606 lines
20 KiB
Go
606 lines
20 KiB
Go
// Copyright 2021 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//go:build go1.17
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// +build go1.17
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package prometheus
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import (
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"math"
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"runtime"
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"runtime/metrics"
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"strings"
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"sync"
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"github.com/prometheus/client_golang/prometheus/internal"
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dto "github.com/prometheus/client_model/go"
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"google.golang.org/protobuf/proto"
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)
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const (
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// constants for strings referenced more than once.
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goGCGogcPercent = "/gc/gogc:percent"
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goGCHeapTinyAllocsObjects = "/gc/heap/tiny/allocs:objects"
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goGCHeapAllocsObjects = "/gc/heap/allocs:objects"
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goGCHeapFreesObjects = "/gc/heap/frees:objects"
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goGCHeapFreesBytes = "/gc/heap/frees:bytes"
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goGCHeapAllocsBytes = "/gc/heap/allocs:bytes"
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goGCHeapObjects = "/gc/heap/objects:objects"
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goGCHeapGoalBytes = "/gc/heap/goal:bytes"
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goGCMemLimit = "/gc/gomemlimit:bytes"
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goMemoryClassesTotalBytes = "/memory/classes/total:bytes"
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goMemoryClassesHeapObjectsBytes = "/memory/classes/heap/objects:bytes"
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goMemoryClassesHeapUnusedBytes = "/memory/classes/heap/unused:bytes"
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goMemoryClassesHeapReleasedBytes = "/memory/classes/heap/released:bytes"
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goMemoryClassesHeapFreeBytes = "/memory/classes/heap/free:bytes"
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goMemoryClassesHeapStacksBytes = "/memory/classes/heap/stacks:bytes"
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goMemoryClassesOSStacksBytes = "/memory/classes/os-stacks:bytes"
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goMemoryClassesMetadataMSpanInuseBytes = "/memory/classes/metadata/mspan/inuse:bytes"
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goMemoryClassesMetadataMSPanFreeBytes = "/memory/classes/metadata/mspan/free:bytes"
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goMemoryClassesMetadataMCacheInuseBytes = "/memory/classes/metadata/mcache/inuse:bytes"
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goMemoryClassesMetadataMCacheFreeBytes = "/memory/classes/metadata/mcache/free:bytes"
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goMemoryClassesProfilingBucketsBytes = "/memory/classes/profiling/buckets:bytes"
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goMemoryClassesMetadataOtherBytes = "/memory/classes/metadata/other:bytes"
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goMemoryClassesOtherBytes = "/memory/classes/other:bytes"
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goSchedMaxProcs = "/sched/gomaxprocs:threads"
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)
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// rmNamesForMemStatsMetrics represents runtime/metrics names required to populate goRuntimeMemStats from like logic.
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var rmNamesForMemStatsMetrics = []string{
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goGCHeapTinyAllocsObjects,
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goGCHeapAllocsObjects,
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goGCHeapFreesObjects,
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goGCHeapAllocsBytes,
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goGCHeapObjects,
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goGCHeapGoalBytes,
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goMemoryClassesTotalBytes,
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goMemoryClassesHeapObjectsBytes,
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goMemoryClassesHeapUnusedBytes,
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goMemoryClassesHeapReleasedBytes,
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goMemoryClassesHeapFreeBytes,
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goMemoryClassesHeapStacksBytes,
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goMemoryClassesOSStacksBytes,
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goMemoryClassesMetadataMSpanInuseBytes,
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goMemoryClassesMetadataMSPanFreeBytes,
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goMemoryClassesMetadataMCacheInuseBytes,
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goMemoryClassesMetadataMCacheFreeBytes,
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goMemoryClassesProfilingBucketsBytes,
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goMemoryClassesMetadataOtherBytes,
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goMemoryClassesOtherBytes,
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}
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var rmNamesForEnvVarsMetrics = []string{ // how to name this var???
