// Update our cons/mark estimate. This is the maximum of the value we just computed and the last
	// 4 cons/mark values we measured. The reason we take the maximum here is to bias a noisy
	// cons/mark measurement toward fewer assists at the expense of additional GC cycles (starting
	// earlier).
	oldConsMark := c.consMark
	c.consMark = currentConsMark
	for i := range c.lastConsMark {
		if c.lastConsMark[i] > c.consMark {

						ok = false
					}
				}

				// cpuHog1 called below is the primary source of CPU
				// load, but there may be some background work by the
				// runtime. Since the OS rusage measurement will
				// include all work done by the process, also compare
				// against all samples in our profile.
				var value time.Duration
				for _, sample := range p.Sample {

	// It's OK to simply skip scavenging in these cases. Something else will notice
	// and pick up the tab.
	var now int64
	if pp != nil && bytesToScavenge > 0 {
		// Measure how long we spent scavenging and add that measurement to the assist
		// time so we can track it for the GC CPU limiter.
		//
		// Limiter event tracking might be disabled if we end up here
		// while on a mark worker.
		start := nanotime()

			"and not directly comparable to system CPU time measurements. Compare " +
			"only with other /cpu/classes metrics.",
		Kind:       KindFloat64,
		Cumulative: true,
	},
	{
		Name: "/cpu/classes/gc/total:cpu-seconds",
		Description: "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 " +

		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 metric
		is an overestimate, and not directly comparable to system CPU
		time measurements. Compare only with other /cpu/classes metrics.

import java.math.BigDecimal;
import java.math.RoundingMode;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.stream.Collectors;

/**
 * A collection of measurements of some given units.
 */
public class DataSeries<Q> extends ArrayList<Amount<Q>> {
    private final Amount<Q> average;
    private final Amount<Q> median;
    private final Amount<Q> max;

        return baselines
    }

    @Option(option = "warmups", description = "Number of warmups before measurements")
    void setWarmups(@Nullable String warmups) {
        this.warmups = warmups
    }

    @Option(option = "runs", description = "Number of iterations of measurements")
    void setRuns(@Nullable String runs) {
        this.runs = runs
    }

	return ValidatedSelectorFromSet(ls)
}

// AsSelectorPreValidated converts labels into a selector, but
// assumes that labels are already validated and thus doesn't
// perform any validation.
// According to our measurements this is significantly faster
// in codepaths that matter at high scale.
// Note: this method copies the Set; if the Set is immutable, consider wrapping it with ValidatedSetSelector
// instead, which does not copy.

			th2 = th
			fmt.Print("  diminishing return")
		}
		deltaOld = delta

		fmt.Println()

		// trigger counter
		if th1 >= 0 && th2 >= 0 && count < 0 {
			count = 10 // this many extra measurements after we got both thresholds
		}

		th++
	}
}

func measureSqr(words, nruns int, mode string) time.Duration {
	// more runs for better statistics

	prefixes string
	suffixes string
	regexps  string
}

var (
	// The following set of inclusions add minimal upstream and downstream metrics.
	// Upstream metrics record client side measurements.
	// Downstream metrics record server side measurements.
	upstreamStatsSuffixes = "upstream_rq_1xx,upstream_rq_2xx,upstream_rq_3xx,upstream_rq_4xx,upstream_rq_5xx," +
		"upstream_rq_time,upstream_cx_tx_bytes_total,upstream_cx_rx_bytes_total,upstream_cx_total"