metrics

原文：https://pkg.go.dev/runtime/metrics@go1.23.0

Package metrics provides a stable interface to access implementation-defined metrics exported by the Go runtime. This package is similar to existing functions like runtime.ReadMemStats and debug.ReadGCStats, but significantly more general.

​ metrics 包提供了一个稳定的接口，用于访问 Go 运行时导出的实现定义的指标。此软件包类似于现有的函数，如 runtime.ReadMemStats 和 debug.ReadGCStats，但更具通用性。

The set of metrics defined by this package may evolve as the runtime itself evolves, and also enables variation across Go implementations, whose relevant metric sets may not intersect.

​ 此包定义的指标集可能会随着运行时本身的演变而演变，并且还支持跨 Go 实现的变化，其相关的指标集可能不会相交。

Interface 接口

Metrics are designated by a string key, rather than, for example, a field name in a struct. The full list of supported metrics is always available in the slice of Descriptions returned by All. Each Description also includes useful information about the metric.

​ 指标由字符串键指定，而不是结构中的字段名。支持的指标的完整列表始终在 All 返回的 Descriptions 片段中可用。每个 Description 还包括有关指标的有用信息。

Thus, users of this API are encouraged to sample supported metrics defined by the slice returned by All to remain compatible across Go versions. Of course, situations arise where reading specific metrics is critical. For these cases, users are encouraged to use build tags, and although metrics may be deprecated and removed, users should consider this to be an exceptional and rare event, coinciding with a very large change in a particular Go implementation.

​ 因此，鼓励此 API 的用户对 All 返回的片段定义的支持的指标进行采样，以保持跨 Go 版本的兼容性。当然，会出现读取特定指标至关重要的的情况。对于这些情况，鼓励用户使用构建标记，并且尽管指标可能会被弃用并删除，但用户应认为这是一个例外且罕见的事件，与特定 Go 实现中的非常大的更改相吻合。

Each metric key also has a “kind” that describes the format of the metric’s value. In the interest of not breaking users of this package, the “kind” for a given metric is guaranteed not to change. If it must change, then a new metric will be introduced with a new key and a new “kind.”

​ 每个指标键还具有一个“类型”，用于描述指标值的格式。为了不破坏此软件包的用户，保证给定指标的“类型”不会更改。如果必须更改，则将引入一个具有新键和新“类型”的新指标。

Metric key format 指标键格式

As mentioned earlier, metric keys are strings. Their format is simple and well-defined, designed to be both human and machine readable. It is split into two components, separated by a colon: a rooted path and a unit. The choice to include the unit in the key is motivated by compatibility: if a metric’s unit changes, its semantics likely did also, and a new key should be introduced.

​ 如前所述，指标键是字符串。它们的格式简单且定义明确，旨在便于人类和机器读取。它分为两个部分，用冒号分隔：根路径和单位。在键中包含单位的选择是出于兼容性的考虑：如果指标的单位发生变化，则其语义也可能发生变化，并且应该引入一个新键。

For more details on the precise definition of the metric key’s path and unit formats, see the documentation of the Name field of the Description struct.

​ 有关指标键的路径和单位格式的精确定义的更多详细信息，请参阅 Description 结构的 Name 字段的文档。

A note about floats 关于浮点数的说明

This package supports metrics whose values have a floating-point representation. In order to improve ease-of-use, this package promises to never produce the following classes of floating-point values: NaN, infinity.

​ 此软件包支持值具有浮点表示形式的指标。为了提高易用性，此软件包承诺绝不会产生以下类别的浮点值：NaN、无穷大。

Supported metrics 支持的指标

Below is the full list of supported metrics, ordered lexicographically.

​ 以下是按字母顺序排列的受支持指标的完整列表。

/cgo/go-to-c-calls:calls
	Count of calls made from Go to C by the current process.

