219 lines
5.1 KiB
Go
219 lines
5.1 KiB
Go
// Package generic implements generic versions of each of the metric types. They
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// can be embedded by other implementations, and converted to specific formats
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// as necessary.
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package generic
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import (
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"fmt"
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"io"
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"math"
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"sync"
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"sync/atomic"
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"github.com/VividCortex/gohistogram"
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"github.com/go-kit/kit/metrics"
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"github.com/go-kit/kit/metrics/internal/lv"
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)
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// Counter is an in-memory implementation of a Counter.
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type Counter struct {
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Name string
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lvs lv.LabelValues
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bits uint64
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}
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// NewCounter returns a new, usable Counter.
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func NewCounter(name string) *Counter {
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return &Counter{
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Name: name,
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}
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}
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// With implements Counter.
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func (c *Counter) With(labelValues ...string) metrics.Counter {
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return &Counter{
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bits: atomic.LoadUint64(&c.bits),
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lvs: c.lvs.With(labelValues...),
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}
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}
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// Add implements Counter.
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func (c *Counter) Add(delta float64) {
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for {
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var (
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old = atomic.LoadUint64(&c.bits)
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newf = math.Float64frombits(old) + delta
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new = math.Float64bits(newf)
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)
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if atomic.CompareAndSwapUint64(&c.bits, old, new) {
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break
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}
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}
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}
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// Value returns the current value of the counter.
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func (c *Counter) Value() float64 {
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return math.Float64frombits(atomic.LoadUint64(&c.bits))
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}
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// ValueReset returns the current value of the counter, and resets it to zero.
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// This is useful for metrics backends whose counter aggregations expect deltas,
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// like Graphite.
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func (c *Counter) ValueReset() float64 {
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for {
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var (
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old = atomic.LoadUint64(&c.bits)
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newf = 0.0
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new = math.Float64bits(newf)
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)
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if atomic.CompareAndSwapUint64(&c.bits, old, new) {
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return math.Float64frombits(old)
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}
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}
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}
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// LabelValues returns the set of label values attached to the counter.
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func (c *Counter) LabelValues() []string {
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return c.lvs
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}
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// Gauge is an in-memory implementation of a Gauge.
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type Gauge struct {
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Name string
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lvs lv.LabelValues
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bits uint64
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}
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// NewGauge returns a new, usable Gauge.
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func NewGauge(name string) *Gauge {
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return &Gauge{
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Name: name,
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}
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}
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// With implements Gauge.
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func (g *Gauge) With(labelValues ...string) metrics.Gauge {
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return &Gauge{
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bits: atomic.LoadUint64(&g.bits),
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lvs: g.lvs.With(labelValues...),
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}
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}
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// Set implements Gauge.
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func (g *Gauge) Set(value float64) {
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atomic.StoreUint64(&g.bits, math.Float64bits(value))
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}
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// Value returns the current value of the gauge.
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func (g *Gauge) Value() float64 {
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return math.Float64frombits(atomic.LoadUint64(&g.bits))
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}
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// LabelValues returns the set of label values attached to the gauge.
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func (g *Gauge) LabelValues() []string {
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return g.lvs
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}
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// Histogram is an in-memory implementation of a streaming histogram, based on
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// VividCortex/gohistogram. It dynamically computes quantiles, so it's not
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// suitable for aggregation.
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type Histogram struct {
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Name string
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lvs lv.LabelValues
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h gohistogram.Histogram
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}
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// NewHistogram returns a numeric histogram based on VividCortex/gohistogram. A
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// good default value for buckets is 50.
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func NewHistogram(name string, buckets int) *Histogram {
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return &Histogram{
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Name: name,
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h: gohistogram.NewHistogram(buckets),
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}
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}
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// With implements Histogram.
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func (h *Histogram) With(labelValues ...string) metrics.Histogram {
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return &Histogram{
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lvs: h.lvs.With(labelValues...),
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h: h.h,
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}
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}
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// Observe implements Histogram.
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func (h *Histogram) Observe(value float64) {
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h.h.Add(value)
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}
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// Quantile returns the value of the quantile q, 0.0 < q < 1.0.
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func (h *Histogram) Quantile(q float64) float64 {
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return h.h.Quantile(q)
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}
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// LabelValues returns the set of label values attached to the histogram.
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func (h *Histogram) LabelValues() []string {
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return h.lvs
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}
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// Print writes a string representation of the histogram to the passed writer.
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// Useful for printing to a terminal.
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func (h *Histogram) Print(w io.Writer) {
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fmt.Fprintf(w, h.h.String())
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}
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// Bucket is a range in a histogram which aggregates observations.
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type Bucket struct {
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From, To, Count int64
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}
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// Quantile is a pair of a quantile (0..100) and its observed maximum value.
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type Quantile struct {
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Quantile int // 0..100
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Value int64
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}
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// SimpleHistogram is an in-memory implementation of a Histogram. It only tracks
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// an approximate moving average, so is likely too naïve for many use cases.
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type SimpleHistogram struct {
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mtx sync.RWMutex
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lvs lv.LabelValues
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avg float64
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n uint64
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}
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// NewSimpleHistogram returns a SimpleHistogram, ready for observations.
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func NewSimpleHistogram() *SimpleHistogram {
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return &SimpleHistogram{}
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}
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// With implements Histogram.
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func (h *SimpleHistogram) With(labelValues ...string) metrics.Histogram {
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return &SimpleHistogram{
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lvs: h.lvs.With(labelValues...),
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avg: h.avg,
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n: h.n,
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}
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}
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// Observe implements Histogram.
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func (h *SimpleHistogram) Observe(value float64) {
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h.mtx.Lock()
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defer h.mtx.Unlock()
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h.n++
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h.avg -= h.avg / float64(h.n)
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h.avg += value / float64(h.n)
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}
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// ApproximateMovingAverage returns the approximate moving average of observations.
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func (h *SimpleHistogram) ApproximateMovingAverage() float64 {
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h.mtx.RLock()
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h.mtx.RUnlock()
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return h.avg
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}
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// LabelValues returns the set of label values attached to the histogram.
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func (h *SimpleHistogram) LabelValues() []string {
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return h.lvs
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}
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