app/vmselect/promql: randomize the static selection of time series returned from limitk()

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.

app/vmselect/promql/aggr.go

@@ -11,6 +11,7 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
 	"github.com/VictoriaMetrics/metrics"
 	"github.com/VictoriaMetrics/metricsql"
+	xxhash "github.com/cespare/xxhash/v2"
 )
 
 var aggrFuncs = map[string]aggrFunc{
@@ -1012,9 +1013,26 @@ func aggrFuncLimitK(afa *aggrFuncArg) ([]*timeseries, error) {
 	afe := func(tss []*timeseries, modifier *metricsql.ModifierExpr) []*timeseries {
 		// Sort series by metricName in order to get consistent set of output series
 		// across multiple calls to limitk() function.
-		sort.Slice(tss, func(i, j int) bool {
-			return metricNameLess(&tss[i].MetricName, &tss[j].MetricName)
+		// Sort series by hash in order to guarantee uniform selection across series.
+		type hashSeries struct {
+			h  uint64
+			ts *timeseries
+		}
+		hss := make([]hashSeries, len(tss))
+		d := xxhash.New()
+		for i, ts := range tss {
+			h := getHash(d, &ts.MetricName)
+			hss[i] = hashSeries{
+				h:  h,
+				ts: ts,
+			}
+		}
+		sort.Slice(hss, func(i, j int) bool {
+			return hss[i].h < hss[j].h
 		})
+		for i, hs := range hss {
+			tss[i] = hs.ts
+		}
 		if len(tss) > maxK {
 			tss = tss[:maxK]
 		}
@@ -1032,6 +1050,17 @@ func aggrFuncLimitK(afa *aggrFuncArg) ([]*timeseries, error) {
 	return aggrFuncExt(afe, args[1], &afa.ae.Modifier, afa.ae.Limit, true)
 }
 
+func getHash(d *xxhash.Digest, mn *storage.MetricName) uint64 {
+	d.Reset()
+	_, _ = d.Write(mn.MetricGroup)
+	for _, tag := range mn.Tags {
+		_, _ = d.Write(tag.Key)
+		_, _ = d.Write(tag.Value)
+	}
+	return d.Sum64()
+
+}
+
 func aggrFuncQuantiles(afa *aggrFuncArg) ([]*timeseries, error) {
 	args := afa.args
 	if len(args) < 3 {