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stats lib for benchmark

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This commit is contained in:
iamqizhao
2015-04-23 13:10:23 -07:00
parent 571bcddd7c
commit c63da93d52
6 changed files with 1010 additions and 0 deletions
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135
benchmark/stats/counter.go Normal file
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package stats
import (
"sync"
"time"
)
var (
// Used for testing.
TimeNow func() time.Time = time.Now
)
const (
hour = 0
tenminutes = 1
minute = 2
)
// Counter is a counter that keeps track of its recent values over a given
// period of time, and with a given resolution. Use newCounter() to instantiate.
type Counter struct {
mu sync.RWMutex
ts [3]*timeseries
lastUpdate time.Time
}
// newCounter returns a new Counter.
func newCounter() *Counter {
now := TimeNow()
c := &Counter{}
c.ts[hour] = newTimeSeries(now, time.Hour, time.Minute)
c.ts[tenminutes] = newTimeSeries(now, 10*time.Minute, 10*time.Second)
c.ts[minute] = newTimeSeries(now, time.Minute, time.Second)
return c
}
func (c *Counter) advance() time.Time {
now := TimeNow()
for _, ts := range c.ts {
ts.advanceTime(now)
}
return now
}
// Value returns the current value of the counter.
func (c *Counter) Value() int64 {
c.mu.RLock()
defer c.mu.RUnlock()
return c.ts[minute].headValue()
}
// LastUpdate returns the last update time of the counter.
func (c *Counter) LastUpdate() time.Time {
c.mu.RLock()
defer c.mu.RUnlock()
return c.lastUpdate
}
// Set updates the current value of the counter.
func (c *Counter) Set(value int64) {
c.mu.Lock()
defer c.mu.Unlock()
c.lastUpdate = c.advance()
for _, ts := range c.ts {
ts.set(value)
}
}
// Incr increments the current value of the counter by 'delta'.
func (c *Counter) Incr(delta int64) {
c.mu.Lock()
defer c.mu.Unlock()
c.lastUpdate = c.advance()
for _, ts := range c.ts {
ts.incr(delta)
}
}
// Delta1h returns the delta for the last hour.
func (c *Counter) Delta1h() int64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[hour].delta()
}
// Delta10m returns the delta for the last 10 minutes.
func (c *Counter) Delta10m() int64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[tenminutes].delta()
}
// Delta1m returns the delta for the last minute.
func (c *Counter) Delta1m() int64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[minute].delta()
}
// Rate1h returns the rate of change of the counter in the last hour.
func (c *Counter) Rate1h() float64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[hour].rate()
}
// Rate10m returns the rate of change of the counter in the last 10 minutes.
func (c *Counter) Rate10m() float64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[tenminutes].rate()
}
// Rate1m returns the rate of change of the counter in the last minute.
func (c *Counter) Rate1m() float64 {
c.mu.RLock()
defer c.mu.RUnlock()
c.advance()
return c.ts[minute].rate()
}
// Reset resets the counter to an empty state.
func (c *Counter) Reset() {
c.mu.Lock()
defer c.mu.Unlock()
now := TimeNow()
for _, ts := range c.ts {
ts.reset(now)
}
}

255
benchmark/stats/histogram.go Normal file
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package stats
import (
"bytes"
"fmt"
"io"
"strconv"
"strings"
"time"
)
// HistogramValue is the value of Histogram objects.
type HistogramValue struct {
// Count is the total number of values added to the histogram.
Count int64
// Sum is the sum of all the values added to the histogram.
Sum int64
// Min is the minimum of all the values added to the histogram.
Min int64
// Max is the maximum of all the values added to the histogram.
Max int64
// Buckets contains all the buckets of the histogram.
Buckets []HistogramBucket
}
// HistogramBucket is one histogram bucket.
type HistogramBucket struct {
// LowBound is the lower bound of the bucket.
LowBound int64
// Count is the number of values in the bucket.
