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authorKevin Lyda <kevin@ie.suberic.net>2017-02-12 14:38:12 +0000
committerNiall Sheridan <nsheridan@gmail.com>2017-02-12 14:38:12 +0000
commited8bc523fd0d1a66acf3fa449c453508035efdfc (patch)
treec05849546e1dd9d771dcc4c4ff52056d249a95fb /vendor/github.com/prometheus/client_golang/prometheus/histogram.go
parent9c344a0a95c44ef9cebade7b8a65ac160d9eb900 (diff)
Initial pass at prometheus support. (#56)
Diffstat (limited to 'vendor/github.com/prometheus/client_golang/prometheus/histogram.go')
-rw-r--r--vendor/github.com/prometheus/client_golang/prometheus/histogram.go444
1 files changed, 444 insertions, 0 deletions
diff --git a/vendor/github.com/prometheus/client_golang/prometheus/histogram.go b/vendor/github.com/prometheus/client_golang/prometheus/histogram.go
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@@ -0,0 +1,444 @@
+// Copyright 2015 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"
+ "sort"
+ "sync/atomic"
+
+ "github.com/golang/protobuf/proto"
+
+ dto "github.com/prometheus/client_model/go"
+)
+
+// A Histogram counts individual observations from an event or sample stream in
+// configurable buckets. Similar to a summary, it also provides a sum of
+// observations and an observation count.
+//
+// On the Prometheus server, quantiles can be calculated from a Histogram using
+// the histogram_quantile function in the query language.
+//
+// Note that Histograms, in contrast to Summaries, can be aggregated with the
+// Prometheus query language (see the documentation for detailed
+// procedures). However, Histograms require the user to pre-define suitable
+// buckets, and they are in general less accurate. The Observe method of a
+// Histogram has a very low performance overhead in comparison with the Observe
+// method of a Summary.
+//
+// To create Histogram instances, use NewHistogram.
+type Histogram interface {
+ Metric
+ Collector
+
+ // Observe adds a single observation to the histogram.
+ Observe(float64)
+}
+
+// bucketLabel is used for the label that defines the upper bound of a
+// bucket of a histogram ("le" -> "less or equal").
+const bucketLabel = "le"
+
+// DefBuckets are the default Histogram buckets. The default buckets are
+// tailored to broadly measure the response time (in seconds) of a network
+// service. Most likely, however, you will be required to define buckets
+// customized to your use case.
+var (
+ DefBuckets = []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10}
+
+ errBucketLabelNotAllowed = fmt.Errorf(
+ "%q is not allowed as label name in histograms", bucketLabel,
+ )
+)
+
+// LinearBuckets creates 'count' buckets, each 'width' wide, where the lowest
+// bucket has an upper bound of 'start'. The final +Inf bucket is not counted
+// and not included in the returned slice. The returned slice is meant to be
+// used for the Buckets field of HistogramOpts.
+//
+// The function panics if 'count' is zero or negative.
+func LinearBuckets(start, width float64, count int) []float64 {
+ if count < 1 {
+ panic("LinearBuckets needs a positive count")
+ }
+ buckets := make([]float64, count)
+ for i := range buckets {
+ buckets[i] = start
+ start += width
+ }
+ return buckets
+}
+
+// ExponentialBuckets creates 'count' buckets, where the lowest bucket has an
+// upper bound of 'start' and each following bucket's upper bound is 'factor'
+// times the previous bucket's upper bound. The final +Inf bucket is not counted
+// and not included in the returned slice. The returned slice is meant to be
+// used for the Buckets field of HistogramOpts.
+//
+// The function panics if 'count' is 0 or negative, if 'start' is 0 or negative,
+// or if 'factor' is less than or equal 1.
+func ExponentialBuckets(start, factor float64, count int) []float64 {
+ if count < 1 {
+ panic("ExponentialBuckets needs a positive count")
+ }
+ if start <= 0 {
+ panic("ExponentialBuckets needs a positive start value")
+ }
+ if factor <= 1 {
+ panic("ExponentialBuckets needs a factor greater than 1")
+ }
+ buckets := make([]float64, count)
+ for i := range buckets {
+ buckets[i] = start
+ start *= factor
+ }
+ return buckets
+}
+
+// HistogramOpts bundles the options for creating a Histogram metric. It is
+// mandatory to set Name and Help to a non-empty string. All other fields are
+// optional and can safely be left at their zero value.
+type HistogramOpts struct {
+ // Namespace, Subsystem, and Name are components of the fully-qualified
+ // name of the Histogram (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 Histogram must be a
+ // valid Prometheus metric name.
+ Namespace string
+ Subsystem string
+ Name string
+
+ // Help provides information about this Histogram. Mandatory!
+ //
+ // Metrics with the same fully-qualified name must have the same Help
+ // string.
+ Help string
+
+ // ConstLabels are used to attach fixed labels to this
+ // Histogram. Histograms with the same fully-qualified name must have the
+ // same label names in their ConstLabels.
