Source: protomem.go in package runtime/pprof


package pprof

import (
	"io"
	"math"
	"runtime"
	"strings"
)

writeHeapProto writes the current heap profile in protobuf format to w.

func writeHeapProto(w io.Writer, p []runtime.MemProfileRecord, rate int64, defaultSampleType string) error {
	b := newProfileBuilder(w)
	b.pbValueType(tagProfile_PeriodType, "space", "bytes")
	b.pb.int64Opt(tagProfile_Period, rate)
	b.pbValueType(tagProfile_SampleType, "alloc_objects", "count")
	b.pbValueType(tagProfile_SampleType, "alloc_space", "bytes")
	b.pbValueType(tagProfile_SampleType, "inuse_objects", "count")
	b.pbValueType(tagProfile_SampleType, "inuse_space", "bytes")
	if defaultSampleType != "" {
		b.pb.int64Opt(tagProfile_DefaultSampleType, b.stringIndex(defaultSampleType))
	}

	values := []int64{0, 0, 0, 0}
	var locs []uint64
	for _, r := range p {
		hideRuntime := true
		for tries := 0; tries < 2; tries++ {

For heap profiles, all stack addresses are return PCs, which is what appendLocsForStack expects.

			if hideRuntime {
				for i, addr := range stk {
					if f := runtime.FuncForPC(addr); f != nil && strings.HasPrefix(f.Name(), "runtime.") {
						continue

Found non-runtime. Show any runtime uses above it.

					stk = stk[i:]
					break
				}
			}
			locs = b.appendLocsForStack(locs[:0], stk)
			if len(locs) > 0 {
				break
			}
			hideRuntime = false // try again, and show all frames next time.
		}

		values[0], values[1] = scaleHeapSample(r.AllocObjects, r.AllocBytes, rate)
		values[2], values[3] = scaleHeapSample(r.InUseObjects(), r.InUseBytes(), rate)
		var blockSize int64
		if r.AllocObjects > 0 {
			blockSize = r.AllocBytes / r.AllocObjects
		}
		b.pbSample(values, locs, func() {
			if blockSize != 0 {
				b.pbLabel(tagSample_Label, "bytes", "", blockSize)
			}
		})
	}
	b.build()
	return nil
}

scaleHeapSample adjusts the data from a heap Sample to account for its probability of appearing in the collected data. heap profiles are a sampling of the memory allocations requests in a program. We estimate the unsampled value by dividing each collected sample by its probability of appearing in the profile. heap profiles rely on a poisson process to determine which samples to collect, based on the desired average collection rate R. The probability of a sample of size S to appear in that profile is 1-exp(-S/R).

func scaleHeapSample(count, size, rate int64) (int64, int64) {
	if count == 0 || size == 0 {
		return 0, 0
	}

if rate==1 all samples were collected so no adjustment is needed. if rate<1 treat as unknown and skip scaling.

		return count, size
	}

	avgSize := float64(size) / float64(count)
	scale := 1 / (1 - math.Exp(-avgSize/float64(rate)))

	return int64(float64(count) * scale), int64(float64(size) * scale)