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// Copyright 2014 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package prometheus
import (
"fmt"
"math"
"runtime"
"sort"
"sync"
"sync/atomic"
"time"
"github.com/beorn7/perks/quantile"
"github.com/golang/protobuf/proto"
dto "github.com/prometheus/client_model/go"
)
// quantileLabel is used for the label that defines the quantile in a
// summary.
const quantileLabel = "quantile"
// A Summary captures individual observations from an event or sample stream and
// summarizes them in a manner similar to traditional summary statistics: 1. sum
// of observations, 2. observation count, 3. rank estimations.
//
// A typical use-case is the observation of request latencies. By default, a
// Summary provides the median, the 90th and the 99th percentile of the latency
// as rank estimations. However, the default behavior will change in the
// upcoming v1.0.0 of the library. There will be no rank estimations at all by
// default. For a sane transition, it is recommended to set the desired rank
// estimations explicitly.
//
// Note that the rank estimations cannot be aggregated in a meaningful way with
// the Prometheus query language (i.e. you cannot average or add them). If you
// need aggregatable quantiles (e.g. you want the 99th percentile latency of all
// queries served across all instances of a service), consider the Histogram
// metric type. See the Prometheus documentation for more details.
//
// To create Summary instances, use NewSummary.
type Summary interface {
Metric
Collector
// Observe adds a single observation to the summary.
Observe(float64)
}
var errQuantileLabelNotAllowed = fmt.Errorf(
"%q is not allowed as label name in summaries", quantileLabel,
)
// Default values for SummaryOpts.
const (
// DefMaxAge is the default duration for which observations stay
// relevant.
DefMaxAge time.Duration = 10 * time.Minute
// DefAgeBuckets is the default number of buckets used to calculate the
// age of observations.
DefAgeBuckets = 5
// DefBufCap is the standard buffer size for collecting Summary observations.
DefBufCap = 500
)
// SummaryOpts bundles the options for creating a Summary metric. It is
// mandatory to set Name to a non-empty string. While all other fields are
// optional and can safely be left at their zero value, it is recommended to set
// a help string and to explicitly set the Objectives field to the desired value
// as the default value will change in the upcoming v1.0.0 of the library.
type SummaryOpts struct {
// Namespace, Subsystem, and Name are components of the fully-qualified
// name of the Summary (created by joining these components with
// "_"). Only Name is mandatory, the others merely help structuring the
// name. Note that the fully-qualified name of the Summary must be a
// valid Prometheus metric name.
Namespace string
Subsystem string
Name string
// Help provides information about this Summary.
//
// Metrics with the same fully-qualified name must have the same Help
// string.
Help string
// ConstLabels are used to attach fixed labels to this metric. Metrics
// with the same fully-qualified name must have the same label names in
// their ConstLabels.
//
// Due to the way a Summary is represented in the Prometheus text format
// and how it is handled by the Prometheus server internally, “quantile”
// is an illegal label name. Construction of a Summary or SummaryVec
// will panic if this label name is used in ConstLabels.
//
// ConstLabels are only used rarely. In particular, do not use them to
// attach the same labels to all your metrics. Those use cases are
// better covered by target labels set by the scraping Prometheus
// server, or by one specific metric (e.g. a build_info or a
// machine_role metric). See also
// https://prometheus.io/docs/instrumenting/writing_exporters/#target-labels,-not-static-scraped-labels
ConstLabels Labels
// Objectives defines the quantile rank estimates with their respective
// absolute error. If Objectives[q] = e, then the value reported for q
// will be the φ-quantile value for some φ between q-e and q+e. The
// default value is an empty map, resulting in a summary without
// quantiles.
Objectives map[float64]float64
// MaxAge defines the duration for which an observation stays relevant
// for the summary. Must be positive. The default value is DefMaxAge.
MaxAge time.Duration
// AgeBuckets is the number of buckets used to exclude observations that
// are older than MaxAge from the summary. A higher number has a
// resource penalty, so only increase it if the higher resolution is
// really required. For very high observation rates, you might want to
// reduce the number of age buckets. With only one age bucket, you will
// effectively see a complete reset of the summary each time MaxAge has
// passed. The default value is DefAgeBuckets.
AgeBuckets uint32
// BufCap defines the default sample stream buffer size. The default
// value of DefBufCap should suffice for most uses. If there is a need
// to increase the value, a multiple of 500 is recommended (because that
// is the internal buffer size of the underlying package
// "github.com/bmizerany/perks/quantile").