/cpu/classes/gc/mark/assist:cpu-seconds
	Estimated total CPU time goroutines spent performing GC tasks
	to assist the GC and prevent it from falling behind the application.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/gc/mark/dedicated:cpu-seconds
	Estimated total CPU time spent performing GC tasks on
	processors (as defined by GOMAXPROCS) dedicated to those tasks.
	This includes time spent with the world stopped due to the GC.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/gc/mark/idle:cpu-seconds
	Estimated total CPU time spent performing GC tasks on
	spare CPU resources that the Go scheduler could not otherwise find
	a use for. This should be subtracted from the total GC CPU time to
	obtain a measure of compulsory GC CPU time.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/gc/pause:cpu-seconds
	Estimated total CPU time spent with the application paused by
	the GC. Even if only one thread is running during the pause, this is
	computed as GOMAXPROCS times the pause latency because nothing else
	can be executing. This is the exact sum of samples in /gc/pause:seconds
	if each sample is multiplied by GOMAXPROCS at the time it is taken.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/gc/total:cpu-seconds
	Estimated total CPU time spent performing GC tasks.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics. Sum of all metrics in /cpu/classes/gc.

/cpu/classes/idle:cpu-seconds
	Estimated total available CPU time not spent executing any Go or Go
	runtime code. In other words, the part of /cpu/classes/total:cpu-seconds
	that was unused.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/scavenge/assist:cpu-seconds
	Estimated total CPU time spent returning unused memory to the
	underlying platform in response eagerly in response to memory pressure.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/scavenge/background:cpu-seconds
	Estimated total CPU time spent performing background tasks
	to return unused memory to the underlying platform.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/cpu/classes/scavenge/total:cpu-seconds
	Estimated total CPU time spent performing tasks that return
	unused memory to the underlying platform.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics. Sum of all metrics in /cpu/classes/scavenge.

/cpu/classes/total:cpu-seconds
	Estimated total available CPU time for user Go code or the Go runtime, as
	defined by GOMAXPROCS. In other words, GOMAXPROCS integrated over the
	wall-clock duration this process has been executing for.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics. Sum of all metrics in /cpu/classes.

/cpu/classes/user:cpu-seconds
	Estimated total CPU time spent running user Go code. This may
	also include some small amount of time spent in the Go runtime.
	This metric is an overestimate, and not directly comparable to
	system CPU time measurements. Compare only with other /cpu/classes
	metrics.

/gc/cycles/automatic:gc-cycles
	Count of completed GC cycles generated by the Go runtime.

/gc/cycles/forced:gc-cycles
	Count of completed GC cycles forced by the application.

/gc/cycles/total:gc-cycles
	Count of all completed GC cycles.

/gc/heap/allocs-by-size:bytes
	Distribution of heap allocations by approximate size.
	Note that this does not include tiny objects as defined by /gc/heap/tiny/allocs:objects,
	only tiny blocks.

/gc/heap/allocs:bytes
	Cumulative sum of memory allocated to the heap by the application.

/gc/heap/allocs:objects
	Cumulative count of heap allocations triggered by the application.
	Note that this does not include tiny objects as defined by /gc/heap/tiny/allocs:objects,
	only tiny blocks.

/gc/heap/frees-by-size:bytes
	Distribution of freed heap allocations by approximate size.
	Note that this does not include tiny objects as defined by /gc/heap/tiny/allocs:objects,
	only tiny blocks.

/gc/heap/frees:bytes
	Cumulative sum of heap memory freed by the garbage collector.

/gc/heap/frees:objects
	Cumulative count of heap allocations whose storage was freed by the garbage collector.
	Note that this does not include tiny objects as defined by /gc/heap/tiny/allocs:objects,
	only tiny blocks.

/gc/heap/goal:bytes
	Heap size target for the end of the GC cycle.

/gc/heap/objects:objects
	Number of objects, live or unswept, occupying heap memory.

/gc/heap/tiny/allocs:objects
	Count of small allocations that are packed together into blocks.
	These allocations are counted separately from other allocations
	because each individual allocation is not tracked by the runtime,
	only their block. Each block is already accounted for in
	allocs-by-size and frees-by-size.

/gc/limiter/last-enabled:gc-cycle
	GC cycle the last time the GC CPU limiter was enabled.
	This metric is useful for diagnosing the root cause of an out-of-memory
	error, because the limiter trades memory for CPU time when the GC's CPU
	time gets too high. This is most likely to occur with use of SetMemoryLimit.
	The first GC cycle is cycle 1, so a value of 0 indicates that it was never enabled.

