Update metric dependencies (#5023)

This commit is contained in:
Manuel Alejandro de Brito Fontes 2020-02-06 09:50:13 -03:00 committed by GitHub
parent 4befa8cc8a
commit 9278f0cad2
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
128 changed files with 3873 additions and 2729 deletions

View file

@ -17,6 +17,7 @@ import (
"errors"
"math"
"sync/atomic"
"time"
dto "github.com/prometheus/client_model/go"
)
@ -42,11 +43,27 @@ type Counter interface {
Add(float64)
}
// ExemplarAdder is implemented by Counters that offer the option of adding a
// value to the Counter together with an exemplar. Its AddWithExemplar method
// works like the Add method of the Counter interface but also replaces the
// currently saved exemplar (if any) with a new one, created from the provided
// value, the current time as timestamp, and the provided labels. Empty Labels
// will lead to a valid (label-less) exemplar. But if Labels is nil, the current
// exemplar is left in place. AddWithExemplar panics if the value is < 0, if any
// of the provided labels are invalid, or if the provided labels contain more
// than 64 runes in total.
type ExemplarAdder interface {
AddWithExemplar(value float64, exemplar Labels)
}
// CounterOpts is an alias for Opts. See there for doc comments.
type CounterOpts Opts
// NewCounter creates a new Counter based on the provided CounterOpts.
//
// The returned implementation also implements ExemplarAdder. It is safe to
// perform the corresponding type assertion.
//
// The returned implementation tracks the counter value in two separate
// variables, a float64 and a uint64. The latter is used to track calls of the
// Inc method and calls of the Add method with a value that can be represented
@ -61,7 +78,7 @@ func NewCounter(opts CounterOpts) Counter {
nil,
opts.ConstLabels,
)
result := &counter{desc: desc, labelPairs: desc.constLabelPairs}
result := &counter{desc: desc, labelPairs: desc.constLabelPairs, now: time.Now}
result.init(result) // Init self-collection.
return result
}
@ -78,6 +95,9 @@ type counter struct {
desc *Desc
labelPairs []*dto.LabelPair
exemplar atomic.Value // Containing nil or a *dto.Exemplar.
now func() time.Time // To mock out time.Now() for testing.
}
func (c *counter) Desc() *Desc {
@ -88,6 +108,7 @@ func (c *counter) Add(v float64) {
if v < 0 {
panic(errors.New("counter cannot decrease in value"))
}
ival := uint64(v)
if float64(ival) == v {
atomic.AddUint64(&c.valInt, ival)
@ -103,6 +124,11 @@ func (c *counter) Add(v float64) {
}
}
func (c *counter) AddWithExemplar(v float64, e Labels) {
c.Add(v)
c.updateExemplar(v, e)
}
func (c *counter) Inc() {
atomic.AddUint64(&c.valInt, 1)
}
@ -112,7 +138,23 @@ func (c *counter) Write(out *dto.Metric) error {
ival := atomic.LoadUint64(&c.valInt)
val := fval + float64(ival)
return populateMetric(CounterValue, val, c.labelPairs, out)
var exemplar *dto.Exemplar
if e := c.exemplar.Load(); e != nil {
exemplar = e.(*dto.Exemplar)
}
return populateMetric(CounterValue, val, c.labelPairs, exemplar, out)
}
func (c *counter) updateExemplar(v float64, l Labels) {
if l == nil {
return
}
e, err := newExemplar(v, c.now(), l)
if err != nil {
panic(err)
}
c.exemplar.Store(e)
}
// CounterVec is a Collector that bundles a set of Counters that all share the

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@ -123,7 +123,7 @@ func (g *gauge) Sub(val float64) {
func (g *gauge) Write(out *dto.Metric) error {
val := math.Float64frombits(atomic.LoadUint64(&g.valBits))
return populateMetric(GaugeValue, val, g.labelPairs, out)
return populateMetric(GaugeValue, val, g.labelPairs, nil, out)
}
// GaugeVec is a Collector that bundles a set of Gauges that all share the same

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@ -73,7 +73,7 @@ func NewGoCollector() Collector {
nil, nil),
gcDesc: NewDesc(
"go_gc_duration_seconds",
"A summary of the GC invocation durations.",
"A summary of the pause duration of garbage collection cycles.",
nil, nil),
goInfoDesc: NewDesc(
"go_info",

