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Diffstat (limited to 'vendor/github.com/rcrowley/go-metrics/sample.go')
| -rw-r--r-- | vendor/github.com/rcrowley/go-metrics/sample.go | 609 |
1 files changed, 609 insertions, 0 deletions
diff --git a/vendor/github.com/rcrowley/go-metrics/sample.go b/vendor/github.com/rcrowley/go-metrics/sample.go new file mode 100644 index 000000000..5f6a37788 --- /dev/null +++ b/vendor/github.com/rcrowley/go-metrics/sample.go @@ -0,0 +1,609 @@ +package metrics + +import ( + "math" + "math/rand" + "sort" + "sync" + "time" +) + +const rescaleThreshold = time.Hour + +// Samples maintain a statistically-significant selection of values from +// a stream. +type Sample interface { + Clear() + Count() int64 + Max() int64 + Mean() float64 + Min() int64 + Percentile(float64) float64 + Percentiles([]float64) []float64 + Size() int + Snapshot() Sample + StdDev() float64 + Sum() int64 + Update(int64) + Values() []int64 + Variance() float64 +} + +// ExpDecaySample is an exponentially-decaying sample using a forward-decaying +// priority reservoir. See Cormode et al's "Forward Decay: A Practical Time +// Decay Model for Streaming Systems". +// +// <http://www.research.att.com/people/Cormode_Graham/library/publications/CormodeShkapenyukSrivastavaXu09.pdf> +type ExpDecaySample struct { + alpha float64 + count int64 + mutex sync.Mutex + reservoirSize int + t0, t1 time.Time + values *expDecaySampleHeap +} + +// NewExpDecaySample constructs a new exponentially-decaying sample with the +// given reservoir size and alpha. +func NewExpDecaySample(reservoirSize int, alpha float64) Sample { + if UseNilMetrics { + return NilSample{} + } + s := &ExpDecaySample{ + alpha: alpha, + reservoirSize: reservoirSize, + t0: time.Now(), + values: newExpDecaySampleHeap(reservoirSize), + } + s.t1 = s.t0.Add(rescaleThreshold) + return s +} + +// Clear clears all samples. +func (s *ExpDecaySample) Clear() { + s.mutex.Lock() + defer s.mutex.Unlock() + s.count = 0 + s.t0 = time.Now() + s.t1 = s.t0.Add(rescaleThreshold) + s.values.Clear() +} + +// Count returns the number of samples recorded, which may exceed the +// reservoir size. +func (s *ExpDecaySample) Count() int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return s.count +} + +// Max returns the maximum value in the sample, which may not be the maximum +// value ever to be part of the sample. +func (s *ExpDecaySample) Max() int64 { + return SampleMax(s.Values()) +} + +// Mean returns the mean of the values in the sample. +func (s *ExpDecaySample) Mean() float64 { + return SampleMean(s.Values()) +} + +// Min returns the minimum value in the sample, which may not be the minimum +// value ever to be part of the sample. +func (s *ExpDecaySample) Min() int64 { + return SampleMin(s.Values()) +} + +// Percentile returns an arbitrary percentile of values in the sample. +func (s *ExpDecaySample) Percentile(p float64) float64 { + return SamplePercentile(s.Values(), p) +} + +// Percentiles returns a slice of arbitrary percentiles of values in the +// sample. +func (s *ExpDecaySample) Percentiles(ps []float64) []float64 { + return SamplePercentiles(s.Values(), ps) +} + +// Size returns the size of the sample, which is at most the reservoir size. +func (s *ExpDecaySample) Size() int { + s.mutex.Lock() + defer s.mutex.Unlock() + return s.values.Size() +} + +// Snapshot returns a read-only copy of the sample. +func (s *ExpDecaySample) Snapshot() Sample { + s.mutex.Lock() + defer s.mutex.Unlock() + vals := s.values.Values() + values := make([]int64, len(vals)) + for i, v := range vals { + values[i] = v.v + } + return &SampleSnapshot{ + count: s.count, + values: values, + } +} + +// StdDev returns the standard deviation of the values in the sample. +func (s *ExpDecaySample) StdDev() float64 { + return SampleStdDev(s.Values()) +} + +// Sum returns the sum of the values in the sample. +func (s *ExpDecaySample) Sum() int64 { + return