Count int64
}
// Print writes textual output of the histogram values.
func (v HistogramValue) Print(w io.Writer) {
avg := float64(v.Sum) / float64(v.Count)
fmt.Fprintf(w, "Count: %d Min: %d Max: %d Avg: %.2f\n", v.Count, v.Min, v.Max, avg)
fmt.Fprintf(w, "%s\n", strings.Repeat("-", 60))
if v.Count <= 0 {
return
}
maxBucketDigitLen := len(strconv.FormatInt(v.Buckets[len(v.Buckets)-1].LowBound, 10))
if maxBucketDigitLen < 3 {
// For "inf".
maxBucketDigitLen = 3
}
maxCountDigitLen := len(strconv.FormatInt(v.Count, 10))
percentMulti := 100 / float64(v.Count)
accCount := int64(0)
for i, b := range v.Buckets {
fmt.Fprintf(w, "[%*d, ", maxBucketDigitLen, b.LowBound)
if i+1 < len(v.Buckets) {
fmt.Fprintf(w, "%*d)", maxBucketDigitLen, v.Buckets[i+1].LowBound)
} else {
fmt.Fprintf(w, "%*s)", maxBucketDigitLen, "inf")
}
accCount += b.Count
fmt.Fprintf(w, " %*d %5.1f%% %5.1f%%", maxCountDigitLen, b.Count, float64(b.Count)*percentMulti, float64(accCount)*percentMulti)
const barScale = 0.1
barLength := int(float64(b.Count)*percentMulti*barScale + 0.5)
fmt.Fprintf(w, " %s\n", strings.Repeat("#", barLength))
}
}
// String returns the textual output of the histogram values as string.
func (v HistogramValue) String() string {
var b bytes.Buffer
v.Print(&b)
return b.String()
}
// A Histogram accumulates values in the form of a histogram. The type of the
// values is int64, which is suitable for keeping track of things like RPC
// latency in milliseconds. New histogram objects should be obtained via the
// New() function.
type Histogram struct {
opts HistogramOptions
buckets []bucketInternal
count *Counter
sum *Counter
tracker *Tracker
}
// HistogramOptions contains the parameters that define the histogram's buckets.
type HistogramOptions struct {
// NumBuckets is the number of buckets.
NumBuckets int
// GrowthFactor is the growth factor of the buckets. A value of 0.1
// indicates that bucket N+1 will be 10% larger than bucket N.
GrowthFactor float64
// SmallestBucketSize is the size of the first bucket. Bucket sizes are
// rounded down to the nearest integer.
SmallestBucketSize float64
// MinValue is the lower bound of the first bucket.
MinValue int64
}
// bucketInternal is the internal representation of a bucket, which includes a
// rate counter.
type bucketInternal struct {
lowBound int64
count *Counter
}
// NewHistogram returns a pointer to a new Histogram object that was created
// with the provided options.
func NewHistogram(opts HistogramOptions) *Histogram {
if opts.NumBuckets == 0 {
opts.NumBuckets = 32
}
if opts.SmallestBucketSize == 0.0 {
opts.SmallestBucketSize = 1.0
}
h := Histogram{
opts: opts,
buckets: make([]bucketInternal, opts.NumBuckets),
count: newCounter(),
sum: newCounter(),
tracker: newTracker(),
}
low := opts.MinValue
delta := opts.SmallestBucketSize
for i := 0; i < opts.NumBuckets; i++ {
h.buckets[i].lowBound = low
h.buckets[i].count = newCounter()
low = low + int64(delta)
delta = delta * (1.0 + opts.GrowthFactor)
}
return &h
}
// Opts returns a copy of the options used to create the Histogram.
func (h *Histogram) Opts() HistogramOptions {
return h.opts
}
// Add adds a value to the histogram.
func (h *Histogram) Add(value int64) error {
bucket, err := h.findBucket(value)
if err != nil {
return err
}
h.buckets[bucket].count.Incr(1)
h.count.Incr(1)
h.sum.Incr(value)
h.tracker.Push(value)
return nil
}
// LastUpdate returns the time at which the object was last updated.