+ //
+ // Note that in most cases, labels have a value that varies during the
+ // lifetime of a process. Those labels are usually managed with a
+ // HistogramVec. ConstLabels serve only special purposes. One is for the
+ // special case where the value of a label does not change during the
+ // lifetime of a process, e.g. if the revision of the running binary is
+ // put into a label. Another, more advanced purpose is if more than one
+ // Collector needs to collect Histograms with the same fully-qualified
+ // name. In that case, those Summaries must differ in the values of
+ // their ConstLabels. See the Collector examples.
+ //
+ // If the value of a label never changes (not even between binaries),
+ // that label most likely should not be a label at all (but part of the
+ // metric name).
+ ConstLabels Labels
+
+ // Buckets defines the buckets into which observations are counted. Each
+ // element in the slice is the upper inclusive bound of a bucket. The
+ // values must be sorted in strictly increasing order. There is no need
+ // to add a highest bucket with +Inf bound, it will be added
+ // implicitly. The default value is DefBuckets.
+ Buckets []float64
+}
+
+// NewHistogram creates a new Histogram based on the provided HistogramOpts. It
+// panics if the buckets in HistogramOpts are not in strictly increasing order.
+func NewHistogram(opts HistogramOpts) Histogram {
+ return newHistogram(
+ NewDesc(
+ BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
+ opts.Help,
+ nil,
+ opts.ConstLabels,
+ ),
+ opts,
+ )
+}
+
+func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogram {
+ if len(desc.variableLabels) != len(labelValues) {
+ panic(errInconsistentCardinality)
+ }
+
+ for _, n := range desc.variableLabels {
+ if n == bucketLabel {
+ panic(errBucketLabelNotAllowed)
+ }
+ }
+ for _, lp := range desc.constLabelPairs {
+ if lp.GetName() == bucketLabel {
+ panic(errBucketLabelNotAllowed)
+ }
+ }
+
+ if len(opts.Buckets) == 0 {
+ opts.Buckets = DefBuckets
+ }
+
+ h := &histogram{
+ desc: desc,
+ upperBounds: opts.Buckets,
+ labelPairs: makeLabelPairs(desc, labelValues),
+ }
+ for i, upperBound := range h.upperBounds {
+ if i < len(h.upperBounds)-1 {
+ if upperBound >= h.upperBounds[i+1] {
+ panic(fmt.Errorf(
+ "histogram buckets must be in increasing order: %f >= %f",
+ upperBound, h.upperBounds[i+1],
+ ))
+ }
+ } else {
+ if math.IsInf(upperBound, +1) {
+ // The +Inf bucket is implicit. Remove it here.
+ h.upperBounds = h.upperBounds[:i]
+ }
+ }
+ }
+ // Finally we know the final length of h.upperBounds and can make counts.
+ h.counts = make([]uint64, len(h.upperBounds))
+
+ h.init(h) // Init self-collection.
+ return h
+}
+
+type histogram 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
+
+ selfCollector
+ // Note that there is no mutex required.
+
+ desc *Desc
+
+ upperBounds []float64
+ counts []uint64
+
+ labelPairs []*dto.LabelPair
+}
+
+func (h *histogram) Desc() *Desc {
+ return h.desc
+}
+
+func (h *histogram) Observe(v float64) {
+ // TODO(beorn7): For small numbers of buckets (<30), a linear search is
+ // slightly faster than the binary search. If we really care, we could
+ // switch from one search strategy to the other depending on the number
+ // of buckets.
+ //
+ // Microbenchmarks (BenchmarkHistogramNoLabels):
+ // 11 buckets: 38.3 ns/op linear - binary 48.7 ns/op
+ // 100 buckets: 78.1 ns/op linear - binary 54.9 ns/op
+ // 300 buckets: 154 ns/op linear - binary 61.6 ns/op
+ i := sort.SearchFloat64s(h.upperBounds, v)
+ if i < len(h.counts) {
+ atomic.AddUint64(&h.counts[i], 1)
+ }
+ atomic.AddUint64(&h.count, 1)
+ for {
+ oldBits := atomic.LoadUint64(&h.sumBits)
+ newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
+ if atomic.CompareAndSwapUint64(&h.sumBits, oldBits, newBits) {
+ break
+ }
+ }
+}
+
+func (h *histogram) Write(out *dto.Metric) error {
+ his := &dto.Histogram{}
+ buckets := make([]*dto.Bucket, len(h.upperBounds))
+
+ his.SampleSum = proto.Float64(math.Float64frombits(atomic.LoadUint64(&h.sumBits)))
+ his.SampleCount = proto.Uint64(atomic.LoadUint64(&h.count))
+ var count uint64
+ for i, upperBound := range h.upperBounds {
+ count += atomic.LoadUint64(&h.counts[i])
+ buckets[i] = &dto.Bucket{
+ CumulativeCount: proto.Uint64(count),
+ UpperBound: proto.Float64(upperBound),
+ }
+ }
+ his.Bucket = buckets
+ out.Histogram = his
+ out.Label = h.labelPairs
+ return nil
+}
+
+// HistogramVec is a Collector that bundles a set of Histograms 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 NewHistogramVec.