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goGCGogcPercent,
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goGCMemLimit,
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goSchedMaxProcs,
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}
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func bestEffortLookupRM(lookup []string) []metrics.Description {
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ret := make([]metrics.Description, 0, len(lookup))
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for _, rm := range metrics.All() {
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for _, m := range lookup {
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if m == rm.Name {
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ret = append(ret, rm)
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}
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}
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}
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return ret
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}
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type goCollector struct {
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base baseGoCollector
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// mu protects updates to all fields ensuring a consistent
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// snapshot is always produced by Collect.
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mu sync.Mutex
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// Contains all samples that has to retrieved from runtime/metrics (not all of them will be exposed).
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sampleBuf []metrics.Sample
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// sampleMap allows lookup for MemStats metrics and runtime/metrics histograms for exact sums.
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sampleMap map[string]*metrics.Sample
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// rmExposedMetrics represents all runtime/metrics package metrics
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// that were configured to be exposed.
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rmExposedMetrics []collectorMetric
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rmExactSumMapForHist map[string]string
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// With Go 1.17, the runtime/metrics package was introduced.
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// From that point on, metric names produced by the runtime/metrics
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// package could be generated from runtime/metrics names. However,
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// these differ from the old names for the same values.
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//
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// This field exists to export the same values under the old names
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// as well.
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msMetrics memStatsMetrics
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msMetricsEnabled bool
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rmEnvVarsMetrics runtimeEnvVarsMetrics // how to call them???
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rmEnvVarsMetricsEnabled bool
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}
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type rmMetricDesc struct {
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metrics.Description
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}
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func matchRuntimeMetricsRules(rules []internal.GoCollectorRule) []rmMetricDesc {
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var descs []rmMetricDesc
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for _, d := range metrics.All() {
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var (
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deny = true
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desc rmMetricDesc
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)
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for _, r := range rules {
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if !r.Matcher.MatchString(d.Name) {
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continue
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}
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deny = r.Deny
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}
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if deny {
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continue
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}
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desc.Description = d
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descs = append(descs, desc)
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}
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return descs
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}
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func defaultGoCollectorOptions() internal.GoCollectorOptions {
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return internal.GoCollectorOptions{
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RuntimeMetricSumForHist: map[string]string{
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"/gc/heap/allocs-by-size:bytes": goGCHeapAllocsBytes,
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"/gc/heap/frees-by-size:bytes": goGCHeapFreesBytes,
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},
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RuntimeMetricRules: []internal.GoCollectorRule{
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//{Matcher: regexp.MustCompile("")},
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},
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}
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}
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// NewGoCollector is the obsolete version of collectors.NewGoCollector.
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// See there for documentation.
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//
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// Deprecated: Use collectors.NewGoCollector instead.
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func NewGoCollector(opts ...func(o *internal.GoCollectorOptions)) Collector {
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opt := defaultGoCollectorOptions()
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for _, o := range opts {
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o(&opt)
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}
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exposedDescriptions := matchRuntimeMetricsRules(opt.RuntimeMetricRules)
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// Collect all histogram samples so that we can get their buckets.
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// The API guarantees that the buckets are always fixed for the lifetime
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// of the process.
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var histograms []metrics.Sample
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for _, d := range exposedDescriptions {
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if d.Kind == metrics.KindFloat64Histogram {
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histograms = append(histograms, metrics.Sample{Name: d.Name})
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}
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}
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if len(histograms) > 0 {
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metrics.Read(histograms)
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}
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bucketsMap := make(map[string][]float64)
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for i := range histograms {
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bucketsMap[histograms[i].Name] = histograms[i].Value.Float64Histogram().Buckets
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}
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// Generate a collector for each exposed runtime/metrics metric.
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metricSet := make([]collectorMetric, 0, len(exposedDescriptions))
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// SampleBuf is used for reading from runtime/metrics.
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// We are assuming the largest case to have stable pointers for sampleMap purposes.
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sampleBuf := make([]metrics.Sample, 0, len(exposedDescriptions)+len(opt.RuntimeMetricSumForHist)+len(rmNamesForMemStatsMetrics)+len(rmNamesForEnvVarsMetrics))
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sampleMap := make(map[string]*metrics.Sample, len(exposedDescriptions))
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for _, d := range exposedDescriptions {
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namespace, subsystem, name, ok := internal.RuntimeMetricsToProm(&d.Description)
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if !ok {
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// Just ignore this metric; we can't do anything with it here.