BufCap uint32
}
// Problem with the sliding-window decay algorithm... The Merge method of
// perk/quantile is actually not working as advertised - and it might be
// unfixable, as the underlying algorithm is apparently not capable of merging
// summaries in the first place. To avoid using Merge, we are currently adding
// observations to _each_ age bucket, i.e. the effort to add a sample is
// essentially multiplied by the number of age buckets. When rotating age
// buckets, we empty the previous head stream. On scrape time, we simply take
// the quantiles from the head stream (no merging required). Result: More effort
// on observation time, less effort on scrape time, which is exactly the
// opposite of what we try to accomplish, but at least the results are correct.
//
// The quite elegant previous contraption to merge the age buckets efficiently
// on scrape time (see code up commit 6b9530d72ea715f0ba612c0120e6e09fbf1d49d0)
// can't be used anymore.
// NewSummary creates a new Summary based on the provided SummaryOpts.
func NewSummary(opts SummaryOpts) Summary {
return newSummary(
NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
opts.Help,
nil,
opts.ConstLabels,
),
opts,
)
}
func newSummary(desc *Desc, opts SummaryOpts, labelValues ...string) Summary {
if len(desc.variableLabels) != len(labelValues) {
panic(makeInconsistentCardinalityError(desc.fqName, desc.variableLabels, labelValues))
}
for _, n := range desc.variableLabels {
if n == quantileLabel {
panic(errQuantileLabelNotAllowed)
}
}
for _, lp := range desc.constLabelPairs {
if lp.GetName() == quantileLabel {
panic(errQuantileLabelNotAllowed)
}
}
if opts.Objectives == nil {
opts.Objectives = map[float64]float64{}
}
if opts.MaxAge < 0 {
panic(fmt.Errorf("illegal max age MaxAge=%v", opts.MaxAge))
}
if opts.MaxAge == 0 {
opts.MaxAge = DefMaxAge
}
if opts.AgeBuckets == 0 {
opts.AgeBuckets = DefAgeBuckets
}
if opts.BufCap == 0 {
opts.BufCap = DefBufCap
}
if len(opts.Objectives) == 0 {
// Use the lock-free implementation of a Summary without objectives.
s := &noObjectivesSummary{
desc: desc,
labelPairs: makeLabelPairs(desc, labelValues),
counts: [2]*summaryCounts{&summaryCounts{}, &summaryCounts{}},
}
s.init(s) // Init self-collection.
return s
}
s := &summary{
desc: desc,
objectives: opts.Objectives,
sortedObjectives: make([]float64, 0, len(opts.Objectives)),
labelPairs: makeLabelPairs(desc, labelValues),
hotBuf: make([]float64, 0, opts.BufCap),
coldBuf: make([]float64, 0, opts.BufCap),
streamDuration: opts.MaxAge / time.Duration(opts.AgeBuckets),
}
s.headStreamExpTime = time.Now().Add(s.streamDuration)
s.hotBufExpTime = s.headStreamExpTime
for i := uint32(0); i < opts.AgeBuckets; i++ {
s.streams = append(s.streams, s.newStream())
}
s.headStream = s.streams[0]
for qu := range s.objectives {
s.sortedObjectives = append(s.sortedObjectives, qu)
}
sort.Float64s(s.sortedObjectives)
s.init(s) // Init self-collection.
return s
}
type summary struct {
selfCollector
bufMtx sync.Mutex // Protects hotBuf and hotBufExpTime.
mtx sync.Mutex // Protects every other moving part.
// Lock bufMtx before mtx if both are needed.
desc *Desc
objectives map[float64]float64
sortedObjectives []float64
labelPairs []*dto.LabelPair
sum float64
cnt uint64
hotBuf, coldBuf []float64
streams []*quantile.Stream
streamDuration time.Duration
headStream *quantile.Stream
headStreamIdx int
headStreamExpTime, hotBufExpTime time.Time
}
func (s *summary) Desc() *Desc {
return s.desc
}
func (s *summary) Observe(v float64) {
s.bufMtx.Lock()
defer s.bufMtx.Unlock()
now := time.Now()
if now.After(s.hotBufExpTime) {
s.asyncFlush(now)
}
s.hotBuf = append(s.hotBuf, v)
if len(s.hotBuf) == cap(s.hotBuf) {
s.asyncFlush(now)
}
}
func (s *summary) Write(out *dto.Metric) error {
sum := &dto.Summary{}
qs := make([]*dto.Quantile, 0, len(s.objectives))
s.bufMtx.Lock()
s.mtx.Lock()
// Swap bufs even if hotBuf is empty to set new hotBufExpTime.