func (h *Histogram) LastUpdate() time.Time {
return h.count.LastUpdate()
}
// Value returns the accumulated state of the histogram since it was created.
func (h *Histogram) Value() HistogramValue {
b := make([]HistogramBucket, len(h.buckets))
for i, v := range h.buckets {
b[i] = HistogramBucket{
LowBound: v.lowBound,
Count: v.count.Value(),
}
}
v := HistogramValue{
Count: h.count.Value(),
Sum: h.sum.Value(),
Min: h.tracker.Min(),
Max: h.tracker.Max(),
Buckets: b,
}
return v
}
// Delta1h returns the change in the last hour.
func (h *Histogram) Delta1h() HistogramValue {
b := make([]HistogramBucket, len(h.buckets))
for i, v := range h.buckets {
b[i] = HistogramBucket{
LowBound: v.lowBound,
Count: v.count.Delta1h(),
}
}
v := HistogramValue{
Count: h.count.Delta1h(),
Sum: h.sum.Delta1h(),
Min: h.tracker.Min1h(),
Max: h.tracker.Max1h(),
Buckets: b,
}
return v
}
// Delta10m returns the change in the last 10 minutes.
func (h *Histogram) Delta10m() HistogramValue {
b := make([]HistogramBucket, len(h.buckets))
for i, v := range h.buckets {
b[i] = HistogramBucket{
LowBound: v.lowBound,
Count: v.count.Delta10m(),
}
}
v := HistogramValue{
Count: h.count.Delta10m(),
Sum: h.sum.Delta10m(),
Min: h.tracker.Min10m(),
Max: h.tracker.Max10m(),
Buckets: b,
}
return v
}
// Delta1m returns the change in the last 10 minutes.
func (h *Histogram) Delta1m() HistogramValue {
b := make([]HistogramBucket, len(h.buckets))
for i, v := range h.buckets {
b[i] = HistogramBucket{
LowBound: v.lowBound,
Count: v.count.Delta1m(),
}
}
v := HistogramValue{
Count: h.count.Delta1m(),
Sum: h.sum.Delta1m(),
Min: h.tracker.Min1m(),
Max: h.tracker.Max1m(),
Buckets: b,
}
return v
}
// findBucket does a binary search to find in which bucket the value goes.
func (h *Histogram) findBucket(value int64) (int, error) {
lastBucket := len(h.buckets) - 1
min, max := 0, lastBucket
for max >= min {
b := (min + max) / 2
if value >= h.buckets[b].lowBound && (b == lastBucket || value < h.buckets[b+1].lowBound) {
return b, nil
}
if value < h.buckets[b].lowBound {
max = b - 1
continue
}
min = b + 1
}
return 0, fmt.Errorf("no bucket for value: %f", value)
}

116
benchmark/stats/stats.go Normal file
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package stats
import (
"bytes"
"fmt"
"io"
"math"
"time"
)
// Stats is a simple helper for gathering additional statistics like histogram
// during benchmarks. This is not thread safe.
type Stats struct {
numBuckets int
unit time.Duration
min, max int64
histogram *Histogram
durations durationSlice
dirty bool
}
type durationSlice []time.Duration
// NewStats creates a new Stats instance. If numBuckets is not positive,
// the default value (16) will be used.
func NewStats(numBuckets int) *Stats {
if numBuckets <= 0 {
numBuckets = 16
}
return &Stats{
// Use one more bucket for the last unbounded bucket.
numBuckets: numBuckets + 1,
durations: make(durationSlice, 0, 100000),
}
}
// Add adds an elapsed time per operation to the stats.
func (stats *Stats) Add(d time.Duration) {
stats.durations = append(stats.durations, d)
stats.dirty = true
}
// Clear resets the stats, removing all values.
