Labels: Add DropMetricName function, used in PromQL (#13446)

This function is called very frequently when executing PromQL functions,
and we can do it much more efficiently inside Labels.

In the common case that `__name__` comes first in the labels, we simply
re-point to start at the next label, which is nearly free.

`DropMetricName` is now so cheap I removed the cache - benchmarks show
everything still goes faster.

Signed-off-by: Bryan Boreham <bjboreham@gmail.com>

model/labels/labels.go

@@ -342,6 +342,19 @@ func (ls Labels) Validate(f func(l Label) error) error {
 	return nil
 }
 
+// DropMetricName returns Labels with "__name__" removed.
+func (ls Labels) DropMetricName() Labels {
+	for i, l := range ls {
+		if l.Name == MetricName {
+			if i == 0 { // Make common case fast with no allocations.
+				return ls[1:]
+			}
+			return append(ls[:i], ls[i+1:]...)
+		}
+	}
+	return ls
+}
+
 // InternStrings calls intern on every string value inside ls, replacing them with what it returns.
 func (ls *Labels) InternStrings(intern func(string) string) {
 	for i, l := range *ls {

model/labels/labels_stringlabels.go

@@ -429,6 +429,27 @@ func (ls Labels) Validate(f func(l Label) error) error {
 	return nil
 }
 
+// DropMetricName returns Labels with "__name__" removed.
+func (ls Labels) DropMetricName() Labels {
+	for i := 0; i < len(ls.data); {
+		lName, i2 := decodeString(ls.data, i)
+		size, i2 := decodeSize(ls.data, i2)
+		i2 += size
+		if lName == MetricName {
+			if i == 0 { // Make common case fast with no allocations.
+				ls.data = ls.data[i2:]
+			} else {
+				ls.data = ls.data[:i] + ls.data[i2:]
+			}
+			break
+		} else if lName[0] > MetricName[0] { // Stop looking if we've gone past.
+			break
+		}
+		i = i2
+	}
+	return ls
+}
+
 // InternStrings calls intern on every string value inside ls, replacing them with what it returns.
 func (ls *Labels) InternStrings(intern func(string) string) {
 	ls.data = intern(ls.data)

model/labels/labels_test.go

@@ -447,6 +447,12 @@ func TestLabels_Get(t *testing.T) {
 	require.Equal(t, "222", FromStrings("aaaa", "111", "bbb", "222").Get("bbb"))
 }
 
+func TestLabels_DropMetricName(t *testing.T) {
+	require.True(t, Equal(FromStrings("aaa", "111", "bbb", "222"), FromStrings("aaa", "111", "bbb", "222").DropMetricName()))
+	require.True(t, Equal(FromStrings("aaa", "111"), FromStrings(MetricName, "myname", "aaa", "111").DropMetricName()))
+	require.True(t, Equal(FromStrings("__aaa__", "111", "bbb", "222"), FromStrings("__aaa__", "111", MetricName, "myname", "bbb", "222").DropMetricName()))
+}
+
 // BenchmarkLabels_Get was written to check whether a binary search can improve the performance vs the linear search implementation
 // The results have shown that binary search would only be better when searching last labels in scenarios with more than 10 labels.
 // In the following list, `old` is the linear search while `new` is the binary search implementation (without calling sort.Search, which performs even worse here)

promql/engine.go

@@ -1076,7 +1076,7 @@ type EvalNodeHelper struct {
 	Out Vector
 
 	// Caches.
-	// DropMetricName and label_*.
+	// label_*.
 	Dmn map[uint64]labels.Labels
 	// funcHistogramQuantile for classic histograms.
 	signatureToMetricWithBuckets map[string]*metricWithBuckets
@@ -1101,21 +1101,6 @@ func (enh *EvalNodeHelper) resetBuilder(lbls labels.Labels) {
 	}
 }
 
-// DropMetricName is a cached version of DropMetricName.
-func (enh *EvalNodeHelper) DropMetricName(l labels.Labels) labels.Labels {
-	if enh.Dmn == nil {
-		enh.Dmn = make(map[uint64]labels.Labels, len(enh.Out))
-	}
-	h := l.Hash()
-	ret, ok := enh.Dmn[h]
-	if ok {
-		return ret
-	}
-	ret = dropMetricName(l)
-	enh.Dmn[h] = ret
-	return ret
-}
-
 // rangeEval evaluates the given expressions, and then for each step calls
 // the given funcCall with the values computed for each expression at that
 // step. The return value is the combination into time series of all the
@@ -1492,7 +1477,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, annotations.Annotatio
 			// vector functions, the only change needed is to drop the
 			// metric name in the output.
 			if e.Func.Name != "last_over_time" {
-				metric = dropMetricName(metric)
+				metric = metric.DropMetricName()
 			}
 			ss := Series{
 				Metric: metric,
@@ -1624,7 +1609,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, annotations.Annotatio
 		mat := val.(Matrix)
 		if e.Op == parser.SUB {
 			for i := range mat {
-				mat[i].Metric = dropMetricName(mat[i].Metric)
+				mat[i].Metric = mat[i].Metric.DropMetricName()
 				for j := range mat[i].Floats {
 					mat[i].Floats[j].F = -mat[i].Floats[j].F
 				}
@@ -2370,7 +2355,7 @@ func (ev *evaluator) VectorBinop(op parser.ItemType, lhs, rhs Vector, matching *
 		}
 		metric := resultMetric(ls.Metric, rs.Metric, op, matching, enh)
 		if returnBool {
-			metric = enh.DropMetricName(metric)
+			metric = metric.DropMetricName()
 		}
 		insertedSigs, exists := matchedSigs[sig]
 		if matching.Card == parser.CardOneToOne {
@@ -2492,7 +2477,7 @@ func (ev *evaluator) VectorscalarBinop(op parser.ItemType, lhs Vector, rhs Scala
 			lhsSample.F = float
 			lhsSample.H = histogram
 			if shouldDropMetricName(op) || returnBool {
-				lhsSample.Metric = enh.DropMetricName(lhsSample.Metric)
+				lhsSample.Metric = lhsSample.Metric.DropMetricName()
 			}
 			enh.Out = append(enh.Out, lhsSample)
 		}
@@ -2500,10 +2485,6 @@ func (ev *evaluator) VectorscalarBinop(op parser.ItemType, lhs Vector, rhs Scala
 	return enh.Out
 }
 