s.swapBufs(time.Now())
s.bufMtx.Unlock()
s.flushColdBuf()
sum.SampleCount = proto.Uint64(s.cnt)
sum.SampleSum = proto.Float64(s.sum)
for _, rank := range s.sortedObjectives {
var q float64
if s.headStream.Count() == 0 {
q = math.NaN()
} else {
q = s.headStream.Query(rank)
}
qs = append(qs, &dto.Quantile{
Quantile: proto.Float64(rank),
Value: proto.Float64(q),
})
}
s.mtx.Unlock()
if len(qs) > 0 {
sort.Sort(quantSort(qs))
}
sum.Quantile = qs
out.Summary = sum
out.Label = s.labelPairs
return nil
}
func (s *summary) newStream() *quantile.Stream {
return quantile.NewTargeted(s.objectives)
}
// asyncFlush needs bufMtx locked.
func (s *summary) asyncFlush(now time.Time) {
s.mtx.Lock()
s.swapBufs(now)
// Unblock the original goroutine that was responsible for the mutation
// that triggered the compaction. But hold onto the global non-buffer
// state mutex until the operation finishes.
go func() {
s.flushColdBuf()
s.mtx.Unlock()
}()
}
// rotateStreams needs mtx AND bufMtx locked.
func (s *summary) maybeRotateStreams() {
for !s.hotBufExpTime.Equal(s.headStreamExpTime) {
s.headStream.Reset()
s.headStreamIdx++
if s.headStreamIdx >= len(s.streams) {
s.headStreamIdx = 0
}
s.headStream = s.streams[s.headStreamIdx]
s.headStreamExpTime = s.headStreamExpTime.Add(s.streamDuration)
}
}
// flushColdBuf needs mtx locked.
func (s *summary) flushColdBuf() {
for _, v := range s.coldBuf {
for _, stream := range s.streams {
stream.Insert(v)
}
s.cnt++
s.sum += v
}
s.coldBuf = s.coldBuf[0:0]
s.maybeRotateStreams()
}
// swapBufs needs mtx AND bufMtx locked, coldBuf must be empty.
func (s *summary) swapBufs(now time.Time) {
if len(s.coldBuf) != 0 {
panic("coldBuf is not empty")
}
s.hotBuf, s.coldBuf = s.coldBuf, s.hotBuf
// hotBuf is now empty and gets new expiration set.
for now.After(s.hotBufExpTime) {
s.hotBufExpTime = s.hotBufExpTime.Add(s.streamDuration)
}
}
type summaryCounts struct {
// sumBits contains the bits of the float64 representing the sum of all
// observations. sumBits and count have to go first in the struct to
// guarantee alignment for atomic operations.
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG
sumBits uint64
count uint64
}
type noObjectivesSummary struct {
// countAndHotIdx enables lock-free writes with use of atomic updates.
// The most significant bit is the hot index [0 or 1] of the count field
// below. Observe calls update the hot one. All remaining bits count the
// number of Observe calls. Observe starts by incrementing this counter,
// and finish by incrementing the count field in the respective
// summaryCounts, as a marker for completion.
//
// Calls of the Write method (which are non-mutating reads from the
// perspective of the summary) swap the hot–cold under the writeMtx
// lock. A cooldown is awaited (while locked) by comparing the number of
// observations with the initiation count. Once they match, then the
// last observation on the now cool one has completed. All cool fields must
// be merged into the new hot before releasing writeMtx.
// Fields with atomic access first! See alignment constraint:
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG
countAndHotIdx uint64
selfCollector
desc *Desc
writeMtx sync.Mutex // Only used in the Write method.
// Two counts, one is "hot" for lock-free observations, the other is
// "cold" for writing out a dto.Metric. It has to be an array of
// pointers to guarantee 64bit alignment of the histogramCounts, see
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG.
counts [2]*summaryCounts
labelPairs []*dto.LabelPair
}
func (s *noObjectivesSummary) Desc() *Desc {
return s.desc
}
func (s *noObjectivesSummary) Observe(v float64) {
// We increment h.countAndHotIdx so that the counter in the lower
// 63 bits gets incremented. At the same time, we get the new value
// back, which we can use to find the currently-hot counts.
n := atomic.AddUint64(&s.countAndHotIdx, 1)
hotCounts := s.counts[n>>63]
for {
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
break
}
}
// Increment count last as we take it as a signal that the observation
// is complete.
atomic.AddUint64(&hotCounts.count, 1)
}
func (s *noObjectivesSummary) Write(out *dto.Metric) error {
// For simplicity, we protect this whole method by a mutex. It is not in
// the hot path, i.e. Observe is called much more often than Write. The
// complication of making Write lock-free isn't worth it, if possible at
// all.