SampleSum(s.Values()) +} + +// Update samples a new value. +func (s *ExpDecaySample) Update(v int64) { + s.update(time.Now(), v) +} + +// Values returns a copy of the values in the sample. +func (s *ExpDecaySample) Values() []int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + vals := s.values.Values() + values := make([]int64, len(vals)) + for i, v := range vals { + values[i] = v.v + } + return values +} + +// Variance returns the variance of the values in the sample. +func (s *ExpDecaySample) Variance() float64 { + return SampleVariance(s.Values()) +} + +// update samples a new value at a particular timestamp. This is a method all +// its own to facilitate testing. +func (s *ExpDecaySample) update(t time.Time, v int64) { + s.mutex.Lock() + defer s.mutex.Unlock() + s.count++ + if s.values.Size() == s.reservoirSize { + s.values.Pop() + } + s.values.Push(expDecaySample{ + k: math.Exp(t.Sub(s.t0).Seconds()*s.alpha) / rand.Float64(), + v: v, + }) + if t.After(s.t1) { + values := s.values.Values() + t0 := s.t0 + s.values.Clear() + s.t0 = t + s.t1 = s.t0.Add(rescaleThreshold) + for _, v := range values { + v.k = v.k * math.Exp(-s.alpha*s.t0.Sub(t0).Seconds()) + s.values.Push(v) + } + } +} + +// NilSample is a no-op Sample. +type NilSample struct{} + +// Clear is a no-op. +func (NilSample) Clear() {} + +// Count is a no-op. +func (NilSample) Count() int64 { return 0 } + +// Max is a no-op. +func (NilSample) Max() int64 { return 0 } + +// Mean is a no-op. +func (NilSample) Mean() float64 { return 0.0 } + +// Min is a no-op. +func (NilSample) Min() int64 { return 0 } + +// Percentile is a no-op. +func (NilSample) Percentile(p float64) float64 { return 0.0 } + +// Percentiles is a no-op. +func (NilSample) Percentiles(ps []float64) []float64 { + return make([]float64, len(ps)) +} + +// Size is a no-op. +func (NilSample) Size() int { return 0 } + +// Sample is a no-op. +func (NilSample) Snapshot() Sample { return NilSample{} } + +// StdDev is a no-op. +func (NilSample) StdDev() float64 { return 0.0 } + +// Sum is a no-op. +func (NilSample) Sum() int64 { return 0 } + +// Update is a no-op. +func (NilSample) Update(v int64) {} + +// Values is a no-op. +func (NilSample) Values() []int64 { return []int64{} } + +// Variance is a no-op. +func (NilSample) Variance() float64 { return 0.0 } + +// SampleMax returns the maximum value of the slice of int64. +func SampleMax(values []int64) int64 { + if 0 == len(values) { + return 0 + } + var max int64 = math.MinInt64 + for _, v := range values { + if max < v { + max = v + } + } + return max +} + +// SampleMean returns the mean value of the slice of int64. +func SampleMean(values []int64) float64 { + if 0 == len(values) { + return 0.0 + } + return float64(SampleSum(values)) / float64(len(values)) +} + +// SampleMin returns the minimum value of the slice of int64. +func SampleMin(values []int64) int64 { + if 0 == len(values) { + return 0 + } + var min int64 = math.MaxInt64 + for _, v := range values { + if min > v { + min = v + } + } + return min +} + +// SamplePercentiles returns an arbitrary percentile of the slice of int64. +func SamplePercentile(values int64Slice, p float64) float64 { + return SamplePercentiles(values, []float64{p})[0] +} + +// SamplePercentiles returns a slice of arbitrary percentiles of the slice of +// int64. +func SamplePercentiles(values int64Slice, ps []float64) []float64 { + scores := make([]float64, len(ps)) + size := len(values) + if size > 0 { + sort.Sort(values) + for i, p := range ps { + pos := p * float64(size+1) + if pos < 1.0 { + scores[i] = float64(values[0]) + } else if pos >= float64(size) { + scores[i] = float64(values[size-1]) + } else { + lower := float64(values[int(pos)-1]) + upper := float64(values[int(pos)]) + scores[i] = lower + (pos-math.Floor(pos))*(upper-lower) + } + } + } + return scores +} + +// SampleSnapshot is a read-only copy of another Sample. +type SampleSnapshot struct { + count int64 + values []int64 +} + +// Clear