+type HistogramVec struct {
+ *MetricVec
+}
+
+// NewHistogramVec creates a new HistogramVec based on the provided HistogramOpts and
+// partitioned by the given label names. At least one label name must be
+// provided.
+func NewHistogramVec(opts HistogramOpts, labelNames []string) *HistogramVec {
+ desc := NewDesc(
+ BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
+ opts.Help,
+ labelNames,
+ opts.ConstLabels,
+ )
+ return &HistogramVec{
+ MetricVec: newMetricVec(desc, func(lvs ...string) Metric {
+ return newHistogram(desc, opts, lvs...)
+ }),
+ }
+}
+
+// GetMetricWithLabelValues replaces the method of the same name in
+// MetricVec. The difference is that this method returns a Histogram and not a
+// Metric so that no type conversion is required.
+func (m *HistogramVec) GetMetricWithLabelValues(lvs ...string) (Histogram, error) {
+ metric, err := m.MetricVec.GetMetricWithLabelValues(lvs...)
+ if metric != nil {
+ return metric.(Histogram), err
+ }
+ return nil, err
+}
+
+// GetMetricWith replaces the method of the same name in MetricVec. The
+// difference is that this method returns a Histogram and not a Metric so that no
+// type conversion is required.
+func (m *HistogramVec) GetMetricWith(labels Labels) (Histogram, error) {
+ metric, err := m.MetricVec.GetMetricWith(labels)
+ if metric != nil {
+ return metric.(Histogram), err
+ }
+ return nil, err
+}
+
+// WithLabelValues works as GetMetricWithLabelValues, but panics where
+// GetMetricWithLabelValues would have returned an error. By not returning an
+// error, WithLabelValues allows shortcuts like
+// myVec.WithLabelValues("404", "GET").Observe(42.21)
+func (m *HistogramVec) WithLabelValues(lvs ...string) Histogram {
+ return m.MetricVec.WithLabelValues(lvs...).(Histogram)
+}
+
+// With works as GetMetricWith, but panics where GetMetricWithLabels would have
+// returned an error. By not returning an error, With allows shortcuts like
+// myVec.With(Labels{"code": "404", "method": "GET"}).Observe(42.21)
+func (m *HistogramVec) With(labels Labels) Histogram {
+ return m.MetricVec.With(labels).(Histogram)
+}
+
+type constHistogram struct {
+ desc *Desc
+ count uint64
+ sum float64
+ buckets map[float64]uint64
+ labelPairs []*dto.LabelPair
+}
+
+func (h *constHistogram) Desc() *Desc {
+ return h.desc
+}
+
+func (h *constHistogram) Write(out *dto.Metric) error {
+ his := &dto.Histogram{}
+ buckets := make([]*dto.Bucket, 0, len(h.buckets))
+
+ his.SampleCount = proto.Uint64(h.count)
+ his.SampleSum = proto.Float64(h.sum)
+
+ for upperBound, count := range h.buckets {
+ buckets = append(buckets, &dto.Bucket{
+ CumulativeCount: proto.Uint64(count),
+ UpperBound: proto.Float64(upperBound),
+ })
+ }
+
+ if len(buckets) > 0 {
+ sort.Sort(buckSort(buckets))
+ }
+ his.Bucket = buckets
+
+ out.Histogram = his
+ out.Label = h.labelPairs
+
+ return nil
+}
+
+// NewConstHistogram returns a metric representing a Prometheus histogram with
+// fixed values for the count, sum, and bucket counts. As those parameters
+// cannot be changed, the returned value does not implement the Histogram
+// 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.
+//
+// buckets is a map of upper bounds to cumulative counts, excluding the +Inf
+// bucket.
+//
+// NewConstHistogram returns an error if the length of labelValues is not
+// consistent with the variable labels in Desc.
+func NewConstHistogram(
+ desc *Desc,
+ count uint64,
+ sum float64,
+ buckets map[float64]uint64,
+ labelValues ...string,
+) (Metric, error) {
+ if len(desc.variableLabels) != len(labelValues) {
+ return nil, errInconsistentCardinality
+ }
+ return &constHistogram{
+ desc: desc,
+ count: count,
+ sum: sum,
+ buckets: buckets,
+ labelPairs: makeLabelPairs(desc, labelValues),
+ }, nil
+}
+
+// MustNewConstHistogram is a version of NewConstHistogram that panics where
+// NewConstMetric would have returned an error.
+func MustNewConstHistogram(
+ desc *Desc,
+ count uint64,
+ sum float64,
+ buckets map[float64]uint64,
+ labelValues ...string,
+) Metric {
+ m, err := NewConstHistogram(desc, count, sum, buckets, labelValues...)
+ if err != nil {
+ panic(err)
+ }
+ return m
+}
+
+type buckSort []*dto.Bucket
+
+func (s buckSort) Len() int {
+ return len(s)
+}
+
+func (s buckSort) Swap(i, j int) {
+ s[i], s[j] = s[j], s[i]
+}
+
+func (s buckSort) Less(i, j int) bool {
+ return s[i].GetUpperBound() < s[j].GetUpperBound()
+}