/gc/pauses:seconds
	Distribution individual GC-related stop-the-world pause latencies.

/gc/stack/starting-size:bytes
	The stack size of new goroutines.

/memory/classes/heap/free:bytes
	Memory that is completely free and eligible to be returned to
	the underlying system, but has not been. This metric is the
	runtime's estimate of free address space that is backed by
	physical memory.

/memory/classes/heap/objects:bytes
	Memory occupied by live objects and dead objects that have
	not yet been marked free by the garbage collector.

/memory/classes/heap/released:bytes
	Memory that is completely free and has been returned to
	the underlying system. This metric is the runtime's estimate of
	free address space that is still mapped into the process, but
	is not backed by physical memory.

/memory/classes/heap/stacks:bytes
	Memory allocated from the heap that is reserved for stack
	space, whether or not it is currently in-use.

/memory/classes/heap/unused:bytes
	Memory that is reserved for heap objects but is not currently
	used to hold heap objects.

/memory/classes/metadata/mcache/free:bytes
	Memory that is reserved for runtime mcache structures, but
	not in-use.

/memory/classes/metadata/mcache/inuse:bytes
	Memory that is occupied by runtime mcache structures that
	are currently being used.

/memory/classes/metadata/mspan/free:bytes
	Memory that is reserved for runtime mspan structures, but
	not in-use.

/memory/classes/metadata/mspan/inuse:bytes
	Memory that is occupied by runtime mspan structures that are
	currently being used.

/memory/classes/metadata/other:bytes
	Memory that is reserved for or used to hold runtime
	metadata.

/memory/classes/os-stacks:bytes
	Stack memory allocated by the underlying operating system.

/memory/classes/other:bytes
	Memory used by execution trace buffers, structures for
	debugging the runtime, finalizer and profiler specials, and
	more.

/memory/classes/profiling/buckets:bytes
	Memory that is used by the stack trace hash map used for
	profiling.

/memory/classes/total:bytes
	All memory mapped by the Go runtime into the current process
	as read-write. Note that this does not include memory mapped
	by code called via cgo or via the syscall package.
	Sum of all metrics in /memory/classes.

/sched/gomaxprocs:threads
	The current runtime.GOMAXPROCS setting, or the number of
	operating system threads that can execute user-level Go code
	simultaneously.

/sched/goroutines:goroutines
	Count of live goroutines.

/sched/latencies:seconds
	Distribution of the time goroutines have spent in the scheduler
	in a runnable state before actually running.

/sync/mutex/wait/total:seconds
	Approximate cumulative time goroutines have spent blocked on a
	sync.Mutex or sync.RWMutex. This metric is useful for identifying
	global changes in lock contention. Collect a mutex or block
	profile using the runtime/pprof package for more detailed
	contention data.

常量

This section is empty.

变量

This section is empty.

函数

func Read

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func Read(m []Sample)

Read populates each Value field in the given slice of metric samples.

​ Read 填充给定度量样本切片中的每个 Value 字段。

Desired metrics should be present in the slice with the appropriate name. The user of this API is encouraged to re-use the same slice between calls for efficiency, but is not required to do so.

​ 所需度量应以适当的名称出现在切片中。为了提高效率，鼓励此 API 的用户在调用之间重复使用相同的切片，但不是必需的。

Note that re-use has some caveats. Notably, Values should not be read or manipulated while a Read with that value is outstanding; that is a data race. This property includes pointer-typed Values (for example, Float64Histogram) whose underlying storage will be reused by Read when possible. To safely use such values in a concurrent setting, all data must be deep-copied.

​ 请注意，重复使用有一些注意事项。值得注意的是，在使用该值进行 Read 时，不应读取或操作 Values；这是一个数据竞争。此属性包括指针类型的值（例如，Float64Histogram），Read 在可能时会重用其基础存储。要在并发设置中安全地使用此类值，必须对所有数据进行深度复制。

It is safe to execute multiple Read calls concurrently, but their arguments must share no underlying memory. When in doubt, create a new []Sample from scratch, which is always safe, though may be inefficient.

​ 可以安全地并发执行多个 Read 调用，但它们的实参不得共享基础内存。如有疑问，请从头创建一个新的 []Sample，这始终是安全的，尽管可能效率低下。

Sample values with names not appearing in All will have their Value populated as KindBad to indicate that the name is unknown.

