Report PeakSamples in query statistics

This exactly corresponds to the statistic compared against MaxSamples
during the course of query execution, so users can see how close their
queries are to a limit.

Co-authored-by: Harkishen Singh <harkishensingh@hotmail.com>
Co-authored-by: Andrew Bloomgarden <blmgrdn@amazon.com>
Signed-off-by: Andrew Bloomgarden <blmgrdn@amazon.com>

promql/engine.go

@@ -1115,6 +1115,7 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 				}
 			}
 			args[i] = vectors[i]
+			ev.samplesStats.UpdatePeak(ev.currentSamples)
 		}
 
 		// Make the function call.
@@ -1130,10 +1131,12 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 		// When we reset currentSamples to tempNumSamples during the next iteration of the loop it also
 		// needs to include the samples from the result here, as they're still in memory.
 		tempNumSamples += len(result)
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
 
 		if ev.currentSamples > ev.maxSamples {
 			ev.error(ErrTooManySamples(env))
 		}
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
 
 		// If this could be an instant query, shortcut so as not to change sort order.
 		if ev.endTimestamp == ev.startTimestamp {
@@ -1143,6 +1146,7 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 				mat[i] = Series{Metric: s.Metric, Points: []Point{s.Point}}
 			}
 			ev.currentSamples = originalNumSamples + mat.TotalSamples()
+			ev.samplesStats.UpdatePeak(ev.currentSamples)
 			return mat, warnings
 		}
 
@@ -1175,17 +1179,20 @@ func (ev *evaluator) rangeEval(prepSeries func(labels.Labels, *EvalSeriesHelper)
 		mat = append(mat, ss)
 	}
 	ev.currentSamples = originalNumSamples + mat.TotalSamples()
+	ev.samplesStats.UpdatePeak(ev.currentSamples)
 	return mat, warnings
 }
 
 // evalSubquery evaluates given SubqueryExpr and returns an equivalent
 // evaluated MatrixSelector in its place. Note that the Name and LabelMatchers are not set.
 func (ev *evaluator) evalSubquery(subq *parser.SubqueryExpr) (*parser.MatrixSelector, int, storage.Warnings) {
-	sampleStats := ev.samplesStats
+	samplesStats := ev.samplesStats
 	// Avoid double counting samples when running a subquery, those samples will be counted in later stage.
-	ev.samplesStats = nil
+	ev.samplesStats = ev.samplesStats.NewChild()
 	val, ws := ev.eval(subq)
-	ev.samplesStats = sampleStats
+	// But do incorporate the peak from the subquery
+	samplesStats.UpdatePeakFromSubquery(ev.samplesStats)
+	ev.samplesStats = samplesStats
 	mat := val.(Matrix)
 	vs := &parser.VectorSelector{
 		OriginalOffset: subq.OriginalOffset,
@@ -1409,7 +1416,9 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, storage.Warnings) {
 			} else {
 				putPointSlice(ss.Points)
 			}
+			ev.samplesStats.UpdatePeak(ev.currentSamples)
 		}
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
 
 		ev.currentSamples -= len(points)
 		putPointSlice(points)
@@ -1563,6 +1572,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, storage.Warnings) {
 				putPointSlice(ss.Points)
 			}
 		}
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
 		return mat, ws
 
 	case *parser.MatrixSelector:
@@ -1607,6 +1617,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, storage.Warnings) {
 
 		res, ws := newEv.eval(e.Expr)
 		ev.currentSamples = newEv.currentSamples
+		ev.samplesStats.UpdatePeakFromSubquery(newEv.samplesStats)
 		ev.samplesStats.IncrementSamplesAtTimestamp(ev.endTimestamp, newEv.samplesStats.TotalSamples)
 		return res, ws
 	case *parser.StepInvariantExpr:
@@ -1629,6 +1640,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, storage.Warnings) {
 		}
 		res, ws := newEv.eval(e.Expr)
 		ev.currentSamples = newEv.currentSamples
+		ev.samplesStats.UpdatePeakFromSubquery(newEv.samplesStats)
 		for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts = ts + ev.interval {
 			step++
 			ev.samplesStats.IncrementSamplesAtStep(step, newEv.samplesStats.TotalSamples)
@@ -1662,6 +1674,7 @@ func (ev *evaluator) eval(expr parser.Expr) (parser.Value, storage.Warnings) {
 				}
 			}
 		}
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
 		return res, ws
 	}
 
