promql: Add support for predict_linear(my_timeseries[1h], 7200)

This will give a prediction for the value of my_timeseries in 2 hours,
based on the last hour of data.

promql/functions.go

@@ -474,6 +474,43 @@ func funcDeriv(ev *evaluator, args Expressions) Value {
 	return resultVector
 }
 
+// === predict_linear(node ExprMatrix, k ExprScalar) Vector ===
+func funcPredictLinear(ev *evaluator, args Expressions) Value {
+	vector := funcDeriv(ev, args[0:1]).(Vector)
+	duration := clientmodel.SampleValue(clientmodel.SampleValue(ev.evalFloat(args[1])))
+
+	excludedLabels := map[clientmodel.LabelName]struct{}{
+		clientmodel.MetricNameLabel: {},
+	}
+
+	// Calculate predicted delta over the duration.
+	signatureToDelta := map[uint64]clientmodel.SampleValue{}
+	for _, el := range vector {
+		signature := clientmodel.SignatureWithoutLabels(el.Metric.Metric, excludedLabels)
+		signatureToDelta[signature] = el.Value * duration
+	}
+
+	// add predicted delta to last value.
+	matrixBounds := ev.evalMatrixBounds(args[0])
+	outVec := make(Vector, 0, len(signatureToDelta))
+	for _, samples := range matrixBounds {
+		if len(samples.Values) < 2 {
+			continue
+		}
+		signature := clientmodel.SignatureWithoutLabels(samples.Metric.Metric, excludedLabels)
+		delta, ok := signatureToDelta[signature]
+		if ok {
+			samples.Metric.Delete(clientmodel.MetricNameLabel)
+			outVec = append(outVec, &Sample{
+				Metric:    samples.Metric,
+				Value:     delta + samples.Values[1].Value,
+				Timestamp: ev.Timestamp,
+			})
+		}
+	}
+	return outVec
+}
+
 // === histogram_quantile(k ExprScalar, vector ExprVector) Vector ===
 func funcHistogramQuantile(ev *evaluator, args Expressions) Value {
 	q := clientmodel.SampleValue(ev.evalFloat(args[0]))
@@ -688,6 +725,12 @@ var functions = map[string]*Function{
 		ReturnType: ExprVector,
 		Call:       funcMinOverTime,
 	},
+	"predict_linear": {
+		Name:       "predict_linear",
+		ArgTypes:   []ExprType{ExprMatrix, ExprScalar},
+		ReturnType: ExprVector,
+		Call:       funcPredictLinear,
+	},
 	"rate": {
 		Name:       "rate",
 		ArgTypes:   []ExprType{ExprMatrix},

promql/testdata/functions.test

@@ -62,3 +62,33 @@ load 5m
 eval instant at 50m increase(http_requests[50m])
 	{path="/foo"} 100
 	{path="/bar"}  90
+
+
+clear
+
+# Tests for deriv() and predict_linear().
+load 5m
+	testcounter_reset_middle	0+10x4 0+10x5
+	http_requests{job="app-server", instance="1", group="canary"}		0+80x10
+
+# Deriv should return the same as rate in simple cases.
+eval instant at 50m rate(http_requests{group="canary", instance="1", job="app-server"}[60m])
+	{group="canary", instance="1", job="app-server"} 0.26666666666666666
+
+eval instant at 50m deriv(http_requests{group="canary", instance="1", job="app-server"}[60m])
+	{group="canary", instance="1", job="app-server"} 0.26666666666666666
+
+# Deriv should return correct result.
+eval instant at 50m deriv(testcounter_reset_middle[100m])
+	{} 0.010606060606060607
+
+# Predict_linear should return correct result.
+eval instant at 50m predict_linear(testcounter_reset_middle[100m], 3600)
+	{} 88.181818181818185200
+
+# Predict_linear is syntactic sugar around deriv.
+eval instant at 50m predict_linear(http_requests[50m], 3600) - (http_requests + deriv(http_requests[50m]) * 3600)
+	{group="canary", instance="1", job="app-server"} 0
+
+eval instant at 50m predict_linear(testcounter_reset_middle[100m], 3600) - (testcounter_reset_middle + deriv(testcounter_reset_middle[100m]) * 3600)
+	{} 0

promql/testdata/legacy.test

@@ -238,10 +238,6 @@ eval instant at 50m delta(http_requests{group="canary", instance="1", job="app-s
 eval instant at 50m rate(http_requests{group="canary", instance="1", job="app-server"}[60m])
 	{group="canary", instance="1", job="app-server"} 0.26666666666666666
 
-# Deriv should return the same as rate in simple cases.
-eval instant at 50m deriv(http_requests{group="canary", instance="1", job="app-server"}[60m])
-	{group="canary", instance="1", job="app-server"} 0.26666666666666666
-
 # Counter resets at in the middle of range are handled correctly by rate().
 eval instant at 50m rate(testcounter_reset_middle[60m])
 	{} 0.03
@@ -251,10 +247,6 @@ eval instant at 50m rate(testcounter_reset_middle[60m])
 eval instant at 50m rate(testcounter_reset_end[5m])
 	{} 0
 
-# Deriv should return correct result.
-eval instant at 50m deriv(testcounter_reset_middle[100m])
-	{} 0.010606060606060607
-
 # count_scalar for a non-empty vector should return scalar element count.
 eval instant at 50m count_scalar(http_requests)
 	8