​ 名称未出现在 All 中的样本值将以 KindBad 填充其 Value，以指示名称未知。

Example(ReadingAllMetrics)

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package main

import (
	"fmt"
	"runtime/metrics"
)

func main() {
	// Get descriptions for all supported metrics.
	descs := metrics.All()

	// Create a sample for each metric.
	samples := make([]metrics.Sample, len(descs))
	for i := range samples {
		samples[i].Name = descs[i].Name
	}

	// Sample the metrics. Re-use the samples slice if you can!
	metrics.Read(samples)

	// Iterate over all results.
	for _, sample := range samples {
		// Pull out the name and value.
		name, value := sample.Name, sample.Value

		// Handle each sample.
		switch value.Kind() {
		case metrics.KindUint64:
			fmt.Printf("%s: %d\n", name, value.Uint64())
		case metrics.KindFloat64:
			fmt.Printf("%s: %f\n", name, value.Float64())
		case metrics.KindFloat64Histogram:
			// The histogram may be quite large, so let's just pull out
			// a crude estimate for the median for the sake of this example.
			fmt.Printf("%s: %f\n", name, medianBucket(value.Float64Histogram()))
		case metrics.KindBad:
			// This should never happen because all metrics are supported
			// by construction.
			panic("bug in runtime/metrics package!")
		default:
			// This may happen as new metrics get added.
			//
			// The safest thing to do here is to simply log it somewhere
			// as something to look into, but ignore it for now.
			// In the worst case, you might temporarily miss out on a new metric.
			fmt.Printf("%s: unexpected metric Kind: %v\n", name, value.Kind())
		}
	}
}

func medianBucket(h *metrics.Float64Histogram) float64 {
	total := uint64(0)
	for _, count := range h.Counts {
		total += count
	}
	thresh := total / 2
	total = 0
	for i, count := range h.Counts {
		total += count
		if total >= thresh {
			return h.Buckets[i]
		}
	}
	panic("should not happen")
}

Example(ReadingOneMetric)

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package main

import (
	"fmt"
	"runtime/metrics"
)

func main() {
	// Name of the metric we want to read.
	const myMetric = "/memory/classes/heap/free:bytes"

	// Create a sample for the metric.
	sample := make([]metrics.Sample, 1)
	sample[0].Name = myMetric

	// Sample the metric.
	metrics.Read(sample)

	// Check if the metric is actually supported.
	// If it's not, the resulting value will always have
	// kind KindBad.
	if sample[0].Value.Kind() == metrics.KindBad {
		panic(fmt.Sprintf("metric %q no longer supported", myMetric))
	}

	// Handle the result.
	//
	// It's OK to assume a particular Kind for a metric;
	// they're guaranteed not to change.
	freeBytes := sample[0].Value.Uint64()

	fmt.Printf("free but not released memory: %d\n", freeBytes)
}

类型

type Description

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type Description struct {
	// Name is the full name of the metric which includes the unit.
	//
	// The format of the metric may be described by the following regular expression.
	//
	// 	^(?P<name>/[^:]+):(?P<unit>[^:*/]+(?:[*/][^:*/]+)*)$
	//
	// The format splits the name into two components, separated by a colon: a path which always
	// starts with a /, and a machine-parseable unit. The name may contain any valid Unicode
	// codepoint in between / characters, but by convention will try to stick to lowercase
	// characters and hyphens. An example of such a path might be "/memory/heap/free".
	//
	// The unit is by convention a series of lowercase English unit names (singular or plural)
	// without prefixes delimited by '*' or '/'. The unit names may contain any valid Unicode
	// codepoint that is not a delimiter.
	// Examples of units might be "seconds", "bytes", "bytes/second", "cpu-seconds",
	// "byte*cpu-seconds", and "bytes/second/second".
	//
	// For histograms, multiple units may apply. For instance, the units of the buckets and
	// the count. By convention, for histograms, the units of the count are always "samples"
	// with the type of sample evident by the metric's name, while the unit in the name
	// specifies the buckets' unit.
	//
	// A complete name might look like "/memory/heap/free:bytes".
	Name string

	// Description is an English language sentence describing the metric.
	Description string

	// Kind is the kind of value for this metric.
	//
	// The purpose of this field is to allow users to filter out metrics whose values are
	// types which their application may not understand.
	Kind ValueKind

	// Cumulative is whether or not the metric is cumulative. If a cumulative metric is just
	// a single number, then it increases monotonically. If the metric is a distribution,
	// then each bucket count increases monotonically.
	//
	// This flag thus indicates whether or not it's useful to compute a rate from this value.
	Cumulative bool
}

Description describes a runtime metric.