func (stats *Stats) Clear() {
stats.durations = stats.durations[:0]
stats.histogram = nil
stats.dirty = false
}
// maybeUpdate updates internal stat data if there was any newly added
// stats since this was updated.
func (stats *Stats) maybeUpdate() {
if !stats.dirty {
return
}
stats.min = math.MaxInt64
stats.max = 0
for _, d := range stats.durations {
if stats.min > int64(d) {
stats.min = int64(d)
}
if stats.max < int64(d) {
stats.max = int64(d)
}
}
// Use the largest unit that can represent the minimum time duration.
stats.unit = time.Nanosecond
for _, u := range []time.Duration{time.Microsecond, time.Millisecond, time.Second} {
if stats.min <= int64(u) {
break
}
stats.unit = u
}
// Adjust the min/max according to the new unit.
stats.min /= int64(stats.unit)
stats.max /= int64(stats.unit)
numBuckets := stats.numBuckets
if n := int(stats.max - stats.min + 1); n < numBuckets {
numBuckets = n
}
stats.histogram = NewHistogram(HistogramOptions{
NumBuckets: numBuckets,
// max(i.e., Nth lower bound) = min + (1 + growthFactor)^(numBuckets-2).
GrowthFactor: math.Pow(float64(stats.max-stats.min), 1/float64(stats.numBuckets-2)) - 1,
SmallestBucketSize: 1.0,
MinValue: stats.min})
for _, d := range stats.durations {
stats.histogram.Add(int64(d / stats.unit))
}
stats.dirty = false
}
// Print writes textual output of the Stats.
func (stats *Stats) Print(w io.Writer) {
stats.maybeUpdate()
if stats.histogram == nil {
fmt.Fprint(w, "Histogram (empty)\n")
} else {
fmt.Fprintf(w, "Histogram (unit: %s)\n", fmt.Sprintf("%v", stats.unit)[1:])
stats.histogram.Value().Print(w)
}
}
// String returns the textual output of the Stats as string.
func (stats *Stats) String() string {
var b bytes.Buffer
stats.Print(&b)
return b.String()
}

154
benchmark/stats/timeseries.go Normal file
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package stats
import (
"math"
"time"
)
// timeseries holds the history of a changing value over a predefined period of
// time.
type timeseries struct {
size int // The number of time slots. Equivalent to len(slots).
resolution time.Duration // The time resolution of each slot.
stepCount int64 // The number of intervals seen since creation.
head int // The position of the current time in slots.
time time.Time // The time at the beginning of the current time slot.
slots []int64 // A circular buffer of time slots.
}
// newTimeSeries returns a newly allocated timeseries that covers the requested
// period with the given resolution.
func newTimeSeries(initialTime time.Time, period, resolution time.Duration) *timeseries {
size := int(period.Nanoseconds()/resolution.Nanoseconds()) + 1
return &timeseries{
size: size,
resolution: resolution,
stepCount: 1,
time: initialTime,
slots: make([]int64, size),
}
}
// advanceTimeWithFill moves the timeseries forward to time t and fills in any
// slots that get skipped in the process with the given value. Values older than
// the timeseries period are lost.
func (ts *timeseries) advanceTimeWithFill(t time.Time, value int64) {
advanceTo := t.Truncate(ts.resolution)
if !advanceTo.After(ts.time) {
// This is shortcut for the most common case of a busy counter
// where updates come in many times per ts.resolution.
ts.time = advanceTo
return
}
steps := int(advanceTo.Sub(ts.time).Nanoseconds() / ts.resolution.Nanoseconds())
ts.stepCount += int64(steps)
if steps > ts.size {
steps = ts.size
}
for steps > 0 {
ts.head = (ts.head + 1) % ts.size
ts.slots[ts.head] = value
steps--
}
ts.time = advanceTo
}
// advanceTime moves the timeseries forward to time t and fills in any slots
// that get skipped in the process with the head value. Values older than the
// timeseries period are lost.
