promql: remove pointer to aggregation groups

Just allocate in one slice.

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

promql/engine.go

@@ -1298,9 +1298,9 @@ func (ev *evaluator) rangeEvalAgg(aggExpr *parser.AggregateExpr, sortedGrouping
 	buf := make([]byte, 0, 1024)
 	groupToResultIndex := make(map[uint64]int)
 	seriesToResult := make([]int, len(inputMatrix))
-	orderedResult := make([]*groupedAggregation, 0, 16)
 	var result Matrix
 
+	groupCount := 0
 	for si, series := range inputMatrix {
 		var groupingKey uint64
 		groupingKey, buf = generateGroupingKey(series.Metric, sortedGrouping, aggExpr.Without, buf)
@@ -1311,13 +1311,13 @@ func (ev *evaluator) rangeEvalAgg(aggExpr *parser.AggregateExpr, sortedGrouping
 				m := generateGroupingLabels(enh, series.Metric, aggExpr.Without, sortedGrouping)
 				result = append(result, Series{Metric: m})
 			}
-			newAgg := &groupedAggregation{}
+			index = groupCount
-			index = len(orderedResult)
 			groupToResultIndex[groupingKey] = index
-			orderedResult = append(orderedResult, newAgg)
+			groupCount++
 		}
 		seriesToResult[si] = index
 	}
+	groups := make([]groupedAggregation, groupCount)
 
 	var k int
 	var seriess map[uint64]Series
@@ -1352,13 +1352,13 @@ func (ev *evaluator) rangeEvalAgg(aggExpr *parser.AggregateExpr, sortedGrouping
 		var ws annotations.Annotations
 		switch aggExpr.Op {
 		case parser.TOPK, parser.BOTTOMK:
-			result, ws = ev.aggregationK(aggExpr, k, inputMatrix, seriesToResult, orderedResult, enh, seriess)
+			result, ws = ev.aggregationK(aggExpr, k, inputMatrix, seriesToResult, groups, enh, seriess)
 			// If this could be an instant query, shortcut so as not to change sort order.
 			if ev.endTimestamp == ev.startTimestamp {
 				return result, ws
 			}
 		default:
-			ws = ev.aggregation(aggExpr, param, inputMatrix, result, seriesToResult, orderedResult, enh)
+			ws = ev.aggregation(aggExpr, param, inputMatrix, result, seriesToResult, groups, enh)
 		}
 
 		warnings.Merge(ws)
@@ -2741,10 +2741,10 @@ type groupedAggregation struct {
 // These functions produce one output series for each group specified in the expression, with just the labels from `by(...)`.
 // outputMatrix should be already populated with grouping labels; groups is one-to-one with outputMatrix.
 // seriesToResult maps inputMatrix indexes to outputMatrix indexes.
-func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix, outputMatrix Matrix, seriesToResult []int, orderedResult []*groupedAggregation, enh *EvalNodeHelper) annotations.Annotations {
+func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix, outputMatrix Matrix, seriesToResult []int, groups []groupedAggregation, enh *EvalNodeHelper) annotations.Annotations {
 	op := e.Op
 	var annos annotations.Annotations
-	seen := make([]bool, len(orderedResult)) // Which output groups were seen in the input at this timestamp.
+	seen := make([]bool, len(groups)) // Which output groups were seen in the input at this timestamp.
 
 	for si := range inputMatrix {
 		f, h, ok := ev.nextValues(enh.Ts, &inputMatrix[si])
@@ -2752,7 +2752,7 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 			continue
 		}
 
-		group := orderedResult[seriesToResult[si]]
+		group := &groups[seriesToResult[si]]
 		// Initialize this group if it's the first time we've seen it.
 		if !seen[seriesToResult[si]] {
 			*group = groupedAggregation{
@@ -2866,7 +2866,7 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 	// Construct the output matrix from the aggregated groups.
 	numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
 
-	for ri, aggr := range orderedResult {
+	for ri, aggr := range groups {
 		if !seen[ri] {
 			continue
 		}
@@ -2920,11 +2920,11 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 // seriesToResult maps inputMatrix indexes to groups indexes.
 // For an instant query, returns a Matrix in descending order for topk or ascending for bottomk.
 // For a range query, aggregates output in the seriess map.
-func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, inputMatrix Matrix, seriesToResult []int, orderedResult []*groupedAggregation, enh *EvalNodeHelper, seriess map[uint64]Series) (Matrix, annotations.Annotations) {
+func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, inputMatrix Matrix, seriesToResult []int, groups []groupedAggregation, enh *EvalNodeHelper, seriess map[uint64]Series) (Matrix, annotations.Annotations) {
 	op := e.Op
 	var s Sample
 	var annos annotations.Annotations
-	seen := make([]bool, len(orderedResult)) // Which output groups were seen in the input at this timestamp.
+	seen := make([]bool, len(groups)) // Which output groups were seen in the input at this timestamp.
 
 	for si := range inputMatrix {
 		f, _, ok := ev.nextValues(enh.Ts, &inputMatrix[si])
@@ -2933,7 +2933,7 @@ func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, inputMatrix Ma
 		}
 		s = Sample{Metric: inputMatrix[si].Metric, F: f}
 
-		group := orderedResult[seriesToResult[si]]
+		group := &groups[seriesToResult[si]]
 		// Initialize this group if it's the first time we've seen it.
 		if !seen[seriesToResult[si]] {
 			*group = groupedAggregation{
@@ -2980,7 +2980,7 @@ func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, inputMatrix Ma
 	numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
 	var mat Matrix
 	if ev.endTimestamp == ev.startTimestamp {
-		mat = make(Matrix, 0, len(orderedResult))
+		mat = make(Matrix, 0, len(groups))
 	}
 
 	add := func(lbls labels.Labels, f float64) {
@@ -2998,7 +2998,7 @@ func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, inputMatrix Ma
 			seriess[hash] = ss
 		}
 	}
-	for ri, aggr := range orderedResult {
+	for ri, aggr := range groups {
 		if !seen[ri] {
 			continue
 		}