1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
package metrics
import (
"fmt"
"math"
"reflect"
"runtime/metrics"
"testing"
)
var _ Histogram = (*runtimeHistogram)(nil)
type runtimeHistogramTest struct {
h metrics.Float64Histogram
Count int64
Min int64
Max int64
Sum int64
Mean float64
Variance float64
StdDev float64
Percentiles []float64 // .5 .8 .9 .99 .995
}
// This test checks the results of statistical functions implemented
// by runtimeHistogramSnapshot.
func TestRuntimeHistogramStats(t *testing.T) {
tests := []runtimeHistogramTest{
0: {
h: metrics.Float64Histogram{
Counts: []uint64{},
Buckets: []float64{},
},
Count: 0,
Max: 0,
Min: 0,
Sum: 0,
Mean: 0,
Variance: 0,
StdDev: 0,
Percentiles: []float64{0, 0, 0, 0, 0},
},
1: {
// This checks the case where the highest bucket is +Inf.
h: metrics.Float64Histogram{
Counts: []uint64{0, 1, 2},
Buckets: []float64{0, 0.5, 1, math.Inf(1)},
},
Count: 3,
Max: 1,
Min: 0,
Sum: 3,
Mean: 0.9166666,
Percentiles: []float64{1, 1, 1, 1, 1},
Variance: 0.020833,
StdDev: 0.144433,
},
2: {
h: metrics.Float64Histogram{
Counts: []uint64{8, 6, 3, 1},
Buckets: []float64{12, 16, 18, 24, 25},
},
Count: 18,
Max: 25,
Min: 12,
Sum: 270,
Mean: 16.75,
Variance: 10.3015,
StdDev: 3.2096,
Percentiles: []float64{16, 18, 18, 24, 24},
},
}
for i, test := range tests {
t.Run(fmt.Sprint(i), func(t *testing.T) {
s := runtimeHistogramSnapshot(test.h)
if v := s.Count(); v != test.Count {
t.Errorf("Count() = %v, want %v", v, test.Count)
}
if v := s.Min(); v != test.Min {
t.Errorf("Min() = %v, want %v", v, test.Min)
}
if v := s.Max(); v != test.Max {
t.Errorf("Max() = %v, want %v", v, test.Max)
}
if v := s.Sum(); v != test.Sum {
t.Errorf("Sum() = %v, want %v", v, test.Sum)
}
if v := s.Mean(); !approxEqual(v, test.Mean, 0.0001) {
t.Errorf("Mean() = %v, want %v", v, test.Mean)
}
if v := s.Variance(); !approxEqual(v, test.Variance, 0.0001) {
t.Errorf("Variance() = %v, want %v", v, test.Variance)
}
if v := s.StdDev(); !approxEqual(v, test.StdDev, 0.0001) {
t.Errorf("StdDev() = %v, want %v", v, test.StdDev)
}
ps := []float64{.5, .8, .9, .99, .995}
if v := s.Percentiles(ps); !reflect.DeepEqual(v, test.Percentiles) {
t.Errorf("Percentiles(%v) = %v, want %v", ps, v, test.Percentiles)
}
})
}
}
func approxEqual(x, y, ε float64) bool {
if math.IsInf(x, -1) && math.IsInf(y, -1) {
return true
}
if math.IsInf(x, 1) && math.IsInf(y, 1) {
return true
}
if math.IsNaN(x) && math.IsNaN(y) {
return true
}
return math.Abs(x-y) < ε
}
// This test verifies that requesting Percentiles in unsorted order
// returns them in the requested order.
func TestRuntimeHistogramStatsPercentileOrder(t *testing.T) {
p := runtimeHistogramSnapshot{
Counts: []uint64{1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
Buckets: []float64{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
}
result := p.Percentiles([]float64{1, 0.2, 0.5, 0.1, 0.2})
expected := []float64{10, 2, 5, 1, 2}
if !reflect.DeepEqual(result, expected) {
t.Fatal("wrong result:", result)
}
}