func (ts *timeseries) advanceTime(t time.Time) {
ts.advanceTimeWithFill(t, ts.slots[ts.head])
}
// set sets the current value of the timeseries.
func (ts *timeseries) set(value int64) {
ts.slots[ts.head] = value
}
// incr sets the current value of the timeseries.
func (ts *timeseries) incr(delta int64) {
ts.slots[ts.head] += delta
}
// headValue returns the latest value from the timeseries.
func (ts *timeseries) headValue() int64 {
return ts.slots[ts.head]
}
// headTime returns the time of the latest value from the timeseries.
func (ts *timeseries) headTime() time.Time {
return ts.time
}
// tailValue returns the oldest value from the timeseries.
func (ts *timeseries) tailValue() int64 {
if ts.stepCount < int64(ts.size) {
return 0
}
return ts.slots[(ts.head+1)%ts.size]
}
// tailTime returns the time of the oldest value from the timeseries.
func (ts *timeseries) tailTime() time.Time {
size := int64(ts.size)
if ts.stepCount < size {
size = ts.stepCount
}
return ts.time.Add(-time.Duration(size-1) * ts.resolution)
}
// delta returns the difference between the newest and oldest values from the
// timeseries.
func (ts *timeseries) delta() int64 {
return ts.headValue() - ts.tailValue()
}
// rate returns the rate of change between the oldest and newest values from
// the timeseries in units per second.
func (ts *timeseries) rate() float64 {
deltaTime := ts.headTime().Sub(ts.tailTime()).Seconds()
if deltaTime == 0 {
return 0
}
return float64(ts.delta()) / deltaTime
}
// min returns the smallest value from the timeseries.
func (ts *timeseries) min() int64 {
to := ts.size
if ts.stepCount < int64(ts.size) {
to = ts.head + 1
}
tail := (ts.head + 1) % ts.size
min := int64(math.MaxInt64)
for b := 0; b < to; b++ {
if b != tail && ts.slots[b] < min {
min = ts.slots[b]
}
}
return min
}
// max returns the largest value from the timeseries.
func (ts *timeseries) max() int64 {
to := ts.size
if ts.stepCount < int64(ts.size) {
to = ts.head + 1
}
tail := (ts.head + 1) % ts.size
max := int64(math.MinInt64)
for b := 0; b < to; b++ {
if b != tail && ts.slots[b] > max {
max = ts.slots[b]
}
}
return max
}
// reset resets the timeseries to an empty state.
func (ts *timeseries) reset(t time.Time) {
ts.head = 0
ts.time = t
ts.stepCount = 1
ts.slots = make([]int64, ts.size)
}

159
benchmark/stats/tracker.go Normal file
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package stats
import (
"math"
"sync"
"time"
)
// Tracker is a min/max value tracker that keeps track of its min/max values
// over a given period of time, and with a given resolution. The initial min
// and max values are math.MaxInt64 and math.MinInt64 respectively.
type Tracker struct {
mu sync.RWMutex
min, max int64 // All time min/max.
minTS, maxTS [3]*timeseries
lastUpdate time.Time
}
// newTracker returns a new Tracker.
func newTracker() *Tracker {
now := TimeNow()
t := &Tracker{}
t.minTS[hour] = newTimeSeries(now, time.Hour, time.Minute)
t.minTS[tenminutes] = newTimeSeries(now, 10*time.Minute, 10*time.Second)
t.minTS[minute] = newTimeSeries(now, time.Minute, time.Second)
t.maxTS[hour] = newTimeSeries(now, time.Hour, time.Minute)
t.maxTS[tenminutes] = newTimeSeries(now, 10*time.Minute, 10*time.Second)
t.maxTS[minute] = newTimeSeries(now, time.Minute, time.Second)
t.init()
return t
}
func (t *Tracker) init() {
t.min = math.MaxInt64
t.max = math.MinInt64
for _, ts := range t.minTS {
ts.set(math.MaxInt64)
}
for _, ts := range t.maxTS {
ts.set(math.MinInt64)
}
}
func (t *Tracker) advance() time.Time {
now := TimeNow()
for _, ts := range t.minTS {
ts.advanceTimeWithFill(now, math.MaxInt64)
}
for _, ts := range t.maxTS {
ts.advanceTimeWithFill(now, math.MinInt64)
}
return now
}
// LastUpdate returns the last update time of the range.