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// If a user decides to use the latest version of Go, we don't want
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// to fail here. This condition is tested in TestExpectedRuntimeMetrics.
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continue
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}
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sampleBuf = append(sampleBuf, metrics.Sample{Name: d.Name})
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sampleMap[d.Name] = &sampleBuf[len(sampleBuf)-1]
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var m collectorMetric
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if d.Kind == metrics.KindFloat64Histogram {
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_, hasSum := opt.RuntimeMetricSumForHist[d.Name]
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unit := d.Name[strings.IndexRune(d.Name, ':')+1:]
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m = newBatchHistogram(
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NewDesc(
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BuildFQName(namespace, subsystem, name),
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d.Description.Description,
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nil,
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nil,
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),
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internal.RuntimeMetricsBucketsForUnit(bucketsMap[d.Name], unit),
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hasSum,
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)
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} else if d.Cumulative {
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m = NewCounter(CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: name,
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Help: d.Description.Description,
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},
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)
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} else {
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m = NewGauge(GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: name,
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Help: d.Description.Description,
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})
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}
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metricSet = append(metricSet, m)
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}
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// Add exact sum metrics to sampleBuf if not added before.
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for _, h := range histograms {
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sumMetric, ok := opt.RuntimeMetricSumForHist[h.Name]
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if !ok {
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continue
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}
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if _, ok := sampleMap[sumMetric]; ok {
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continue
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}
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sampleBuf = append(sampleBuf, metrics.Sample{Name: sumMetric})
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sampleMap[sumMetric] = &sampleBuf[len(sampleBuf)-1]
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}
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var (
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msMetrics memStatsMetrics
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msDescriptions []metrics.Description
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rmEnvVarsMetrics runtimeEnvVarsMetrics
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rmEnvVarsDescriptions []metrics.Description
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)
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if !opt.DisableMemStatsLikeMetrics {
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msMetrics = goRuntimeMemStats()
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msDescriptions = bestEffortLookupRM(rmNamesForMemStatsMetrics)
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// Check if metric was not exposed before and if not, add to sampleBuf.
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for _, mdDesc := range msDescriptions {
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if _, ok := sampleMap[mdDesc.Name]; ok {
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continue
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}
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sampleBuf = append(sampleBuf, metrics.Sample{Name: mdDesc.Name})
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sampleMap[mdDesc.Name] = &sampleBuf[len(sampleBuf)-1]
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}
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}
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if !opt.DisableRuntimeEnvVarsMetrics {
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rmEnvVarsMetrics = goRuntimeEnvVarsMetrics()
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rmEnvVarsDescriptions = bestEffortLookupRM(rmNamesForEnvVarsMetrics)
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// Check if metric was not exposed before and if not, add to sampleBuf.
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for _, rnevDesc := range rmEnvVarsDescriptions {
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if _, ok := sampleMap[rnevDesc.Name]; ok {
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continue
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}
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sampleBuf = append(sampleBuf, metrics.Sample{Name: rnevDesc.Name})
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sampleMap[rnevDesc.Name] = &sampleBuf[len(sampleBuf)-1]
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}
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}
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return &goCollector{
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base: newBaseGoCollector(),
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sampleBuf: sampleBuf,
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sampleMap: sampleMap,
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rmExposedMetrics: metricSet,
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rmExactSumMapForHist: opt.RuntimeMetricSumForHist,
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msMetrics: msMetrics,
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msMetricsEnabled: !opt.DisableMemStatsLikeMetrics,
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rmEnvVarsMetrics: rmEnvVarsMetrics,
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rmEnvVarsMetricsEnabled: !opt.DisableRuntimeEnvVarsMetrics,
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}
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}
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// Describe returns all descriptions of the collector.
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func (c *goCollector) Describe(ch chan<- *Desc) {
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c.base.Describe(ch)
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for _, i := range c.msMetrics {
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ch <- i.desc
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}
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for _, m := range c.rmExposedMetrics {
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ch <- m.Desc()
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}
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}
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// Collect returns the current state of all metrics of the collector.
