app/vmselect/promql: allow passing multiple args to aggregate functions such as avg(q1, q2, q3)

app/vmselect/promql/aggr.go

@@ -65,14 +65,25 @@ func getAggrFunc(s string) aggrFunc {
 
 func newAggrFunc(afe func(tss []*timeseries) []*timeseries) aggrFunc {
 	return func(afa *aggrFuncArg) ([]*timeseries, error) {
-		args := afa.args
-		if err := expectTransformArgsNum(args, 1); err != nil {
+		tss, err := getAggrTimeseries(afa.args)
+		if err != nil {
 			return nil, err
 		}
-		return aggrFuncExt(afe, args[0], &afa.ae.Modifier, afa.ae.Limit, false)
+		return aggrFuncExt(afe, tss, &afa.ae.Modifier, afa.ae.Limit, false)
 	}
 }
 
+func getAggrTimeseries(args [][]*timeseries) ([]*timeseries, error) {
+	if len(args) == 0 {
+		return nil, fmt.Errorf("expecting at least one arg")
+	}
+	tss := args[0]
+	for _, arg := range args[1:] {
+		tss = append(tss, arg...)
+	}
+	return tss, nil
+}
+
 func removeGroupTags(metricName *storage.MetricName, modifier *metricsql.ModifierExpr) {
 	groupOp := strings.ToLower(modifier.Op)
 	switch groupOp {
@@ -126,8 +137,8 @@ func aggrFuncExt(afe func(tss []*timeseries) []*timeseries, argOrig []*timeserie
 }
 
 func aggrFuncAny(afa *aggrFuncArg) ([]*timeseries, error) {
-	args := afa.args
-	if err := expectTransformArgsNum(args, 1); err != nil {
+	tss, err := getAggrTimeseries(afa.args)
+	if err != nil {
 		return nil, err
 	}
 	afe := func(tss []*timeseries) []*timeseries {
@@ -138,7 +149,7 @@ func aggrFuncAny(afa *aggrFuncArg) ([]*timeseries, error) {
 		// Only a single time series per group must be returned
 		limit = 1
 	}
-	return aggrFuncExt(afe, args[0], &afa.ae.Modifier, limit, true)
+	return aggrFuncExt(afe, tss, &afa.ae.Modifier, limit, true)
 }
 
 func aggrFuncGroup(tss []*timeseries) []*timeseries {
@@ -434,8 +445,8 @@ func aggrFuncMode(tss []*timeseries) []*timeseries {
 }
 
 func aggrFuncZScore(afa *aggrFuncArg) ([]*timeseries, error) {
-	args := afa.args
-	if err := expectTransformArgsNum(args, 1); err != nil {
+	tss, err := getAggrTimeseries(afa.args)
+	if err != nil {
 		return nil, err
 	}
 	afe := func(tss []*timeseries) []*timeseries {
@@ -476,7 +487,7 @@ func aggrFuncZScore(afa *aggrFuncArg) ([]*timeseries, error) {
 		}
 		return tss
 	}
-	return aggrFuncExt(afe, args[0], &afa.ae.Modifier, afa.ae.Limit, true)
+	return aggrFuncExt(afe, tss, &afa.ae.Modifier, afa.ae.Limit, true)
 }
 
 // modeNoNaNs returns mode for a.
@@ -811,13 +822,13 @@ func aggrFuncQuantile(afa *aggrFuncArg) ([]*timeseries, error) {
 }
 
 func aggrFuncMedian(afa *aggrFuncArg) ([]*timeseries, error) {
-	args := afa.args
-	if err := expectTransformArgsNum(args, 1); err != nil {
+	tss, err := getAggrTimeseries(afa.args)
+	if err != nil {
 		return nil, err
 	}
 	phis := evalNumber(afa.ec, 0.5)[0].Values
 	afe := newAggrQuantileFunc(phis)
-	return aggrFuncExt(afe, args[0], &afa.ae.Modifier, afa.ae.Limit, false)
+	return aggrFuncExt(afe, tss, &afa.ae.Modifier, afa.ae.Limit, false)
 }
 
 func newAggrQuantileFunc(phis []float64) func(tss []*timeseries) []*timeseries {

app/vmselect/promql/exec_test.go

@@ -3380,6 +3380,28 @@ func TestExecSuccess(t *testing.T) {
 		resultExpected := []netstorage.Result{r}
 		f(q, resultExpected)
 	})
+	t.Run(`sum(multi-args)`, func(t *testing.T) {
+		t.Parallel()
+		q := `sum(1, 2, 3)`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{6, 6, 6, 6, 6, 6},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
+	t.Run(`sum(union-args)`, func(t *testing.T) {
+		t.Parallel()
+		q := `sum((1, 2, 3))`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{1, 1, 1, 1, 1, 1},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
 	t.Run(`sum(scalar) by ()`, func(t *testing.T) {
 		t.Parallel()
 		q := `sum(123) by ()`
@@ -5966,7 +5988,6 @@ func TestExecError(t *testing.T) {
 	f(`label_move()`)
 	f(`median_over_time()`)
 	f(`median()`)
-	f(`median("foo", "bar")`)
 	f(`keep_last_value()`)
 	f(`keep_next_value()`)
 	f(`interpolate()`)
@@ -6068,7 +6089,6 @@ func TestExecError(t *testing.T) {
 	) + 10`)
 
 	// Invalid aggregates
-	f(`sum(1, 2)`)
 	f(`sum(1) foo (bar)`)
 	f(`sum foo () (bar)`)
 	f(`sum(foo) by (1)`)

docs/MetricsQL.md

@@ -37,6 +37,7 @@ This functionality can be tried at [an editable Grafana dashboard](http://play-g
 - `offset` may be negative. For example, `q offset -1h`.
 - [Range duration](https://prometheus.io/docs/prometheus/latest/querying/basics/#range-vector-selectors) and [offset](https://prometheus.io/docs/prometheus/latest/querying/basics/#offset-modifier) may be fractional. For instance, `rate(node_network_receive_bytes_total[1.5m] offset 0.5d)`.
 - `default` binary operator. `q1 default q2` fills gaps in `q1` with the corresponding values from `q2`.
+- Most aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point across `q1`, `q2` and `q3`.
 - `histogram_quantile` accepts optional third arg - `boundsLabel`. In this case it returns `lower` and `upper` bounds for the estimated percentile. See [this issue for details](https://github.com/prometheus/prometheus/issues/5706).
 - `if` binary operator. `q1 if q2` removes values from `q1` for missing values from `q2`.
 - `ifnot` binary operator. `q1 ifnot q2` removes values from `q1` for existing values from `q2`.