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

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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>
This commit is contained in:
George Krajcsovits 2024-03-27 18:19:14 +01:00 committed by GitHub
parent a3d1a46eda
commit dc7b282d39
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1 changed files with 21 additions and 21 deletions
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42
promql/engine_test.go
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@ -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,