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func (c *goCollector) Collect(ch chan<- Metric) {
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// Collect base non-memory metrics.
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c.base.Collect(ch)
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if len(c.sampleBuf) == 0 {
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return
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}
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// Collect must be thread-safe, so prevent concurrent use of
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// sampleBuf elements. Just read into sampleBuf but write all the data
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// we get into our Metrics or MemStats.
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//
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// This lock also ensures that the Metrics we send out are all from
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// the same updates, ensuring their mutual consistency insofar as
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// is guaranteed by the runtime/metrics package.
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//
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// N.B. This locking is heavy-handed, but Collect is expected to be called
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// relatively infrequently. Also the core operation here, metrics.Read,
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// is fast (O(tens of microseconds)) so contention should certainly be
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// low, though channel operations and any allocations may add to that.
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c.mu.Lock()
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defer c.mu.Unlock()
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// Populate runtime/metrics sample buffer.
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metrics.Read(c.sampleBuf)
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// Collect all our runtime/metrics user chose to expose from sampleBuf (if any).
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for i, metric := range c.rmExposedMetrics {
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// We created samples for exposed metrics first in order, so indexes match.
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sample := c.sampleBuf[i]
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// N.B. switch on concrete type because it's significantly more efficient
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// than checking for the Counter and Gauge interface implementations. In
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// this case, we control all the types here.
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switch m := metric.(type) {
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case *counter:
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// Guard against decreases. This should never happen, but a failure
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// to do so will result in a panic, which is a harsh consequence for
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// a metrics collection bug.
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v0, v1 := m.get(), unwrapScalarRMValue(sample.Value)
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if v1 > v0 {
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m.Add(unwrapScalarRMValue(sample.Value) - m.get())
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}
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m.Collect(ch)
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case *gauge:
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m.Set(unwrapScalarRMValue(sample.Value))
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m.Collect(ch)
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case *batchHistogram:
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m.update(sample.Value.Float64Histogram(), c.exactSumFor(sample.Name))
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m.Collect(ch)
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default:
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panic("unexpected metric type")
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}
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}
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if c.msMetricsEnabled {
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// ms is a dummy MemStats that we populate ourselves so that we can
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// populate the old metrics from it if goMemStatsCollection is enabled.
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var ms runtime.MemStats
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memStatsFromRM(&ms, c.sampleMap)
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for _, i := range c.msMetrics {
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ch <- MustNewConstMetric(i.desc, i.valType, i.eval(&ms))
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}
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}
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if c.rmEnvVarsMetricsEnabled {
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sampleBuf := make([]metrics.Sample, len(c.rmEnvVarsMetrics))
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for i, v := range c.rmEnvVarsMetrics {
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sampleBuf[i].Name = v.origMetricName
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metrics.Read(sampleBuf)
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ch <- MustNewConstMetric(v.desc, GaugeValue, unwrapScalarRMValue(sampleBuf[i].Value))
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}
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}
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}
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// unwrapScalarRMValue unwraps a runtime/metrics value that is assumed
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// to be scalar and returns the equivalent float64 value. Panics if the
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// value is not scalar.
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func unwrapScalarRMValue(v metrics.Value) float64 {
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switch v.Kind() {
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case metrics.KindUint64:
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return float64(v.Uint64())
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case metrics.KindFloat64:
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return v.Float64()
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case metrics.KindBad:
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// Unsupported metric.
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//
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// This should never happen because we always populate our metric
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// set from the runtime/metrics package.
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panic("unexpected unsupported metric")
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default:
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// Unsupported metric kind.
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//
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// This should never happen because we check for this during initialization
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// and flag and filter metrics whose kinds we don't understand.
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panic("unexpected unsupported metric kind")
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}
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}
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// exactSumFor takes a runtime/metrics metric name (that is assumed to
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// be of kind KindFloat64Histogram) and returns its exact sum and whether
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// its exact sum exists.
