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runtimehistogram_test.go
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runtimehistogram_test.go
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package metrics
import (
"bytes"
"encoding/gob"
"fmt"
"math"
"reflect"
"runtime/metrics"
"testing"
"time"
)
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 := RuntimeHistogramFromData(1.0, &test.h).Snapshot()
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) {
s := RuntimeHistogramFromData(1.0, &metrics.Float64Histogram{
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},
}).Snapshot()
result := s.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)
}
}
func BenchmarkRuntimeHistogramSnapshotRead(b *testing.B) {
var sLatency = "7\xff\x81\x03\x01\x01\x10Float64Histogram\x01\xff\x82\x00\x01\x02\x01\x06Counts\x01\xff\x84\x00\x01\aBuckets\x01\xff\x86\x00\x00\x00\x16\xff\x83\x02\x01\x01\b[]uint64\x01\xff\x84\x00\x01\x06\x00\x00\x17\xff\x85\x02\x01\x01\t[]float64\x01\xff\x86\x00\x01\b\x00\x00\xfe\x06T\xff\x82\x01\xff\xa2\x00\xfe\r\xef\x00\x01\x02\x02\x04\x05\x04\b\x15\x17 B?6.L;$!2) \x1a? \x190aH7FY6#\x190\x1d\x14\x10\x1b\r\t\x04\x03\x01\x01\x00\x03\x02\x00\x03\x05\x05\x02\x02\x06\x04\v\x06\n\x15\x18\x13'&.\x12=H/L&\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\xff\xa3\xfe\xf0\xff\x00\xf8\x95\xd6&\xe8\v.q>\xf8\x95\xd6&\xe8\v.\x81>\xf8\xdfA:\xdc\x11ʼn>\xf8\x95\xd6&\xe8\v.\x91>\xf8:\x8c0\xe2\x8ey\x95>\xf8\xdfA:\xdc\x11ř>\xf8\x84\xf7C֔\x10\x9e>\xf8\x95\xd6&\xe8\v.\xa1>\xf8:\x8c0\xe2\x8ey\xa5>\xf8\xdfA:\xdc\x11ũ>\xf8\x84\xf7C֔\x10\xae>\xf8\x95\xd6&\xe8\v.\xb1>\xf8:\x8c0\xe2\x8ey\xb5>\xf8\xdfA:\xdc\x11Ź>\xf8\x84\xf7C֔\x10\xbe>\xf8\x95\xd6&\xe8\v.\xc1>\xf8:\x8c0\xe2\x8ey\xc5>\xf8\xdfA:\xdc\x11\xc5\xc9>\xf8\x84\xf7C֔\x10\xce>\xf8\x95\xd6&\xe8\v.\xd1>\xf8:\x8c0\xe2\x8ey\xd5>\xf8\xdfA:\xdc\x11\xc5\xd9>\xf8\x84\xf7C֔\x10\xde>\xf8\x95\xd6&\xe8\v.\xe1>\xf8:\x8c0\xe2\x8ey\xe5>\xf8\xdfA:\xdc\x11\xc5\xe9>\xf8\x84\xf7C֔\x10\xee>\xf8\x95\xd6&\xe8\v.\xf1>\xf8:\x8c0\xe2\x8ey\xf5>\xf8\xdfA:\xdc\x11\xc5\xf9>\xf8\x84\xf7C֔\x10\xfe>\xf8\x95\xd6&\xe8\v.\x01?\xf8:\x8c0\xe2\x8ey\x05?\xf8\xdfA:\xdc\x11\xc5\t?\xf8\x84\xf7C֔\x10\x0e?\xf8\x95\xd6&\xe8\v.\x11?\xf8:\x8c0\xe2\x8ey\x15?\xf8\xdfA:\xdc\x11\xc5\x19?\xf8\x84\xf7C֔\x10\x1e?\xf8\x95\xd6&\xe8\v.!?\xf8:\x8c0\xe2\x8ey%?\xf8\xdfA:\xdc\x11\xc5)?\xf8\x84\xf7C֔\x10.?\xf8\x95\xd6&\xe8\v.1?\xf8:\x8c0\xe2\x8ey5?\xf8\xdfA:\xdc\x11\xc59?\xf8\x84\xf7C֔\x10>?\xf8\x95\xd6&\xe8\v.A?\xf8:\x8c0\xe2\x8eyE?\xf8\xdfA:\xdc\x11\xc5I?\xf8\x84\xf7C֔\x10N?\xf8\x95\xd6&\xe8\v.Q?\xf8:\x8c0\xe2\x8eyU?\xf8\xdfA:\xdc\x11\xc5Y?\xf8\x84\xf7C֔\x10^?\xf8\x95\xd6&\xe8\v.a?\xf8:\x8c0\xe2\x8eye?\xf8\xdfA:\xdc\x11\xc5i?\xf8\x84\xf7C֔\x10n?\xf8\x95\xd6&\xe8\v.q?\xf8:\x8c0\xe2\x8eyu?\xf8\xdfA:\xdc\x11\xc5y?\xf8\x84\xf7C֔\x10~?\xf8\x95\xd6&\xe8\v.\x81?\xf8:\x8c0\xe2\x8ey\x85?