func (t *Tracker) LastUpdate() time.Time {
t.mu.RLock()
defer t.mu.RUnlock()
return t.lastUpdate
}
// Push adds a new value if it is a new minimum or maximum.
func (t *Tracker) Push(value int64) {
t.mu.Lock()
defer t.mu.Unlock()
t.lastUpdate = t.advance()
if t.min > value {
t.min = value
}
if t.max < value {
t.max = value
}
for _, ts := range t.minTS {
if ts.headValue() > value {
ts.set(value)
}
}
for _, ts := range t.maxTS {
if ts.headValue() < value {
ts.set(value)
}
}
}
// Min returns the minimum value of the tracker
func (t *Tracker) Min() int64 {
t.mu.RLock()
defer t.mu.RUnlock()
return t.min
}
// Max returns the maximum value of the tracker.
func (t *Tracker) Max() int64 {
t.mu.RLock()
defer t.mu.RUnlock()
return t.max
}
// Min1h returns the minimum value for the last hour.
func (t *Tracker) Min1h() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.minTS[hour].min()
}
// Max1h returns the maximum value for the last hour.
func (t *Tracker) Max1h() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.maxTS[hour].max()
}
// Min10m returns the minimum value for the last 10 minutes.
func (t *Tracker) Min10m() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.minTS[tenminutes].min()
}
// Max10m returns the maximum value for the last 10 minutes.
func (t *Tracker) Max10m() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.maxTS[tenminutes].max()
}
// Min1m returns the minimum value for the last 1 minute.
func (t *Tracker) Min1m() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.minTS[minute].min()
}
// Max1m returns the maximum value for the last 1 minute.
func (t *Tracker) Max1m() int64 {
t.mu.Lock()
defer t.mu.Unlock()
t.advance()
return t.maxTS[minute].max()
}
// Reset resets the range to an empty state.
func (t *Tracker) Reset() {
t.mu.Lock()
defer t.mu.Unlock()
now := TimeNow()
for _, ts := range t.minTS {
ts.reset(now)
}
for _, ts := range t.maxTS {
ts.reset(now)
}
t.init()
}

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benchmark/stats/util.go Normal file
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package stats
import (
"bufio"
"bytes"
"fmt"
"os"
"runtime"
"sort"
"strings"
"sync"
"testing"
)
var (
curB *testing.B
curBenchName string
curStats map[string]*Stats
orgStdout *os.File
nextOutPos int
injectCond *sync.Cond
injectDone chan struct{}
)
// AddStats adds a new unnamed Stats instance to the current benchmark. You need
// to run benchmarks by calling RunTestMain() to inject the stats to the
// benchmark results. If numBuckets is not positive, the default value (16) will
// be used. Please note that this calls b.ResetTimer() since it may be blocked
// until the previous benchmark stats is printed out. So AddStats() should
// typically be called at the very beginning of each benchmark function.
func AddStats(b *testing.B, numBuckets int) *Stats {
return AddStatsWithName(b, "", numBuckets)
}
// AddStatsWithName adds a new named Stats instance to the current benchmark.