s.writeMtx.Lock()
defer s.writeMtx.Unlock()
// Adding 1<<63 switches the hot index (from 0 to 1 or from 1 to 0)
// without touching the count bits. See the struct comments for a full
// description of the algorithm.
n := atomic.AddUint64(&s.countAndHotIdx, 1<<63)
// count is contained unchanged in the lower 63 bits.
count := n & ((1 << 63) - 1)
// The most significant bit tells us which counts is hot. The complement
// is thus the cold one.
hotCounts := s.counts[n>>63]
coldCounts := s.counts[(^n)>>63]
// Await cooldown.
for count != atomic.LoadUint64(&coldCounts.count) {
runtime.Gosched() // Let observations get work done.
}
sum := &dto.Summary{
SampleCount: proto.Uint64(count),
SampleSum: proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sumBits))),
}
out.Summary = sum
out.Label = s.labelPairs
// Finally add all the cold counts to the new hot counts and reset the cold counts.
atomic.AddUint64(&hotCounts.count, count)
atomic.StoreUint64(&coldCounts.count, 0)
for {
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + sum.GetSampleSum())
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
atomic.StoreUint64(&coldCounts.sumBits, 0)
break
}
}
return nil
}
type quantSort []*dto.Quantile
func (s quantSort) Len() int {
return len(s)
}
func (s quantSort) Swap(i, j int) {
s[i], s[j] = s[j], s[i]
}
func (s quantSort) Less(i, j int) bool {
return s[i].GetQuantile() < s[j].GetQuantile()
}
// SummaryVec is a Collector that bundles a set of Summaries that all share the
// same Desc, but have different values for their variable labels. This is used
// if you want to count the same thing partitioned by various dimensions
// (e.g. HTTP request latencies, partitioned by status code and method). Create
// instances with NewSummaryVec.
type SummaryVec struct {
*metricVec
}
// NewSummaryVec creates a new SummaryVec based on the provided SummaryOpts and
// partitioned by the given label names.
//
// Due to the way a Summary is represented in the Prometheus text format and how
// it is handled by the Prometheus server internally, “quantile” is an illegal
// label name. NewSummaryVec will panic if this label name is used.
func NewSummaryVec(opts SummaryOpts, labelNames []string) *SummaryVec {
for _, ln := range labelNames {
if ln == quantileLabel {
panic(errQuantileLabelNotAllowed)
}
}
desc := NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
opts.Help,
labelNames,
opts.ConstLabels,
)
return &SummaryVec{
metricVec: newMetricVec(desc, func(lvs ...string) Metric {
return newSummary(desc, opts, lvs...)
}),
}
}
// GetMetricWithLabelValues returns the Summary for the given slice of label
// values (same order as the VariableLabels in Desc). If that combination of
// label values is accessed for the first time, a new Summary is created.
//
// It is possible to call this method without using the returned Summary to only
// create the new Summary but leave it at its starting value, a Summary without
// any observations.
//
// Keeping the Summary for later use is possible (and should be considered if
// performance is critical), but keep in mind that Reset, DeleteLabelValues and
// Delete can be used to delete the Summary from the SummaryVec. In that case,
// the Summary will still exist, but it will not be exported anymore, even if a
// Summary with the same label values is created later. See also the CounterVec
// example.
//
// An error is returned if the number of label values is not the same as the
// number of VariableLabels in Desc (minus any curried labels).
//
// Note that for more than one label value, this method is prone to mistakes
// caused by an incorrect order of arguments. Consider GetMetricWith(Labels) as
// an alternative to avoid that type of mistake. For higher label numbers, the
// latter has a much more readable (albeit more verbose) syntax, but it comes
// with a performance overhead (for creating and processing the Labels map).
// See also the GaugeVec example.
func (v *SummaryVec) GetMetricWithLabelValues(lvs ...string) (Observer, error) {
metric, err := v.metricVec.getMetricWithLabelValues(lvs...)
if metric != nil {
return metric.(Observer), err
}
return nil, err
}
// GetMetricWith returns the Summary for the given Labels map (the label names
// must match those of the VariableLabels in Desc). If that label map is
// accessed for the first time, a new Summary is created. Implications of
// creating a Summary without using it and keeping the Summary for later use are
// the same as for GetMetricWithLabelValues.
//
// An error is returned if the number and names of the Labels are inconsistent
// with those of the VariableLabels in Desc (minus any curried labels).