panics. +func (*SampleSnapshot) Clear() { + panic("Clear called on a SampleSnapshot") +} + +// Count returns the count of inputs at the time the snapshot was taken. +func (s *SampleSnapshot) Count() int64 { return s.count } + +// Max returns the maximal value at the time the snapshot was taken. +func (s *SampleSnapshot) Max() int64 { return SampleMax(s.values) } + +// Mean returns the mean value at the time the snapshot was taken. +func (s *SampleSnapshot) Mean() float64 { return SampleMean(s.values) } + +// Min returns the minimal value at the time the snapshot was taken. +func (s *SampleSnapshot) Min() int64 { return SampleMin(s.values) } + +// Percentile returns an arbitrary percentile of values at the time the +// snapshot was taken. +func (s *SampleSnapshot) Percentile(p float64) float64 { + return SamplePercentile(s.values, p) +} + +// Percentiles returns a slice of arbitrary percentiles of values at the time +// the snapshot was taken. +func (s *SampleSnapshot) Percentiles(ps []float64) []float64 { + return SamplePercentiles(s.values, ps) +} + +// Size returns the size of the sample at the time the snapshot was taken. +func (s *SampleSnapshot) Size() int { return len(s.values) } + +// Snapshot returns the snapshot. +func (s *SampleSnapshot) Snapshot() Sample { return s } + +// StdDev returns the standard deviation of values at the time the snapshot was +// taken. +func (s *SampleSnapshot) StdDev() float64 { return SampleStdDev(s.values) } + +// Sum returns the sum of values at the time the snapshot was taken. +func (s *SampleSnapshot) Sum() int64 { return SampleSum(s.values) } + +// Update panics. +func (*SampleSnapshot) Update(int64) { + panic("Update called on a SampleSnapshot") +} + +// Values returns a copy of the values in the sample. +func (s *SampleSnapshot) Values() []int64 { + values := make([]int64, len(s.values)) + copy(values, s.values) + return values +} + +// Variance returns the variance of values at the time the snapshot was taken. +func (s *SampleSnapshot) Variance() float64 { return SampleVariance(s.values) } + +// SampleStdDev returns the standard deviation of the slice of int64. +func SampleStdDev(values []int64) float64 { + return math.Sqrt(SampleVariance(values)) +} + +// SampleSum returns the sum of the slice of int64. +func SampleSum(values []int64) int64 { + var sum int64 + for _, v := range values { + sum += v + } + return sum +} + +// SampleVariance returns the variance of the slice of int64. +func SampleVariance(values []int64) float64 { + if 0 == len(values) { + return 0.0 + } + m := SampleMean(values) + var sum float64 + for _, v := range values { + d := float64(v) - m + sum += d * d + } + return sum / float64(len(values)) +} + +// A uniform sample using Vitter's Algorithm R. +// +// <http://www.cs.umd.edu/~samir/498/vitter.pdf> +type UniformSample struct { + count int64 + mutex sync.Mutex + reservoirSize int + values []int64 +} + +// NewUniformSample constructs a new uniform sample with the given reservoir +// size. +func NewUniformSample(reservoirSize int) Sample { + if UseNilMetrics { + return NilSample{} + } + return &UniformSample{ + reservoirSize: reservoirSize, + values: make([]int64, 0, reservoirSize), + } +} + +// Clear clears all samples. +func (s *UniformSample) Clear() { + s.mutex.Lock() + defer s.mutex.Unlock() + s.count = 0 + s.values = make([]int64, 0, s.reservoirSize) +} + +// Count returns the number of samples recorded, which may exceed the +// reservoir size. +func (s *UniformSample) Count() int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return s.count +} + +// Max returns the maximum value in the sample, which may not be the maximum +// value ever to be part of the sample. +func (s *UniformSample) Max() int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleMax(s.values) +} + +// Mean returns the mean of the values in the sample. +func (s *UniformSample) Mean() float64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleMean(s.values) +} + +// Min