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package metrics
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import (
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"bytes"
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"encoding/gob"
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"fmt"
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"math"
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"reflect"
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"runtime/metrics"
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"testing"
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"time"
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)
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var _ Histogram = (*runtimeHistogram)(nil)
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type runtimeHistogramTest struct {
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h metrics.Float64Histogram
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Count int64
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Min int64
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Max int64
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Sum int64
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Mean float64
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Variance float64
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StdDev float64
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Percentiles []float64 // .5 .8 .9 .99 .995
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}
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// This test checks the results of statistical functions implemented
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// by runtimeHistogramSnapshot.
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func TestRuntimeHistogramStats(t *testing.T) {
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tests := []runtimeHistogramTest{
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0: {
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h: metrics.Float64Histogram{
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Counts: []uint64{},
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Buckets: []float64{},
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},
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Count: 0,
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Max: 0,
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Min: 0,
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Sum: 0,
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Mean: 0,
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Variance: 0,
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StdDev: 0,
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Percentiles: []float64{0, 0, 0, 0, 0},
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},
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1: {
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// This checks the case where the highest bucket is +Inf.
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h: metrics.Float64Histogram{
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Counts: []uint64{0, 1, 2},
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Buckets: []float64{0, 0.5, 1, math.Inf(1)},
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},
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Count: 3,
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Max: 1,
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Min: 0,
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Sum: 3,
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Mean: 0.9166666,
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Percentiles: []float64{1, 1, 1, 1, 1},
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Variance: 0.020833,
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StdDev: 0.144433,
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},
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2: {
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h: metrics.Float64Histogram{
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Counts: []uint64{8, 6, 3, 1},
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Buckets: []float64{12, 16, 18, 24, 25},
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},
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Count: 18,
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Max: 25,
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Min: 12,
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Sum: 270,
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Mean: 16.75,
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Variance: 10.3015,
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StdDev: 3.2096,
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Percentiles: []float64{16, 18, 18, 24, 24},
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},
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}
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for i, test := range tests {
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t.Run(fmt.Sprint(i), func(t *testing.T) {
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s := RuntimeHistogramFromData(1.0, &test.h).Snapshot()
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if v := s.Count(); v != test.Count {
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t.Errorf("Count() = %v, want %v", v, test.Count)
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}
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if v := s.Min(); v != test.Min {
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t.Errorf("Min() = %v, want %v", v, test.Min)
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}
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if v := s.Max(); v != test.Max {
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t.Errorf("Max() = %v, want %v", v, test.Max)
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}
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if v := s.Sum(); v != test.Sum {
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t.Errorf("Sum() = %v, want %v", v, test.Sum)
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}
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if v := s.Mean(); !approxEqual(v, test.Mean, 0.0001) {
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t.Errorf("Mean() = %v, want %v", v, test.Mean)
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}
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if v := s.Variance(); !approxEqual(v, test.Variance, 0.0001) {
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t.Errorf("Variance() = %v, want %v", v, test.Variance)
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}
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if v := s.StdDev(); !approxEqual(v, test.StdDev, 0.0001) {
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t.Errorf("StdDev() = %v, want %v", v, test.StdDev)
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}
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ps := []float64{.5, .8, .9, .99, .995}
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if v := s.Percentiles(ps); !reflect.DeepEqual(v, test.Percentiles) {
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t.Errorf("Percentiles(%v) = %v, want %v", ps, v, test.Percentiles)
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}
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})
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}
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}
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func approxEqual(x, y, ε float64) bool {
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if math.IsInf(x, -1) && math.IsInf(y, -1) {
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return true
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}
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if math.IsInf(x, 1) && math.IsInf(y, 1) {
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return true
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}
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if math.IsNaN(x) && math.IsNaN(y) {
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return true
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}
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return math.Abs(x-y) < ε
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}
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// This test verifies that requesting Percentiles in unsorted order
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// returns them in the requested order.
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func TestRuntimeHistogramStatsPercentileOrder(t *testing.T) {
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s := RuntimeHistogramFromData(1.0, &metrics.Float64Histogram{
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Counts: []uint64{1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
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Buckets: []float64{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
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}).Snapshot()
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result := s.Percentiles([]float64{1, 0.2, 0.5, 0.1, 0.2})
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expected := []float64{10, 2, 5, 1, 2}
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if !reflect.DeepEqual(result, expected) {
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t.Fatal("wrong result:", result)
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}
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}
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func BenchmarkRuntimeHistogramSnapshotRead(b *testing.B) {
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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"
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dserialize := func(data string) *metrics.Float64Histogram {
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var res metrics.Float64Histogram
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if err := gob.NewDecoder(bytes.NewReader([]byte(data))).Decode(&res); err != nil {
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panic(err)
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}
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return &res
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}
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latency := RuntimeHistogramFromData(float64(time.Second), dserialize(sLatency))
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b.ResetTimer()
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b.ReportAllocs()
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for i := 0; i < b.N; i++ {
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snap := latency.Snapshot()
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// These are the fields that influxdb accesses
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_ = snap.Count()
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_ = snap.Max()
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_ = snap.Mean()
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_ = snap.Min()
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_ = snap.StdDev()
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_ = snap.Variance()
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_ = snap.Percentiles([]float64{0.25, 0.5, 0.75, 0.95, 0.99, 0.999, 0.9999})
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}
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}
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