//
// This method is used for the same purpose as
// GetMetricWithLabelValues(...string). See there for pros and cons of the two
// methods.
func (v *SummaryVec) GetMetricWith(labels Labels) (Observer, error) {
metric, err := v.metricVec.getMetricWith(labels)
if metric != nil {
return metric.(Observer), err
}
return nil, err
}
// WithLabelValues works as GetMetricWithLabelValues, but panics where
// GetMetricWithLabelValues would have returned an error. Not returning an
// error allows shortcuts like
// myVec.WithLabelValues("404", "GET").Observe(42.21)
func (v *SummaryVec) WithLabelValues(lvs ...string) Observer {
s, err := v.GetMetricWithLabelValues(lvs...)
if err != nil {
panic(err)
}
return s
}
// With works as GetMetricWith, but panics where GetMetricWithLabels would have
// returned an error. Not returning an error allows shortcuts like
// myVec.With(prometheus.Labels{"code": "404", "method": "GET"}).Observe(42.21)
func (v *SummaryVec) With(labels Labels) Observer {
s, err := v.GetMetricWith(labels)
if err != nil {
panic(err)
}
return s
}
// CurryWith returns a vector curried with the provided labels, i.e. the
// returned vector has those labels pre-set for all labeled operations performed
// on it. The cardinality of the curried vector is reduced accordingly. The
// order of the remaining labels stays the same (just with the curried labels
// taken out of the sequence – which is relevant for the
// (GetMetric)WithLabelValues methods). It is possible to curry a curried
// vector, but only with labels not yet used for currying before.
//
// The metrics contained in the SummaryVec are shared between the curried and
// uncurried vectors. They are just accessed differently. Curried and uncurried
// vectors behave identically in terms of collection. Only one must be
// registered with a given registry (usually the uncurried version). The Reset
// method deletes all metrics, even if called on a curried vector.
func (v *SummaryVec) CurryWith(labels Labels) (ObserverVec, error) {
vec, err := v.curryWith(labels)
if vec != nil {
return &SummaryVec{vec}, err
}
return nil, err
}
// MustCurryWith works as CurryWith but panics where CurryWith would have
// returned an error.
func (v *SummaryVec) MustCurryWith(labels Labels) ObserverVec {
vec, err := v.CurryWith(labels)
if err != nil {
panic(err)
}
return vec
}
type constSummary struct {
desc *Desc
count uint64
sum float64
quantiles map[float64]float64
labelPairs []*dto.LabelPair
}
func (s *constSummary) Desc() *Desc {
return s.desc
}
func (s *constSummary) Write(out *dto.Metric) error {
sum := &dto.Summary{}
qs := make([]*dto.Quantile, 0, len(s.quantiles))
sum.SampleCount = proto.Uint64(s.count)
sum.SampleSum = proto.Float64(s.sum)
for rank, q := range s.quantiles {
qs = append(qs, &dto.Quantile{
Quantile: proto.Float64(rank),
Value: proto.Float64(q),
})
}
if len(qs) > 0 {
sort.Sort(quantSort(qs))
}
sum.Quantile = qs
out.Summary = sum
out.Label = s.labelPairs
return nil
}
// NewConstSummary returns a metric representing a Prometheus summary with fixed
// values for the count, sum, and quantiles. As those parameters cannot be
// changed, the returned value does not implement the Summary interface (but
// only the Metric interface). Users of this package will not have much use for
// it in regular operations. However, when implementing custom Collectors, it is
// useful as a throw-away metric that is generated on the fly to send it to
// Prometheus in the Collect method.
//
// quantiles maps ranks to quantile values. For example, a median latency of
// 0.23s and a 99th percentile latency of 0.56s would be expressed as:
// map[float64]float64{0.5: 0.23, 0.99: 0.56}
//
// NewConstSummary returns an error if the length of labelValues is not
// consistent with the variable labels in Desc or if Desc is invalid.
func NewConstSummary(
desc *Desc,
count uint64,
sum float64,
quantiles map[float64]float64,
labelValues ...string,
) (Metric, error) {
if desc.err != nil {
return nil, desc.err
}
if err := validateLabelValues(labelValues, len(desc.variableLabels)); err != nil {
return nil, err
}
return &constSummary{
desc: desc,
count: count,
sum: sum,
quantiles: quantiles,
labelPairs: makeLabelPairs(desc, labelValues),
}, nil
}
// MustNewConstSummary is a version of NewConstSummary that panics where
// NewConstMetric would have returned an error.
func MustNewConstSummary(
desc *Desc,
count uint64,
sum float64,
quantiles map[float64]float64,
labelValues ...string,
) Metric {
m, err := NewConstSummary(desc, count, sum, quantiles, labelValues...)
if err != nil {
panic(err)
}
return m
}