promql: simplify data collection in aggregations

We don't need a Sample, just the float and histogram values.

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

promql/engine.go

@@ -2740,7 +2740,7 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 	}
 
 	for si := range inputMatrix {
-		s, ok := ev.nextSample(enh.Ts, inputMatrix, si)
+		f, h, ok := ev.nextValues(enh.Ts, &inputMatrix[si])
 		if !ok {
 			continue
 		}
@@ -2749,18 +2749,18 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 		// Initialize this group if it's the first time we've seen it.
 		if !seen[seriesToResult[si]] {
 			*group = groupedAggregation{
-				floatValue: s.F,
+				floatValue: f,
-				floatMean:  s.F,
+				floatMean:  f,
 				groupCount: 1,
 			}
 			switch {
-			case s.H == nil:
+			case h == nil:
 				group.hasFloat = true
 			case op == parser.SUM:
-				group.histogramValue = s.H.Copy()
+				group.histogramValue = h.Copy()
 				group.hasHistogram = true
 			case op == parser.AVG:
-				group.histogramMean = s.H.Copy()
+				group.histogramMean = h.Copy()
 				group.hasHistogram = true
 			case op == parser.STDVAR || op == parser.STDDEV:
 				group.groupCount = 0
@@ -2771,10 +2771,7 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 				group.floatValue = 0
 			case parser.QUANTILE:
 				group.heap = make(vectorByValueHeap, 1)
-				group.heap[0] = Sample{
+				group.heap[0] = Sample{F: f}
-					F:      s.F,
-					Metric: s.Metric,
-				}
 			case parser.GROUP:
 				group.floatValue = 1
 			}
@@ -2784,25 +2781,25 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 
 		switch op {
 		case parser.SUM:
-			if s.H != nil {
+			if h != nil {
 				group.hasHistogram = true
 				if group.histogramValue != nil {
-					group.histogramValue.Add(s.H)
+					group.histogramValue.Add(h)
 				}
 				// Otherwise the aggregation contained floats
 				// previously and will be invalid anyway. No
 				// point in copying the histogram in that case.
 			} else {
 				group.hasFloat = true
-				group.floatValue += s.F
+				group.floatValue += f
 			}
 
 		case parser.AVG:
 			group.groupCount++
-			if s.H != nil {
+			if h != nil {
 				group.hasHistogram = true
 				if group.histogramMean != nil {
-					left := s.H.Copy().Div(float64(group.groupCount))
+					left := h.Copy().Div(float64(group.groupCount))
 					right := group.histogramMean.Copy().Div(float64(group.groupCount))
 					toAdd := left.Sub(right)
 					group.histogramMean.Add(toAdd)
@@ -2813,13 +2810,13 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 			} else {
 				group.hasFloat = true
 				if math.IsInf(group.floatMean, 0) {
-					if math.IsInf(s.F, 0) && (group.floatMean > 0) == (s.F > 0) {
+					if math.IsInf(f, 0) && (group.floatMean > 0) == (f > 0) {
 						// The `floatMean` and `s.F` values are `Inf` of the same sign.  They
 						// can't be subtracted, but the value of `floatMean` is correct
 						// already.
 						break
 					}
-					if !math.IsInf(s.F, 0) && !math.IsNaN(s.F) {
+					if !math.IsInf(f, 0) && !math.IsNaN(f) {
 						// At this stage, the mean is an infinite. If the added
 						// value is neither an Inf or a Nan, we can keep that mean
 						// value.
@@ -2830,35 +2827,35 @@ func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix
 					}
 				}
 				// Divide each side of the `-` by `group.groupCount` to avoid float64 overflows.
-				group.floatMean += s.F/float64(group.groupCount) - group.floatMean/float64(group.groupCount)
+				group.floatMean += f/float64(group.groupCount) - group.floatMean/float64(group.groupCount)
 			}
 
 		case parser.GROUP:
 			// Do nothing. Required to avoid the panic in `default:` below.
 
 		case parser.MAX:
-			if group.floatValue < s.F || math.IsNaN(group.floatValue) {
+			if group.floatValue < f || math.IsNaN(group.floatValue) {
-				group.floatValue = s.F
+				group.floatValue = f
 			}
 
 		case parser.MIN:
-			if group.floatValue > s.F || math.IsNaN(group.floatValue) {
+			if group.floatValue > f || math.IsNaN(group.floatValue) {
-				group.floatValue = s.F
+				group.floatValue = f
 			}
 
 		case parser.COUNT:
 			group.groupCount++
 
 		case parser.STDVAR, parser.STDDEV:
-			if s.H == nil { // Ignore native histograms.
+			if h == nil { // Ignore native histograms.
 				group.groupCount++
-				delta := s.F - group.floatMean
+				delta := f - group.floatMean
 				group.floatMean += delta / float64(group.groupCount)
-				group.floatValue += delta * (s.F - group.floatMean)
+				group.floatValue += delta * (f - group.floatMean)
 			}
 
 		case parser.QUANTILE:
-			group.heap = append(group.heap, s)
+			group.heap = append(group.heap, Sample{F: f})
 
 		default:
 			panic(fmt.Errorf("expected aggregation operator but got %q", op))