@@ -1694,6 +1707,7 @@ func (ev *evaluator) vectorSelector(node *parser.VectorSelector, ts int64) (Vect
 		}
 
 	}
+	ev.samplesStats.UpdatePeak(ev.currentSamples)
 	return vec, ws
 }
 
@@ -1841,6 +1855,7 @@ func (ev *evaluator) matrixIterSlice(it *storage.BufferedSeriesIterator, mint, m
 			ev.currentSamples++
 		}
 	}
+	ev.samplesStats.UpdatePeak(ev.currentSamples)
 	return out
 }
 

promql/engine_test.go

@@ -756,14 +756,17 @@ load 10s
 
 	cases := []struct {
 		Query               string
+		SkipMaxCheck        bool
 		TotalSamples        int
 		TotalSamplesPerStep stats.TotalSamplesPerStep
+		PeakSamples         int
 		Start               time.Time
 		End                 time.Time
 		Interval            time.Duration
 	}{
 		{
 			Query:        `"literal string"`,
+			SkipMaxCheck: true, // This can't fail from a max samples limit.
 			Start:        time.Unix(21, 0),
 			TotalSamples: 0,
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
@@ -774,6 +777,7 @@ load 10s
 			Query:        "1",
 			Start:        time.Unix(21, 0),
 			TotalSamples: 0,
+			PeakSamples:  1,
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 0,
 			},
@@ -781,6 +785,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds",
 			Start:        time.Unix(21, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -790,6 +795,7 @@ load 10s
 			// timestamp function has a special handling.
 			Query:        "timestamp(metricWith1SampleEvery10Seconds)",
 			Start:        time.Unix(21, 0),
+			PeakSamples:  2,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -798,6 +804,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds",
 			Start:        time.Unix(22, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				22000: 1, // Aligned to the step time, not the sample time.
@@ -806,6 +813,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds offset 10s",
 			Start:        time.Unix(21, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -814,6 +822,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds @ 15",
 			Start:        time.Unix(21, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -822,6 +831,7 @@ load 10s
 		{
 			Query:        `metricWith3SampleEvery10Seconds{a="1"}`,
 			Start:        time.Unix(21, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -830,6 +840,7 @@ load 10s
 		{
 			Query:        `metricWith3SampleEvery10Seconds{a="1"} @ 19`,
 			Start:        time.Unix(21, 0),
+			PeakSamples:  1,
 			TotalSamples: 1, // 1 sample / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -838,6 +849,7 @@ load 10s
 		{
 			Query:        `metricWith3SampleEvery10Seconds{a="1"}[20s] @ 19`,
 			Start:        time.Unix(21, 0),
+			PeakSamples:  2,
 			TotalSamples: 2, // (1 sample / 10 seconds) * 20s
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 2,
@@ -846,6 +858,7 @@ load 10s
 		{
 			Query:        "metricWith3SampleEvery10Seconds",
 			Start:        time.Unix(21, 0),
+			PeakSamples:  3,
 			TotalSamples: 3, // 3 samples / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 3,
@@ -854,6 +867,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds[60s]",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  6,
 			TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 6,
@@ -862,6 +876,7 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith1SampleEvery10Seconds[59s])[20s:5s]",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  10,
 			TotalSamples: 24, // (1 sample / 10 seconds * 60 seconds) * 60/5 (using 59s so we always return 6 samples
 			// as if we run a query on 00 looking back 60 seconds we will return 7 samples;
 			// see next test).
@@ -872,6 +887,7 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith1SampleEvery10Seconds[60s])[20s:5s]",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  11,
 			TotalSamples: 26, // (1 sample / 10 seconds * 60 seconds) + 2 as
 			// max_over_time(metricWith1SampleEvery10Seconds[60s]) @ 190 and 200 will return 7 samples.
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
@@ -881,6 +897,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds[60s] @ 30",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  4,
 			TotalSamples: 4, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 4,
@@ -889,6 +906,7 @@ load 10s
 		{
 			Query:        "sum(max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  7,
 			TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -897,6 +915,7 @@ load 10s
 		{
 			Query:        "sum by (b) (max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  8,
 			TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -905,6 +924,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds[60s] offset 10s",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  6,
 			TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 6,
@@ -913,6 +933,7 @@ load 10s
 		{
 			Query:        "metricWith3SampleEvery10Seconds[60s]",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  18,
