}

		f, u := measurement.Scale(total, o.SampleUnit, o.OutputUnit)
		fmt.Fprintf(tabw, "%s:\t Total %.1f%s\n", key, f, u)
		for _, t := range graph.SortTags(tags, true) {
			f, u := measurement.Scale(t.FlatValue(), o.SampleUnit, o.OutputUnit)
			if total > 0 {
				fmt.Fprintf(tabw, " \t%.1f%s (%s):\t %s\n", f, u, measurement.Percentage(t.FlatValue(), total), t.Name)
			} else {

			flatValue,
			strings.TrimSpace(measurement.Percentage(flat, b.config.Total)))
	} else {
		label = label + "0"
	}
	cumValue := flatValue
	if cum != flat {
		if flat != 0 {
			label = label + `\n`
		} else {
			label = label + " "
		}
		cumValue = b.config.FormatValue(cum)
		label = label + fmt.Sprintf(`of %s (%s)`,
			cumValue,
			strings.TrimSpace(measurement.Percentage(cum, b.config.Total)))
	}

        return false;
    }

    /**
     * This is a temporary measure for Gradle tasks to track a legacy measurement of all input snapshotting together.
     */
    default void markLegacySnapshottingInputsStarted() {}

    /**
     * This is a temporary measure for Gradle tasks to track a legacy measurement of all input snapshotting together.
     */

	"fmt"
	"html/template"
	"io"
	"net"
	"net/http"
	gourl "net/url"
	"os"
	"os/exec"
	"strconv"
	"strings"
	"time"

	"github.com/google/pprof/internal/graph"
	"github.com/google/pprof/internal/measurement"
	"github.com/google/pprof/internal/plugin"
	"github.com/google/pprof/internal/report"
	"github.com/google/pprof/profile"
)

// webInterface holds the state needed for serving a browser based interface.

import (
	"bytes"
	"fmt"
	"io"
	"net/http"
	"net/url"
	"os"
	"os/exec"
	"path/filepath"
	"runtime"
	"strconv"
	"strings"
	"sync"
	"time"

	"github.com/google/pprof/internal/measurement"
	"github.com/google/pprof/internal/plugin"
	"github.com/google/pprof/profile"
)

// fetchProfiles fetches and symbolizes the profiles specified by s.
// It will merge all the profiles it is able to retrieve, even if

	// Note that the metrics is partially based on the time exported by the endpoints controller on
	// the master machine. The measurement may be inaccurate if there is a clock drift between the
	// node and master machine.
	NetworkProgrammingLatency = metrics.NewHistogram(
		&metrics.HistogramOpts{
			Subsystem: kubeProxySubsystem,

import (
	"bufio"
	"fmt"
	"html/template"
	"io"
	"os"
	"path/filepath"
	"regexp"
	"sort"
	"strconv"
	"strings"

	"github.com/google/pprof/internal/graph"
	"github.com/google/pprof/internal/measurement"
	"github.com/google/pprof/internal/plugin"
	"github.com/google/pprof/profile"
)

// printSource prints an annotated source listing, include all
// functions with samples that match the regexp rpt.options.symbol.

	lock(&ticks.lock)
	t.startTime = nanotime()
	t.startTicks = cputicks()
	unlock(&ticks.lock)
}

// minTimeForTicksPerSecond is the minimum elapsed time we require to consider our ticksPerSecond
// measurement to be of decent enough quality for profiling.
//
// There's a linear relationship here between minimum time and error from the true value.
// The error from the true ticks-per-second in a linux/amd64 VM seems to be:

	startTime            time.Time // Start time for window
	expMovingAvg         float64   // Previously calculated exponential moving average
}

// newRateMeasurement creates a new instance of the measurement with the initial start time.
func newRateMeasurement(initTime time.Time) *rateMeasurement {
	return &rateMeasurement{
		startTime: initTime,
	}
}

// incrementBytes add bytes reported for a bucket/target.

	// so as to be roughly exponential but still round numbers in everyday units. This is to minimise the number
	// of buckets while allowing accurate measurement of thresholds which might be used in SLOs
	// e.g. x% of pods start up within 30 seconds, or 15 minutes, etc.
	PodStartSLIDuration = metrics.NewHistogramVec(
		&metrics.HistogramOpts{
			Subsystem:      KubeletSubsystem,