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//
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// The runtime/metrics API for histograms doesn't currently expose exact
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// sums, but some of the other metrics are in fact exact sums of histograms.
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func (c *goCollector) exactSumFor(rmName string) float64 {
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sumName, ok := c.rmExactSumMapForHist[rmName]
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if !ok {
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return 0
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}
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s, ok := c.sampleMap[sumName]
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if !ok {
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return 0
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}
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return unwrapScalarRMValue(s.Value)
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}
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func memStatsFromRM(ms *runtime.MemStats, rm map[string]*metrics.Sample) {
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lookupOrZero := func(name string) uint64 {
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if s, ok := rm[name]; ok {
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return s.Value.Uint64()
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}
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return 0
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}
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// Currently, MemStats adds tiny alloc count to both Mallocs AND Frees.
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// The reason for this is because MemStats couldn't be extended at the time
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// but there was a desire to have Mallocs at least be a little more representative,
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// while having Mallocs - Frees still represent a live object count.
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// Unfortunately, MemStats doesn't actually export a large allocation count,
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// so it's impossible to pull this number out directly.
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tinyAllocs := lookupOrZero(goGCHeapTinyAllocsObjects)
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ms.Mallocs = lookupOrZero(goGCHeapAllocsObjects) + tinyAllocs
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ms.Frees = lookupOrZero(goGCHeapFreesObjects) + tinyAllocs
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ms.TotalAlloc = lookupOrZero(goGCHeapAllocsBytes)
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ms.Sys = lookupOrZero(goMemoryClassesTotalBytes)
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ms.Lookups = 0 // Already always zero.
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ms.HeapAlloc = lookupOrZero(goMemoryClassesHeapObjectsBytes)
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ms.Alloc = ms.HeapAlloc
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ms.HeapInuse = ms.HeapAlloc + lookupOrZero(goMemoryClassesHeapUnusedBytes)
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ms.HeapReleased = lookupOrZero(goMemoryClassesHeapReleasedBytes)
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ms.HeapIdle = ms.HeapReleased + lookupOrZero(goMemoryClassesHeapFreeBytes)
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ms.HeapSys = ms.HeapInuse + ms.HeapIdle
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ms.HeapObjects = lookupOrZero(goGCHeapObjects)
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ms.StackInuse = lookupOrZero(goMemoryClassesHeapStacksBytes)
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ms.StackSys = ms.StackInuse + lookupOrZero(goMemoryClassesOSStacksBytes)
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ms.MSpanInuse = lookupOrZero(goMemoryClassesMetadataMSpanInuseBytes)
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ms.MSpanSys = ms.MSpanInuse + lookupOrZero(goMemoryClassesMetadataMSPanFreeBytes)
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ms.MCacheInuse = lookupOrZero(goMemoryClassesMetadataMCacheInuseBytes)
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ms.MCacheSys = ms.MCacheInuse + lookupOrZero(goMemoryClassesMetadataMCacheFreeBytes)
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ms.BuckHashSys = lookupOrZero(goMemoryClassesProfilingBucketsBytes)
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ms.GCSys = lookupOrZero(goMemoryClassesMetadataOtherBytes)
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ms.OtherSys = lookupOrZero(goMemoryClassesOtherBytes)
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ms.NextGC = lookupOrZero(goGCHeapGoalBytes)
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// N.B. GCCPUFraction is intentionally omitted. This metric is not useful,
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// and often misleading due to the fact that it's an average over the lifetime
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// of the process.
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// See https://github.com/prometheus/client_golang/issues/842#issuecomment-861812034
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// for more details.