 			TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 18,
@@ -921,6 +942,7 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith1SampleEvery10Seconds[60s])",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  7,
 			TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 6,
@@ -929,6 +951,7 @@ load 10s
 		{
 			Query:        "absent_over_time(metricWith1SampleEvery10Seconds[60s])",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  7,
 			TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 6,
@@ -937,6 +960,7 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith3SampleEvery10Seconds[60s])",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  9,
 			TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 18,
@@ -945,6 +969,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds[60s:5s]",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  12,
 			TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -953,6 +978,7 @@ load 10s
 		{
 			Query:        "metricWith1SampleEvery10Seconds[60s:5s] offset 10s",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  12,
 			TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -961,6 +987,7 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith3SampleEvery10Seconds[60s:5s])",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  51,
 			TotalSamples: 36, // 3 sample per query * 12 queries (60/5)
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 36,
@@ -969,6 +996,7 @@ load 10s
 		{
 			Query:        "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s]))",
 			Start:        time.Unix(201, 0),
+			PeakSamples:  52,
 			TotalSamples: 72, // 2 * (3 sample per query * 12 queries (60/5))
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 72,
@@ -979,6 +1007,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  4,
 			TotalSamples: 4, // 1 sample per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 1,
@@ -992,6 +1021,7 @@ load 10s
 			Start:        time.Unix(204, 0),
 			End:          time.Unix(223, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  4,
 			TotalSamples: 4, // 1 sample per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				204000: 1, // aligned to the step time, not the sample time
@@ -1006,6 +1036,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  5,
 			TotalSamples: 4, // (1 sample / 10 seconds) * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 1,
@@ -1019,6 +1050,7 @@ load 10s
 			Start:        time.Unix(991, 0),
 			End:          time.Unix(1021, 0),
 			Interval:     10 * time.Second,
+			PeakSamples:  2,
 			TotalSamples: 2, // 1 sample per query * 2 steps with data
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				991000:  1,
@@ -1032,6 +1064,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  4,
 			TotalSamples: 4, // 1 sample per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 1,
@@ -1045,6 +1078,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  12,
 			TotalSamples: 48, // @ modifier force the evaluation timestamp at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -1057,6 +1091,7 @@ load 10s
 			Query:        `metricWith3SampleEvery10Seconds`,
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
+			PeakSamples:  12,
 			Interval:     5 * time.Second,
 			TotalSamples: 12, // 3 sample per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
@@ -1071,6 +1106,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  18,
 			TotalSamples: 72, // (3 sample / 10 seconds * 60 seconds) * 4 steps = 72
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 18,
@@ -1084,6 +1120,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  72,
 			TotalSamples: 144, // 3 sample per query * 12 queries (60/5) * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 36,
@@ -1097,6 +1134,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  32,
 			TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -1110,6 +1148,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  32,
 			TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 12,
@@ -1123,6 +1162,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  76,
 			TotalSamples: 288, // 2 * (3 sample per query * 12 queries (60/5) * 4 steps)
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 72,
@@ -1136,6 +1176,7 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
+			PeakSamples:  72,
 			TotalSamples: 192, // (1 sample per query * 12 queries (60/5) + 3 sample per query * 12 queries (60/5)) * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 48,
@@ -1148,25 +1189,39 @@ load 10s
 
 	engine := test.QueryEngine()
 	engine.enablePerStepStats = true
+	origMaxSamples := engine.maxSamplesPerQuery
 	for _, c := range cases {
 		t.Run(c.Query, func(t *testing.T) {
 			opts := &QueryOpts{EnablePerStepStats: true}
+			engine.maxSamplesPerQuery = origMaxSamples
 
