engine_test: adjust and comment histogram sample counts (#13841)

The size of histogram points are now bigger by 24 bytes due to the
custom values slice.

When histograms are loaded into partial results in vector selectors
we use HPoint type where the size is calculated as
(size of histogram + 8 for timestamp)/16.
a3d1a46eda/promql/value.go (L176)

When histograms are put into Sample type in range evaluations, the
Sample has more overhead and the size is calculated differently:
(size of histogram / 16) + 1 for time stamp.
a3d1a46eda/promql/engine.go (L1928)

When the size of the histogram is 16k, then the first calculation gives k
but the second gives k+1 for the sample count.
If the histogram size is 16k+8, then both would give k+1.

Signed-off-by: György Krajcsovits <gyorgy.krajcsovits@grafana.com>

promql/engine_test.go

@@ -799,10 +799,10 @@ load 10s
 		{
 			Query:        "metricWith1HistogramEvery10Seconds",
 			Start:        time.Unix(21, 0),
-			PeakSamples:  12,
-			TotalSamples: 12, // 1 histogram sample of size 12 / 10 seconds
+			PeakSamples:  13,
+			TotalSamples: 13, // 1 histogram HPoint of size 13 / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
-				21000: 12,
+				21000: 13,
 			},
 		},
 		{
@@ -818,7 +818,7 @@ load 10s
 		{
 			Query:        "timestamp(metricWith1HistogramEvery10Seconds)",
 			Start:        time.Unix(21, 0),
-			PeakSamples:  13, // histogram size 12 + 1 extra because of timestamp
+			PeakSamples:  15, // histogram size 13 + 1 extra because Sample overhead + 1 float result
 			TotalSamples: 1,  // 1 float sample (because of timestamp) / 10 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				21000: 1,
@@ -899,10 +899,10 @@ load 10s
 		{
 			Query:        "metricWith1HistogramEvery10Seconds[60s]",
 			Start:        time.Unix(201, 0),
-			PeakSamples:  72,
-			TotalSamples: 72, // 1 histogram (size 12) / 10 seconds * 60 seconds
+			PeakSamples:  78,
+			TotalSamples: 78, // 1 histogram (size 13 HPoint) / 10 seconds * 60 seconds
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
-				201000: 72,
+				201000: 78,
 			},
 		},
 		{
@@ -929,11 +929,11 @@ load 10s
 		{
 			Query:        "max_over_time(metricWith1HistogramEvery10Seconds[60s])[20s:5s]",
 			Start:        time.Unix(201, 0),
-			PeakSamples:  72,
-			TotalSamples: 312, // (1 histogram (size 12) / 10 seconds * 60 seconds) * 4 + 2 * 12 as
+			PeakSamples:  78,
+			TotalSamples: 338, // (1 histogram (size 13 HPoint) / 10 seconds * 60 seconds) * 4 + 2 * 13 as
 			// max_over_time(metricWith1SampleEvery10Seconds[60s]) @ 190 and 200 will return 7 samples.
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
-				201000: 312,
+				201000: 338,
 			},
 		},
 		{
@@ -948,10 +948,10 @@ load 10s
 		{
 			Query:        "metricWith1HistogramEvery10Seconds[60s] @ 30",
 			Start:        time.Unix(201, 0),
-			PeakSamples:  48,
-			TotalSamples: 48, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
+			PeakSamples:  52,
+			TotalSamples: 52, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
-				201000: 48,
+				201000: 52,
 			},
 		},
 		{
@@ -1086,13 +1086,13 @@ load 10s
 			Start:        time.Unix(204, 0),
 			End:          time.Unix(223, 0),
 			Interval:     5 * time.Second,
-			PeakSamples:  48,
-			TotalSamples: 48, // 1 histogram (size 12) per query * 4 steps
+			PeakSamples:  52,
+			TotalSamples: 52, // 1 histogram (size 13 HPoint) per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
-				204000: 12, // aligned to the step time, not the sample time
-				209000: 12,
-				214000: 12,
-				219000: 12,
+				204000: 13, // aligned to the step time, not the sample time
+				209000: 13,
+				214000: 13,
+				219000: 13,
 			},
 		},
 		{
@@ -1116,8 +1116,8 @@ load 10s
 			Start:        time.Unix(201, 0),
 			End:          time.Unix(220, 0),
 			Interval:     5 * time.Second,
-			PeakSamples:  16,
-			TotalSamples: 4, // 1 sample per query * 4 steps
+			PeakSamples:  18, // 13 histogram size + 1 extra because of Sample overhead + 4 float results
+			TotalSamples: 4,  // 1 sample per query * 4 steps
 			TotalSamplesPerStep: stats.TotalSamplesPerStep{
 				201000: 1,
 				206000: 1,