View file

@ -20,6 +20,7 @@ import (
"sort"
"sync"
"sync/atomic"
"time"
"github.com/golang/protobuf/proto"
@ -151,6 +152,10 @@ type HistogramOpts struct {
// NewHistogram creates a new Histogram based on the provided HistogramOpts. It
// panics if the buckets in HistogramOpts are not in strictly increasing order.
//
// The returned implementation also implements ExemplarObserver. It is safe to
// perform the corresponding type assertion. Exemplars are tracked separately
// for each bucket.
func NewHistogram(opts HistogramOpts) Histogram {
return newHistogram(
NewDesc(
@ -188,6 +193,7 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
upperBounds: opts.Buckets,
labelPairs: makeLabelPairs(desc, labelValues),
counts: [2]*histogramCounts{{}, {}},
now: time.Now,
}
for i, upperBound := range h.upperBounds {
if i < len(h.upperBounds)-1 {
@ -205,9 +211,10 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
}
}
// Finally we know the final length of h.upperBounds and can make buckets
// for both counts:
// for both counts as well as exemplars:
h.counts[0].buckets = make([]uint64, len(h.upperBounds))
h.counts[1].buckets = make([]uint64, len(h.upperBounds))
h.exemplars = make([]atomic.Value, len(h.upperBounds)+1)
h.init(h) // Init self-collection.
return h
@ -254,6 +261,9 @@ type histogram struct {
upperBounds []float64
labelPairs []*dto.LabelPair
exemplars []atomic.Value // One more than buckets (to include +Inf), each a *dto.Exemplar.
now func() time.Time // To mock out time.Now() for testing.
}
func (h *histogram) Desc() *Desc {
@ -261,36 +271,13 @@ func (h *histogram) Desc() *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)
h.observe(v, h.findBucket(v))
}
// 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(&h.countAndHotIdx, 1)
hotCounts := h.counts[n>>63]
if i < len(h.upperBounds) {
atomic.AddUint64(&hotCounts.buckets[i], 1)
}
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 (h *histogram) ObserveWithExemplar(v float64, e Labels) {
i := h.findBucket(v)
h.observe(v, i)
h.updateExemplar(v, i, e)
}
func (h *histogram) Write(out *dto.Metric) error {
@ -329,6 +316,18 @@ func (h *histogram) Write(out *dto.Metric) error {
CumulativeCount: proto.Uint64(cumCount),
UpperBound: proto.Float64(upperBound),
}
if e := h.exemplars[i].Load(); e != nil {
his.Bucket[i].Exemplar = e.(*dto.Exemplar)
}
}
// If there is an exemplar for the +Inf bucket, we have to add that bucket explicitly.
if e := h.exemplars[len(h.upperBounds)].Load(); e != nil {
b := &dto.Bucket{
CumulativeCount: proto.Uint64(count),
UpperBound: proto.Float64(math.Inf(1)),
Exemplar: e.(*dto.Exemplar),
}
his.Bucket = append(his.Bucket, b)
}
out.Histogram = his
@ -352,6 +351,57 @@ func (h *histogram) Write(out *dto.Metric) error {
return nil
}
// findBucket returns the index of the bucket for the provided value, or
// len(h.upperBounds) for the +Inf bucket.
func (h *histogram) findBucket(v float64) int {
// 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
return sort.SearchFloat64s(h.upperBounds, v)
}
// observe is the implementation for Observe without the findBucket part.
func (h *histogram) observe(v float64, bucket int) {
// 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(&h.countAndHotIdx, 1)
hotCounts := h.counts[n>>63]
if bucket < len(h.upperBounds) {
atomic.AddUint64(&hotCounts.buckets[bucket], 1)
}
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)
}
// updateExemplar replaces the exemplar for the provided bucket. With empty
// labels, it's a no-op. It panics if any of the labels is invalid.
func (h *histogram) updateExemplar(v float64, bucket int, l Labels) {
if l == nil {
return
}
e, err := newExemplar(v, h.now(), l)
if err != nil {
panic(err)
}
h.exemplars[bucket].Store(e)
}
// 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

View file

@ -50,3 +50,15 @@ type ObserverVec interface {
Collector
}
// ExemplarObserver is implemented by Observers that offer the option of
// observing a value together with an exemplar. Its ObserveWithExemplar method
// works like the Observe method of an Observer but also replaces the currently
// saved exemplar (if any) with a new one, created from the provided value, the
// current time as timestamp, and the provided Labels. Empty Labels will lead to
// a valid (label-less) exemplar. But if Labels is nil, the current exemplar is
// left in place. ObserveWithExemplar panics if any of the provided labels are
// invalid or if the provided labels contain more than 64 runes in total.
type ExemplarObserver interface {
ObserveWithExemplar(value float64, exemplar Labels)
}