-			var err error
+			runQuery := func(expErr error) *stats.Statistics {
-			var qry Query
+				var err error
-			if c.Interval == 0 {
+				var qry Query
-				qry, err = engine.NewInstantQuery(test.Queryable(), opts, c.Query, c.Start)
+				if c.Interval == 0 {
-			} else {
+					qry, err = engine.NewInstantQuery(test.Queryable(), opts, c.Query, c.Start)
-				qry, err = engine.NewRangeQuery(test.Queryable(), opts, c.Query, c.Start, c.End, c.Interval)
+				} else {
+					qry, err = engine.NewRangeQuery(test.Queryable(), opts, c.Query, c.Start, c.End, c.Interval)
+				}
+				require.NoError(t, err)
+
+				res := qry.Exec(test.Context())
+				require.Equal(t, expErr, res.Err)
+
+				return qry.Stats()
 			}
-			require.NoError(t, err)
 
-			res := qry.Exec(test.Context())
+			stats := runQuery(nil)
-			require.Nil(t, res.Err)
-
-			stats := qry.Stats()
 			require.Equal(t, c.TotalSamples, stats.Samples.TotalSamples, "Total samples mismatch")
 			require.Equal(t, &c.TotalSamplesPerStep, stats.Samples.TotalSamplesPerStepMap(), "Total samples per time mismatch")
+			require.Equal(t, c.PeakSamples, stats.Samples.PeakSamples, "Peak samples mismatch")
+
+			// Check that the peak is correct by setting the max to one less.
+			if c.SkipMaxCheck {
+				return
+			}
+			engine.maxSamplesPerQuery = stats.Samples.PeakSamples - 1
+			runQuery(ErrTooManySamples(env))
 		})
 	}
 }
@@ -1337,6 +1392,9 @@ load 10s
 				stats := qry.Stats()
 				require.Equal(t, expError, res.Err)
 				require.NotNil(t, stats)
+				if expError == nil {
+					require.Equal(t, c.MaxSamples, stats.Samples.PeakSamples, "peak samples mismatch for query %q", c.Query)
+				}
 			}
 
 			// Within limit.

util/stats/query_stats.go

@@ -108,6 +108,7 @@ type queryTimings struct {
 type querySamples struct {
 	TotalQueryableSamplesPerStep []stepStat `json:"totalQueryableSamplesPerStep,omitempty"`
 	TotalQueryableSamples        int        `json:"totalQueryableSamples"`
+	PeakSamples                  int        `json:"peakSamples"`
 }
 
 // BuiltinStats holds the statistics that Prometheus's core gathers.
@@ -156,6 +157,7 @@ func NewQueryStats(s *Statistics) QueryStats {
 	if sp != nil {
 		samples = &querySamples{
 			TotalQueryableSamples: sp.TotalSamples,
+			PeakSamples:           sp.PeakSamples,
 		}
 		samples.TotalQueryableSamplesPerStep = sp.totalSamplesPerStepPoints()
 	}
@@ -229,6 +231,12 @@ type QueryTimers struct {
 type TotalSamplesPerStep map[int64]int
 
 type QuerySamples struct {
+	// PeakSamples represent the highest count of samples considered
+	// while evaluating a query. It corresponds to the peak value of
+	// currentSamples, which is in turn compared against the MaxSamples
+	// configured in the engine.
+	PeakSamples int
+
 	// TotalSamples represents the total number of samples scanned
 	// while evaluating a query.
 	TotalSamples int
@@ -287,6 +295,28 @@ func (qs *QuerySamples) IncrementSamplesAtTimestamp(t int64, samples int) {
 	}
 }
 
+// UpdatePeak updates the peak number of samples considered in
+// the evaluation of a query as used with the MaxSamples limit.
+func (qs *QuerySamples) UpdatePeak(samples int) {
+	if qs == nil {
+		return
+	}
+	if samples > qs.PeakSamples {
+		qs.PeakSamples = samples
+	}
+}
+
+// UpdatePeakFromSubquery updates the peak number of samples considered
+// in a query from its evaluation of a subquery.
+func (qs *QuerySamples) UpdatePeakFromSubquery(other *QuerySamples) {
+	if qs == nil || other == nil {
+		return
+	}
+	if other.PeakSamples > qs.PeakSamples {
+		qs.PeakSamples = other.PeakSamples
+	}
+}
+
 func NewQueryTimers() *QueryTimers {
 	return &QueryTimers{NewTimerGroup()}
 }