// With this, you can add multiple stats in a single benchmark. You need
// to run benchmarks by calling RunTestMain() to inject the stats to the
// benchmark results. If numBuckets is not positive, the default value (16) will
// be used. Please note that this calls b.ResetTimer() since it may be blocked
// until the previous benchmark stats is printed out. So AddStatsWithName()
// should typically be called at the very beginning of each benchmark function.
func AddStatsWithName(b *testing.B, name string, numBuckets int) *Stats {
var benchName string
for i := 1; ; i++ {
pc, _, _, ok := runtime.Caller(i)
if !ok {
panic("benchmark function not found")
}
p := strings.Split(runtime.FuncForPC(pc).Name(), ".")
benchName = p[len(p)-1]
if strings.HasPrefix(benchName, "Benchmark") {
break
}
}
procs := runtime.GOMAXPROCS(-1)
if procs != 1 {
benchName = fmt.Sprintf("%s-%d", benchName, procs)
}
stats := NewStats(numBuckets)
if injectCond != nil {
// We need to wait until the previous benchmark stats is printed out.
injectCond.L.Lock()
for curB != nil && curBenchName != benchName {
injectCond.Wait()
}
curB = b
curBenchName = benchName
curStats[name] = stats
injectCond.L.Unlock()
}
b.ResetTimer()
return stats
}
// RunTestMain runs the tests with enabling injection of benchmark stats. It
// returns an exit code to pass to os.Exit.
func RunTestMain(m *testing.M) int {
startStatsInjector()
defer stopStatsInjector()
return m.Run()
}
// startStatsInjector starts stats injection to benchmark results.
func startStatsInjector() {
orgStdout = os.Stdout
r, w, _ := os.Pipe()
os.Stdout = w
nextOutPos = 0
resetCurBenchStats()
injectCond = sync.NewCond(&sync.Mutex{})
injectDone = make(chan struct{})
go func() {
defer close(injectDone)
scanner := bufio.NewScanner(r)
scanner.Split(splitLines)
for scanner.Scan() {
injectStatsIfFinished(scanner.Text())
}
if err := scanner.Err(); err != nil {
panic(err)
}
}()
}
// stopStatsInjector stops stats injection and restores os.Stdout.
func stopStatsInjector() {
os.Stdout.Close()
<-injectDone
injectCond = nil
os.Stdout = orgStdout
}
// splitLines is a split function for a bufio.Scanner that returns each line
// of text, teeing texts to the original stdout even before each line ends.
func splitLines(data []byte, eof bool) (advance int, token []byte, err error) {
if eof && len(data) == 0 {
return 0, nil, nil
}
if i := bytes.IndexByte(data, '\n'); i >= 0 {
orgStdout.Write(data[nextOutPos : i+1])
nextOutPos = 0
return i + 1, data[0:i], nil
}
orgStdout.Write(data[nextOutPos:])
nextOutPos = len(data)
if eof {
// This is a final, non-terminated line. Return it.
return len(data), data, nil
}
return 0, nil, nil
}
// injectStatsIfFinished prints out the stats if the current benchmark finishes.
func injectStatsIfFinished(line string) {
injectCond.L.Lock()
defer injectCond.L.Unlock()
// We assume that the benchmark results start with the benchmark name.
if curB == nil || !strings.HasPrefix(line, curBenchName) {
return
}
if !curB.Failed() {
// Output all stats in alphabetical order.
names := make([]string, 0, len(curStats))
for name := range curStats {
names = append(names, name)
}
sort.Strings(names)
for _, name := range names {
stats := curStats[name]
// The output of stats starts with a header like "Histogram (unit: ms)"
// followed by statistical properties and the buckets. Add the stats name
// if it is a named stats and indent them as Go testing outputs.
lines := strings.Split(stats.String(), "\n")
if n := len(lines); n > 0 {
if name != "" {
name = ": " + name
}
fmt.Fprintf(orgStdout, "--- %s%s\n", lines[0], name)
for _, line := range lines[1 : n-1] {
fmt.Fprintf(orgStdout, "\t%s\n", line)
}
}
}
}
resetCurBenchStats()
injectCond.Signal()
}
// resetCurBenchStats resets the current benchmark stats.
func resetCurBenchStats() {
curB = nil
curBenchName = ""
curStats = make(map[string]*Stats)
}