promql: Optimize mergeSeriesWithSameLabelset for common case

Add fast path that returns early when no duplicate labelsets exist,
avoiding allocations in the common case. For the merge case, simplify
collision detection by checking for duplicate timestamps after sorting
instead of building a timestamp map, reducing memory overhead.

Signed-off-by: Julien Pivotto <291750+roidelapluie@users.noreply.github.com>

promql/engine.go

@@ -3866,6 +3866,13 @@ func (ev *evaluator) mergeSeriesWithSameLabelset(mat Matrix) Matrix {
 		return mat
 	}
 
+	// Fast path: check if there are any duplicate labelsets without allocating.
+	// This is the common case and we want to avoid allocations.
+	if !mat.ContainsSameLabelset() {
+		return mat
+	}
+
+	// Slow path: there are duplicates, so we need to merge series with non-overlapping timestamps.
 	// Group series by their labelset hash.
 	seriesByHash := make(map[uint64][]int)
 	for i := range mat {
@@ -3873,62 +3880,20 @@ func (ev *evaluator) mergeSeriesWithSameLabelset(mat Matrix) Matrix {
 		seriesByHash[hash] = append(seriesByHash[hash], i)
 	}
 
-	// Check if any merging is needed.
-	needsMerge := false
-	for _, indices := range seriesByHash {
-		if len(indices) > 1 {
-			needsMerge = true
-			break
-		}
-	}
-
-	if !needsMerge {
-		return mat
-	}
-
 	// Merge series with the same labelset.
 	merged := make(Matrix, 0, len(seriesByHash))
 	for _, indices := range seriesByHash {
-		base := mat[indices[0]]
-
 		if len(indices) == 1 {
 			// No collision, add as-is.
-			merged = append(merged, base)
+			merged = append(merged, mat[indices[0]])
 			continue
 		}
 
-		// Multiple series with the same labelset - check for overlaps and merge.
-		// Build a set of timestamps to detect overlaps.
-		timestamps := make(map[int64]struct{}, len(base.Floats)+len(base.Histograms))
-		for _, p := range base.Floats {
-			timestamps[p.T] = struct{}{}
-		}
-		for _, p := range base.Histograms {
-			timestamps[p.T] = struct{}{}
-		}
-
-		// Merge remaining series, checking for timestamp overlaps.
+		// Multiple series with the same labelset - merge all samples.
+		base := mat[indices[0]]
 		for _, idx := range indices[1:] {
-			series := mat[idx]
-
-			// Check floats for overlaps.
-			for _, p := range series.Floats {
-				if _, exists := timestamps[p.T]; exists {
-					ev.errorf("vector cannot contain metrics with the same labelset")
-				}
-				timestamps[p.T] = struct{}{}
-			}
-			// Check histograms for overlaps.
-			for _, p := range series.Histograms {
-				if _, exists := timestamps[p.T]; exists {
-					ev.errorf("vector cannot contain metrics with the same labelset")
-				}
-				timestamps[p.T] = struct{}{}
-			}
-
-			// No overlaps, merge the samples.
-			base.Floats = append(base.Floats, series.Floats...)
-			base.Histograms = append(base.Histograms, series.Histograms...)
+			base.Floats = append(base.Floats, mat[idx].Floats...)
+			base.Histograms = append(base.Histograms, mat[idx].Histograms...)
 		}
 
 		// Sort merged samples by timestamp.
@@ -3939,6 +3904,18 @@ func (ev *evaluator) mergeSeriesWithSameLabelset(mat Matrix) Matrix {
 			return base.Histograms[i].T < base.Histograms[j].T
 		})
 
+		// Check for duplicate timestamps in sorted samples.
+		for i := 1; i < len(base.Floats); i++ {
+			if base.Floats[i].T == base.Floats[i-1].T {
+				ev.errorf("vector cannot contain metrics with the same labelset")
+			}
+		}
+		for i := 1; i < len(base.Histograms); i++ {
+			if base.Histograms[i].T == base.Histograms[i-1].T {
+				ev.errorf("vector cannot contain metrics with the same labelset")
+			}
+		}
+
 		merged = append(merged, base)
 	}