden on per-query basis via max_lookback arg. "+
"See also '-search.maxStalenessInterval' flag, which has the same meaining due to historical reasons")
maxStalenessInterval = flag.Duration("search.maxStalenessInterval", 0, "The maximum interval for staleness calculations. "+
"By default it is automatically calculated from the median interval between samples. This flag can be useful for tuning "+
"By default it is automatically calculated from the median interval between samples. This flag could be useful for tuning "+
"Prometheus data model closer to Influx-style data model. See https://prometheus.io/docs/prometheus/latest/querying/basics/#staleness for details. "+
"See also '-search.maxLookback' flag, which has the same meanining due to historical reasons")
)

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@ -1,6 +1,7 @@
package promql
import (
"flag"
"fmt"
"math"
"strings"
@ -14,6 +15,10 @@ import (
"github.com/valyala/histogram"
)
var minStalenessInterval = flag.Duration("search.minStalenessInterval", 0, "The mimimum interval for staleness calculations. "+
"This flag could be useful for removing gaps on graphs generated from time series with irregular intervals between samples. "+
"See also '-search.maxStalenessInterval'")
var rollupFuncs = map[string]newRollupFunc{
// Standard rollup funcs from PromQL.
// See funcs accepting range-vector on https://prometheus.io/docs/prometheus/latest/querying/functions/ .
@ -451,6 +456,11 @@ func (rc *rollupConfig) doInternal(dstValues []float64, tsm *timeseriesMap, valu
if rc.LookbackDelta > 0 && maxPrevInterval > rc.LookbackDelta {
maxPrevInterval = rc.LookbackDelta
}
if *minStalenessInterval > 0 {
if msi := minStalenessInterval.Milliseconds(); msi > 0 && maxPrevInterval < msi {
maxPrevInterval = msi
}
}
window := rc.Window
if window <= 0 {
window = rc.Step

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@ -923,6 +923,9 @@ The most interesting metrics are:
If this removes gaps on the graphs, then it is likely data with timestamps older than `-search.cacheTimestampOffset`
is ingested into VictoriaMetrics. Make sure that data sources have synchronized time with VictoriaMetrics.
If the gaps are related to irregular intervals between samples, then try adjusting `-search.minStalenessInterval` command-line flag
to value close to the maximum interval between samples.
### Backfilling
VictoriaMetrics accepts historical data in arbitrary order of time via [any supported ingestion method](#how-to-import-time-series-data).