app/vmselect/promql: add increases_over_time and decreases_over_time functions

`increases_over_time(q[d])` returns the number of `q` increases during the given duration `d`.
`decreases_over_time(q[d])` returns the number of `q` decreases during the given duration `d`.

app/vmselect/promql/exec_test.go

@@ -2671,6 +2671,28 @@ func TestExecSuccess(t *testing.T) {
 		resultExpected := []netstorage.Result{r}
 		f(q, resultExpected)
 	})
+	t.Run(`increases_over_time`, func(t *testing.T) {
+		t.Parallel()
+		q := `increases_over_time(rand(0)[200s:10s])`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{11, 9, 9, 12, 9, 8},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
+	t.Run(`decreases_over_time`, func(t *testing.T) {
+		t.Parallel()
+		q := `decreases_over_time(rand(0)[200s:10s])`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{9, 11, 11, 8, 11, 12},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
 	t.Run(`limitk(-1)`, func(t *testing.T) {
 		t.Parallel()
 		q := `limitk(-1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`

app/vmselect/promql/rollup.go

@@ -43,6 +43,8 @@ var rollupFuncs = map[string]newRollupFunc{
 	"first_over_time":     newRollupFuncOneArg(rollupFirst),
 	"last_over_time":      newRollupFuncOneArg(rollupLast),
 	"distinct_over_time":  newRollupFuncOneArg(rollupDistinct),
+	"increases_over_time": newRollupFuncOneArg(rollupIncreases),
+	"decreases_over_time": newRollupFuncOneArg(rollupDecreases),
 	"integrate":           newRollupFuncOneArg(rollupIntegrate),
 	"ideriv":              newRollupFuncOneArg(rollupIderiv),
 	"lifetime":            newRollupFuncOneArg(rollupLifetime),
@@ -820,6 +822,37 @@ func rollupChanges(rfa *rollupFuncArg) float64 {
 	return float64(n)
 }
 
+func rollupIncreases(rfa *rollupFuncArg) float64 {
+	// There is no need in handling NaNs here, since they must be cleaned up
+	// before calling rollup funcs.
+	values := rfa.values
+	if len(values) == 0 {
+		if math.IsNaN(rfa.prevValue) {
+			return nan
+		}
+		return 0
+	}
+	prevValue := rfa.prevValue
+	if math.IsNaN(prevValue) {
+		prevValue = values[0]
+		values = values[1:]
+	}
+	if len(values) == 0 {
+		return 0
+	}
+	n := 0
+	for _, v := range values {
+		if v > prevValue {
+			n++
+		}
+		prevValue = v
+	}
+	return float64(n)
+}
+
+// `decreases_over_time` logic is the same as `resets` logic.
+var rollupDecreases = rollupResets
+
 func rollupResets(rfa *rollupFuncArg) float64 {
 	// There is no need in handling NaNs here, since they must be cleaned up
 	// before calling rollup funcs.

app/vmselect/promql/rollup_test.go

@@ -294,6 +294,8 @@ func TestRollupNewRollupFuncSuccess(t *testing.T) {
 	f("integrate", 61.0275)
 	f("distinct_over_time", 8)
 	f("ideriv", 0)
+	f("decreases_over_time", 5)
+	f("increases_over_time", 5)
 }
 
 func TestRollupNewRollupFuncError(t *testing.T) {