​ Description 描述运行时度量。

func All

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func All() []Description

All returns a slice of containing metric descriptions for all supported metrics.

​ All 返回一个切片，其中包含所有受支持指标的指标说明。

type Float64Histogram

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type Float64Histogram struct {
	// Counts contains the weights for each histogram bucket.
	//
	// Given N buckets, Count[n] is the weight of the range
	// [bucket[n], bucket[n+1]), for 0 <= n < N.
	Counts []uint64

	// Buckets contains the boundaries of the histogram buckets, in increasing order.
	//
	// Buckets[0] is the inclusive lower bound of the minimum bucket while
	// Buckets[len(Buckets)-1] is the exclusive upper bound of the maximum bucket.
	// Hence, there are len(Buckets)-1 counts. Furthermore, len(Buckets) != 1, always,
	// since at least two boundaries are required to describe one bucket (and 0
	// boundaries are used to describe 0 buckets).
	//
	// Buckets[0] is permitted to have value -Inf and Buckets[len(Buckets)-1] is
	// permitted to have value Inf.
	//
	// For a given metric name, the value of Buckets is guaranteed not to change
	// between calls until program exit.
	//
	// This slice value is permitted to alias with other Float64Histograms' Buckets
	// fields, so the values within should only ever be read. If they need to be
	// modified, the user must make a copy.
	Buckets []float64
}

Float64Histogram represents a distribution of float64 values.

​ Float64Histogram 表示 float64 值的分布。

type Sample

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type Sample struct {
	// Name is the name of the metric sampled.
	//
	// It must correspond to a name in one of the metric descriptions
	// returned by All.
	Name string

	// Value is the value of the metric sample.
	Value Value
}

Sample captures a single metric sample.

​ Sample 捕获单个指标样本。

type Value

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type Value struct {
	// contains filtered or unexported fields
}

Value represents a metric value returned by the runtime.

​ Value 表示运行时返回的指标值。

(Value) Float64

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func (v Value) Float64() float64

Float64 returns the internal float64 value for the metric.

​ Float64 返回指标的内部 float64 值。

If v.Kind() != KindFloat64, this method panics.

​ 如果 v.Kind() != KindFloat64，此方法会引发 panic。

(Value) Float64Histogram

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func (v Value) Float64Histogram() *Float64Histogram

Float64Histogram returns the internal *Float64Histogram value for the metric.

​ Float64Histogram 返回指标的内部 *Float64Histogram 值。

If v.Kind() != KindFloat64Histogram, this method panics.

​ 如果 v.Kind() != KindFloat64Histogram，则此方法会引发 panic。

(Value) Kind

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func (v Value) Kind() ValueKind

Kind returns the tag representing the kind of value this is.

​ 类型返回表示此值类型的标签。

(Value) Uint64

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func (v Value) Uint64() uint64

Uint64 returns the internal uint64 value for the metric.

​ Uint64 返回度量的内部 uint64 值。

If v.Kind() != KindUint64, this method panics.

​ 如果 v.Kind() != KindUint64，此方法会引发恐慌。

type ValueKind

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type ValueKind int

ValueKind is a tag for a metric Value which indicates its type.

​ ValueKind 是度量值 Value 的标签，用于指示其类型。

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const (
	// KindBad indicates that the Value has no type and should not be used.
	KindBad ValueKind = iota

	// KindUint64 indicates that the type of the Value is a uint64.
	KindUint64

	// KindFloat64 indicates that the type of the Value is a float64.
	KindFloat64

	// KindFloat64Histogram indicates that the type of the Value is a *Float64Histogram.
	KindFloat64Histogram
)