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ms.GCCPUFraction = 0
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}
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|
|
|
// batchHistogram is a mutable histogram that is updated
|
|
// in batches.
|
|
type batchHistogram struct {
|
|
selfCollector
|
|
|
|
// Static fields updated only once.
|
|
desc *Desc
|
|
hasSum bool
|
|
|
|
// Because this histogram operates in batches, it just uses a
|
|
// single mutex for everything. updates are always serialized
|
|
// but Write calls may operate concurrently with updates.
|
|
// Contention between these two sources should be rare.
|
|
mu sync.Mutex
|
|
buckets []float64 // Inclusive lower bounds, like runtime/metrics.
|
|
counts []uint64
|
|
sum float64 // Used if hasSum is true.
|
|
}
|
|
|
|
// newBatchHistogram creates a new batch histogram value with the given
|
|
// Desc, buckets, and whether or not it has an exact sum available.
|
|
//
|
|
// buckets must always be from the runtime/metrics package, following
|
|
// the same conventions.
|
|
func newBatchHistogram(desc *Desc, buckets []float64, hasSum bool) *batchHistogram {
|
|
// We need to remove -Inf values. runtime/metrics keeps them around.
|
|
// But -Inf bucket should not be allowed for prometheus histograms.
|
|
if buckets[0] == math.Inf(-1) {
|
|
buckets = buckets[1:]
|
|
}
|
|
h := &batchHistogram{
|
|
desc: desc,
|
|
buckets: buckets,
|
|
// Because buckets follows runtime/metrics conventions, there's
|
|
// 1 more value in the buckets list than there are buckets represented,
|
|
// because in runtime/metrics, the bucket values represent *boundaries*,
|
|
// and non-Inf boundaries are inclusive lower bounds for that bucket.
|
|
counts: make([]uint64, len(buckets)-1),
|
|
hasSum: hasSum,
|
|
}
|
|
h.init(h)
|
|
return h
|
|
}
|
|
|
|
// update updates the batchHistogram from a runtime/metrics histogram.
|
|
//
|
|
// sum must be provided if the batchHistogram was created to have an exact sum.
|
|
// h.buckets must be a strict subset of his.Buckets.
|
|
func (h *batchHistogram) update(his *metrics.Float64Histogram, sum float64) {
|
|
counts, buckets := his.Counts, his.Buckets
|
|
|
|
h.mu.Lock()
|
|
defer h.mu.Unlock()
|
|
|
|
// Clear buckets.
|
|
for i := range h.counts {
|
|
h.counts[i] = 0
|
|
}
|
|
// Copy and reduce buckets.
|
|
var j int
|
|
for i, count := range counts {
|
|
h.counts[j] += count
|
|
if buckets[i+1] == h.buckets[j+1] {
|
|
j++
|
|
}
|
|
}
|
|
if h.hasSum {
|
|
h.sum = sum
|
|
}
|
|
}
|
|
|
|
func (h *batchHistogram) Desc() *Desc {
|
|
return h.desc
|
|
}
|
|
|
|
func (h *batchHistogram) Write(out *dto.Metric) error {
|
|
h.mu.Lock()
|
|
defer h.mu.Unlock()
|
|
|
|
sum := float64(0)
|
|
if h.hasSum {
|
|
sum = h.sum
|
|
}
|
|
dtoBuckets := make([]*dto.Bucket, 0, len(h.counts))
|
|
totalCount := uint64(0)
|
|
for i, count := range h.counts {
|
|
totalCount += count
|
|
if !h.hasSum {
|
|
if count != 0 {
|
|
// N.B. This computed sum is an underestimate.
|
|
sum += h.buckets[i] * float64(count)
|
|
}
|
|
}
|
|
|
|
// Skip the +Inf bucket, but only for the bucket list.
|
|
// It must still count for sum and totalCount.
|
|
if math.IsInf(h.buckets[i+1], 1) {
|
|
break
|
|
}
|
|
// Float64Histogram's upper bound is exclusive, so make it inclusive
|
|
// by obtaining the next float64 value down, in order.
|
|
upperBound := math.Nextafter(h.buckets[i+1], h.buckets[i])
|
|
dtoBuckets = append(dtoBuckets, &dto.Bucket{
|
|
CumulativeCount: proto.Uint64(totalCount),
|
|
UpperBound: proto.Float64(upperBound),
|
|
})
|
|
}
|
|
out.Histogram = &dto.Histogram{
|
|
Bucket: dtoBuckets,
|
|
SampleCount: proto.Uint64(totalCount),
|
|
SampleSum: proto.Float64(sum),
|
|
}
|
|
return nil
|
|
}
|