View file

@ -144,7 +144,12 @@ func HandlerFor(reg prometheus.Gatherer, opts HandlerOpts) http.Handler {
}
}
contentType := expfmt.Negotiate(req.Header)
var contentType expfmt.Format
if opts.EnableOpenMetrics {
contentType = expfmt.NegotiateIncludingOpenMetrics(req.Header)
} else {
contentType = expfmt.Negotiate(req.Header)
}
header := rsp.Header()
header.Set(contentTypeHeader, string(contentType))
@ -163,22 +168,38 @@ func HandlerFor(reg prometheus.Gatherer, opts HandlerOpts) http.Handler {
enc := expfmt.NewEncoder(w, contentType)
var lastErr error
// handleError handles the error according to opts.ErrorHandling
// and returns true if we have to abort after the handling.
handleError := func(err error) bool {
if err == nil {
return false
}
lastErr = err
if opts.ErrorLog != nil {
opts.ErrorLog.Println("error encoding and sending metric family:", err)
}
errCnt.WithLabelValues("encoding").Inc()
switch opts.ErrorHandling {
case PanicOnError:
panic(err)
case HTTPErrorOnError:
httpError(rsp, err)
return true
}
// Do nothing in all other cases, including ContinueOnError.
return false
}
for _, mf := range mfs {
if err := enc.Encode(mf); err != nil {
lastErr = err
if opts.ErrorLog != nil {
opts.ErrorLog.Println("error encoding and sending metric family:", err)
}
errCnt.WithLabelValues("encoding").Inc()
switch opts.ErrorHandling {
case PanicOnError:
panic(err)
case ContinueOnError:
// Handled later.
case HTTPErrorOnError:
httpError(rsp, err)
return
}
if handleError(enc.Encode(mf)) {
return
}
}
if closer, ok := enc.(expfmt.Closer); ok {
// This in particular takes care of the final "# EOF\n" line for OpenMetrics.
if handleError(closer.Close()) {
return
}
}
@ -318,6 +339,16 @@ type HandlerOpts struct {
// away). Until the implementation is improved, it is recommended to
// implement a separate timeout in potentially slow Collectors.
Timeout time.Duration
// If true, the experimental OpenMetrics encoding is added to the
// possible options during content negotiation. Note that Prometheus
// 2.5.0+ will negotiate OpenMetrics as first priority. OpenMetrics is
// the only way to transmit exemplars. However, the move to OpenMetrics
// is not completely transparent. Most notably, the values of "quantile"
// labels of Summaries and "le" labels of Histograms are formatted with
// a trailing ".0" if they would otherwise look like integer numbers
// (which changes the identity of the resulting series on the Prometheus
// server).
EnableOpenMetrics bool
}
// gzipAccepted returns whether the client will accept gzip-encoded content.

View file

@ -16,8 +16,11 @@ package prometheus
import (
"fmt"
"sort"
"time"
"unicode/utf8"
"github.com/golang/protobuf/proto"
"github.com/golang/protobuf/ptypes"
dto "github.com/prometheus/client_model/go"
)
@ -69,7 +72,7 @@ func (v *valueFunc) Desc() *Desc {
}
func (v *valueFunc) Write(out *dto.Metric) error {
return populateMetric(v.valType, v.function(), v.labelPairs, out)
return populateMetric(v.valType, v.function(), v.labelPairs, nil, out)
}
// NewConstMetric returns a metric with one fixed value that cannot be
@ -116,19 +119,20 @@ func (m *constMetric) Desc() *Desc {
}
func (m *constMetric) Write(out *dto.Metric) error {
return populateMetric(m.valType, m.val, m.labelPairs, out)
return populateMetric(m.valType, m.val, m.labelPairs, nil, out)
}
func populateMetric(
t ValueType,
v float64,
labelPairs []*dto.LabelPair,
e *dto.Exemplar,
m *dto.Metric,
) error {
m.Label = labelPairs
switch t {
case CounterValue:
m.Counter = &dto.Counter{Value: proto.Float64(v)}
m.Counter = &dto.Counter{Value: proto.Float64(v), Exemplar: e}
case GaugeValue:
m.Gauge = &dto.Gauge{Value: proto.Float64(v)}
case UntypedValue:
@ -160,3 +164,40 @@ func makeLabelPairs(desc *Desc, labelValues []string) []*dto.LabelPair {
sort.Sort(labelPairSorter(labelPairs))
return labelPairs
}
// ExemplarMaxRunes is the max total number of runes allowed in exemplar labels.
const ExemplarMaxRunes = 64
// newExemplar creates a new dto.Exemplar from the provided values. An error is
// returned if any of the label names or values are invalid or if the total
// number of runes in the label names and values exceeds ExemplarMaxRunes.
func newExemplar(value float64, ts time.Time, l Labels) (*dto.Exemplar, error) {
e := &dto.Exemplar{}
e.Value = proto.Float64(value)
tsProto, err := ptypes.TimestampProto(ts)
if err != nil {
return nil, err
}
e.Timestamp = tsProto
labelPairs := make([]*dto.LabelPair, 0, len(l))
var runes int
for name, value := range l {
if !checkLabelName(name) {
return nil, fmt.Errorf("exemplar label name %q is invalid", name)
}
runes += utf8.RuneCountInString(name)
if !utf8.ValidString(value) {
return nil, fmt.Errorf("exemplar label value %q is not valid UTF-8", value)
}
runes += utf8.RuneCountInString(value)
labelPairs = append(labelPairs, &dto.LabelPair{
Name: proto.String(name),
Value: proto.String(value),
})
}
if runes > ExemplarMaxRunes {
return nil, fmt.Errorf("exemplar labels have %d runes, exceeding the limit of %d", runes, ExemplarMaxRunes)
}
e.Label = labelPairs
return e, nil
}