returns the minimum value in the sample, which may not be the minimum +// value ever to be part of the sample. +func (s *UniformSample) Min() int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleMin(s.values) +} + +// Percentile returns an arbitrary percentile of values in the sample. +func (s *UniformSample) Percentile(p float64) float64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SamplePercentile(s.values, p) +} + +// Percentiles returns a slice of arbitrary percentiles of values in the +// sample. +func (s *UniformSample) Percentiles(ps []float64) []float64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SamplePercentiles(s.values, ps) +} + +// Size returns the size of the sample, which is at most the reservoir size. +func (s *UniformSample) Size() int { + s.mutex.Lock() + defer s.mutex.Unlock() + return len(s.values) +} + +// Snapshot returns a read-only copy of the sample. +func (s *UniformSample) Snapshot() Sample { + s.mutex.Lock() + defer s.mutex.Unlock() + values := make([]int64, len(s.values)) + copy(values, s.values) + return &SampleSnapshot{ + count: s.count, + values: values, + } +} + +// StdDev returns the standard deviation of the values in the sample. +func (s *UniformSample) StdDev() float64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleStdDev(s.values) +} + +// Sum returns the sum of the values in the sample. +func (s *UniformSample) Sum() int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleSum(s.values) +} + +// Update samples a new value. +func (s *UniformSample) Update(v int64) { + s.mutex.Lock() + defer s.mutex.Unlock() + s.count++ + if len(s.values) < s.reservoirSize { + s.values = append(s.values, v) + } else { + r := rand.Int63n(s.count) + if r < int64(len(s.values)) { + s.values[int(r)] = v + } + } +} + +// Values returns a copy of the values in the sample. +func (s *UniformSample) Values() []int64 { + s.mutex.Lock() + defer s.mutex.Unlock() + values := make([]int64, len(s.values)) + copy(values, s.values) + return values +} + +// Variance returns the variance of the values in the sample. +func (s *UniformSample) Variance() float64 { + s.mutex.Lock() + defer s.mutex.Unlock() + return SampleVariance(s.values) +} + +// expDecaySample represents an individual sample in a heap. +type expDecaySample struct { + k float64 + v int64 +} + +func newExpDecaySampleHeap(reservoirSize int) *expDecaySampleHeap { + return &expDecaySampleHeap{make([]expDecaySample, 0, reservoirSize)} +} + +// expDecaySampleHeap is a min-heap of expDecaySamples. +// The internal implementation is copied from the standard library's container/heap +type expDecaySampleHeap struct { + s []expDecaySample +} + +func (h *expDecaySampleHeap) Clear() { + h.s = h.s[:0] +} + +func (h *expDecaySampleHeap) Push(s expDecaySample) { + n := len(h.s) + h.s = h.s[0 : n+1] + h.s[n] = s + h.up(n) +} + +func (h *expDecaySampleHeap) Pop() expDecaySample { + n := len(h.s) - 1 + h.s[0], h.s[n] = h.s[n], h.s[0] + h.down(0, n) + + n = len(h.s) + s := h.s[n-1] + h.s = h.s[0 : n-1] + return s +} + +func (h *expDecaySampleHeap) Size() int { + return len(h.s) +} + +func (h *expDecaySampleHeap) Values() []expDecaySample { + return h.s +} + +func (h *expDecaySampleHeap) up(j int) { + for { + i := (j - 1) / 2 // parent + if i == j || !(h.s[j].k < h.s[i].k) { + break + } + h.s[i], h.s[j] = h.s[j], h.s[i] + j = i + } +} + +func (h *expDecaySampleHeap) down(i, n int) { + for { + j1 := 2*i + 1 + if j1 >= n || j1 < 0 { // j1 < 0 after int overflow + break + } + j := j1 // left child + if j2 := j1 + 1; j2 < n && !(h.s[j1].k < h.s[j2].k) { + j = j2 // = 2*i + 2 // right child + } + if !(h.s[j].k < h.s[i].k) { + break + } + h.s[i], h.s[j] = h.s[j], h.s[i] + i = j + } +} + +type int64Slice []int64 + +func (p int64Slice) Len() int { return len(p) } +func (p int64Slice) Less(i, j int) bool { return p[i] < p[j] } +func (p int64Slice) Swap(i, j int) { p[i], p[j] = p[j], p[i] } |