From ed8bc523fd0d1a66acf3fa449c453508035efdfc Mon Sep 17 00:00:00 2001 From: Kevin Lyda Date: Sun, 12 Feb 2017 14:38:12 +0000 Subject: Initial pass at prometheus support. (#56) --- .../client_golang/prometheus/histogram.go | 444 +++++++++++++++++++++ 1 file changed, 444 insertions(+) create mode 100644 vendor/github.com/prometheus/client_golang/prometheus/histogram.go (limited to 'vendor/github.com/prometheus/client_golang/prometheus/histogram.go') diff --git a/vendor/github.com/prometheus/client_golang/prometheus/histogram.go b/vendor/github.com/prometheus/client_golang/prometheus/histogram.go new file mode 100644 index 0000000..9719e8f --- /dev/null +++ b/vendor/github.com/prometheus/client_golang/prometheus/histogram.go @@ -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() +} -- cgit v1.2.3