\xf8\xdfA:\xdc\x11ʼn?\xf8\x84\xf7C֔\x10\x8e?\xf8\x95\xd6&\xe8\v.\x91?\xf8:\x8c0\xe2\x8ey\x95?\xf8\xdfA:\xdc\x11ř?\xf8\x84\xf7C֔\x10\x9e?\xf8\x95\xd6&\xe8\v.\xa1?\xf8:\x8c0\xe2\x8ey\xa5?\xf8\xdfA:\xdc\x11ũ?\xf8\x84\xf7C֔\x10\xae?\xf8\x95\xd6&\xe8\v.\xb1?\xf8:\x8c0\xe2\x8ey\xb5?\xf8\xdfA:\xdc\x11Ź?\xf8\x84\xf7C֔\x10\xbe?\xf8\x95\xd6&\xe8\v.\xc1?\xf8:\x8c0\xe2\x8ey\xc5?\xf8\xdfA:\xdc\x11\xc5\xc9?\xf8\x84\xf7C֔\x10\xce?\xf8\x95\xd6&\xe8\v.\xd1?\xf8:\x8c0\xe2\x8ey\xd5?\xf8\xdfA:\xdc\x11\xc5\xd9?\xf8\x84\xf7C֔\x10\xde?\xf8\x95\xd6&\xe8\v.\xe1?\xf8:\x8c0\xe2\x8ey\xe5?\xf8\xdfA:\xdc\x11\xc5\xe9?\xf8\x84\xf7C֔\x10\xee?\xf8\x95\xd6&\xe8\v.\xf1?\xf8:\x8c0\xe2\x8ey\xf5?\xf8\xdfA:\xdc\x11\xc5\xf9?\xf8\x84\xf7C֔\x10\xfe?\xf8\x95\xd6&\xe8\v.\x01@\xf8:\x8c0\xe2\x8ey\x05@\xf8\xdfA:\xdc\x11\xc5\t@\xf8\x84\xf7C֔\x10\x0e@\xf8\x95\xd6&\xe8\v.\x11@\xf8:\x8c0\xe2\x8ey\x15@\xf8\xdfA:\xdc\x11\xc5\x19@\xf8\x84\xf7C֔\x10\x1e@\xf8\x95\xd6&\xe8\v.!@\xf8:\x8c0\xe2\x8ey%@\xf8\xdfA:\xdc\x11\xc5)@\xf8\x84\xf7C֔\x10.@\xf8\x95\xd6&\xe8\v.1@\xf8:\x8c0\xe2\x8ey5@\xf8\xdfA:\xdc\x11\xc59@\xf8\x84\xf7C֔\x10>@\xf8\x95\xd6&\xe8\v.A@\xf8:\x8c0\xe2\x8eyE@\xf8\xdfA:\xdc\x11\xc5I@\xf8\x84\xf7C֔\x10N@\xf8\x95\xd6&\xe8\v.Q@\xf8:\x8c0\xe2\x8eyU@\xf8\xdfA:\xdc\x11\xc5Y@\xf8\x84\xf7C֔\x10^@\xf8\x95\xd6&\xe8\v.a@\xf8:\x8c0\xe2\x8eye@\xf8\xdfA:\xdc\x11\xc5i@\xf8\x84\xf7C֔\x10n@\xf8\x95\xd6&\xe8\v.q@\xf8:\x8c0\xe2\x8eyu@\xf8\xdfA:\xdc\x11\xc5y@\xf8\x84\xf7C֔\x10~@\xf8\x95\xd6&\xe8\v.\x81@\xf8:\x8c0\xe2\x8ey\x85@\xf8\xdfA:\xdc\x11ʼn@\xf8\x84\xf7C֔\x10\x8e@\xf8\x95\xd6&\xe8\v.\x91@\xf8:\x8c0\xe2\x8ey\x95@\xf8\xdfA:\xdc\x11ř@\xf8\x84\xf7C֔\x10\x9e@\xf8\x95\xd6&\xe8\v.\xa1@\xf8:\x8c0\xe2\x8ey\xa5@\xf8\xdfA:\xdc\x11ũ@\xf8\x84\xf7C֔\x10\xae@\xf8\x95\xd6&\xe8\v.\xb1@\xf8:\x8c0\xe2\x8ey\xb5@\xf8\xdfA:\xdc\x11Ź@\xf8\x84\xf7C֔\x10\xbe@\xf8\x95\xd6&\xe8\v.\xc1@\xf8:\x8c0\xe2\x8ey\xc5@\xf8\xdfA:\xdc\x11\xc5\xc9@\xf8\x84\xf7C֔\x10\xce@\xf8\x95\xd6&\xe8\v.\xd1@\xf8:\x8c0\xe2\x8ey\xd5@\xf8\xdfA:\xdc\x11\xc5\xd9@\xf8\x84\xf7C֔\x10\xde@\xf8\x95\xd6&\xe8\v.\xe1@\xf8:\x8c0\xe2\x8ey\xe5@\xf8\xdfA:\xdc\x11\xc5\xe9@\xf8\x84\xf7C֔\x10\xee@\xf8\x95\xd6&\xe8\v.\xf1@\xf8:\x8c0\xe2\x8ey\xf5@\xf8\xdfA:\xdc\x11\xc5\xf9@\xf8\x84\xf7C֔\x10\xfe@\xf8\x95\xd6&\xe8\v.\x01A\xfe\xf0\x7f\x00"
dserialize := func(data string) *metrics.Float64Histogram {
var res metrics.Float64Histogram
if err := gob.NewDecoder(bytes.NewReader([]byte(data))).Decode(&res); err != nil {
panic(err)
}
return &res
}
latency := RuntimeHistogramFromData(float64(time.Second), dserialize(sLatency))
b.ResetTimer()
b.ReportAllocs()
for i := 0; i < b.N; i++ {
snap := latency.Snapshot()
// These are the fields that influxdb accesses
_ = snap.Count()
_ = snap.Max()
_ = snap.Mean()
_ = snap.Min()
_ = snap.StdDev()
_ = snap.Variance()
_ = snap.Percentiles([]float64{0.25, 0.5, 0.75, 0.95, 0.99, 0.999, 0.9999})
}
}