-func dropMetricName(l labels.Labels) labels.Labels {
-	return labels.NewBuilder(l).Del(labels.MetricName).Labels()
-}
-
 // scalarBinop evaluates a binary operation between two Scalars.
 func scalarBinop(op parser.ItemType, lhs, rhs float64) float64 {
 	switch op {

promql/functions.go

@@ -445,7 +445,7 @@ func funcClamp(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper
 	}
 	for _, el := range vec {
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      math.Max(min, math.Min(max, el.F)),
 		})
 	}
@@ -458,7 +458,7 @@ func funcClampMax(vals []parser.Value, args parser.Expressions, enh *EvalNodeHel
 	max := vals[1].(Vector)[0].F
 	for _, el := range vec {
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      math.Min(max, el.F),
 		})
 	}
@@ -471,7 +471,7 @@ func funcClampMin(vals []parser.Value, args parser.Expressions, enh *EvalNodeHel
 	min := vals[1].(Vector)[0].F
 	for _, el := range vec {
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      math.Max(min, el.F),
 		})
 	}
@@ -493,7 +493,7 @@ func funcRound(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper
 	for _, el := range vec {
 		f := math.Floor(el.F*toNearestInverse+0.5) / toNearestInverse
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      f,
 		})
 	}
@@ -797,7 +797,7 @@ func simpleFunc(vals []parser.Value, enh *EvalNodeHelper, f func(float64) float6
 	for _, el := range vals[0].(Vector) {
 		if el.H == nil { // Process only float samples.
 			enh.Out = append(enh.Out, Sample{
-				Metric: enh.DropMetricName(el.Metric),
+				Metric: el.Metric.DropMetricName(),
 				F:      f(el.F),
 			})
 		}
@@ -943,7 +943,7 @@ func funcTimestamp(vals []parser.Value, args parser.Expressions, enh *EvalNodeHe
 	vec := vals[0].(Vector)
 	for _, el := range vec {
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      float64(el.T) / 1000,
 		})
 	}
@@ -1057,7 +1057,7 @@ func funcHistogramCount(vals []parser.Value, args parser.Expressions, enh *EvalN
 			continue
 		}
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      sample.H.Count,
 		})
 	}
@@ -1074,7 +1074,7 @@ func funcHistogramSum(vals []parser.Value, args parser.Expressions, enh *EvalNod
 			continue
 		}
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      sample.H.Sum,
 		})
 	}
@@ -1107,7 +1107,7 @@ func funcHistogramStdDev(vals []parser.Value, args parser.Expressions, enh *Eval
 		variance += cVariance
 		variance /= sample.H.Count
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      math.Sqrt(variance),
 		})
 	}
@@ -1140,7 +1140,7 @@ func funcHistogramStdVar(vals []parser.Value, args parser.Expressions, enh *Eval
 		variance += cVariance
 		variance /= sample.H.Count
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      variance,
 		})
 	}
@@ -1159,7 +1159,7 @@ func funcHistogramFraction(vals []parser.Value, args parser.Expressions, enh *Ev
 			continue
 		}
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      histogramFraction(lower, upper, sample.H),
 		})
 	}
@@ -1230,7 +1230,7 @@ func funcHistogramQuantile(vals []parser.Value, args parser.Expressions, enh *Ev
 		}
 
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(sample.Metric),
+			Metric: sample.Metric.DropMetricName(),
 			F:      histogramQuantile(q, sample.H),
 		})
 	}
@@ -1440,7 +1440,7 @@ func dateWrapper(vals []parser.Value, enh *EvalNodeHelper, f func(time.Time) flo
 	for _, el := range vals[0].(Vector) {
 		t := time.Unix(int64(el.F), 0).UTC()
 		enh.Out = append(enh.Out, Sample{
-			Metric: enh.DropMetricName(el.Metric),
+			Metric: el.Metric.DropMetricName(),
 			F:      f(t),
 		})
 	}