metrics: pull library and introduce ResettingTimer and InfluxDB reporter (#15910)
* go-metrics: fork library and introduce ResettingTimer and InfluxDB reporter. * vendor: change nonsense/go-metrics to ethersphere/go-metrics * go-metrics: add tests. move ResettingTimer logic from reporter to type. * all, metrics: pull in metrics package in go-ethereum * metrics/test: make sure metrics are enabled for tests * metrics: apply gosimple rules * metrics/exp, internal/debug: init expvar endpoint when starting pprof server * internal/debug: tiny comment formatting fix
This commit is contained in:
Anton Evangelatov
committed by
Péter Szilágyi
Péter Szilágyi
parent
7f74bdf8dd
commit
ae9f97221a
363
metrics/sample_test.go
Normal file
363
metrics/sample_test.go
Normal file
@ -0,0 +1,363 @@
|
||||
package metrics
|
||||
|
||||
import (
|
||||
"math/rand"
|
||||
"runtime"
|
||||
"testing"
|
||||
"time"
|
||||
)
|
||||
|
||||
// Benchmark{Compute,Copy}{1000,1000000} demonstrate that, even for relatively
|
||||
// expensive computations like Variance, the cost of copying the Sample, as
|
||||
// approximated by a make and copy, is much greater than the cost of the
|
||||
// computation for small samples and only slightly less for large samples.
|
||||
func BenchmarkCompute1000(b *testing.B) {
|
||||
s := make([]int64, 1000)
|
||||
for i := 0; i < len(s); i++ {
|
||||
s[i] = int64(i)
|
||||
}
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
SampleVariance(s)
|
||||
}
|
||||
}
|
||||
func BenchmarkCompute1000000(b *testing.B) {
|
||||
s := make([]int64, 1000000)
|
||||
for i := 0; i < len(s); i++ {
|
||||
s[i] = int64(i)
|
||||
}
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
SampleVariance(s)
|
||||
}
|
||||
}
|
||||
func BenchmarkCopy1000(b *testing.B) {
|
||||
s := make([]int64, 1000)
|
||||
for i := 0; i < len(s); i++ {
|
||||
s[i] = int64(i)
|
||||
}
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
sCopy := make([]int64, len(s))
|
||||
copy(sCopy, s)
|
||||
}
|
||||
}
|
||||
func BenchmarkCopy1000000(b *testing.B) {
|
||||
s := make([]int64, 1000000)
|
||||
for i := 0; i < len(s); i++ {
|
||||
s[i] = int64(i)
|
||||
}
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
sCopy := make([]int64, len(s))
|
||||
copy(sCopy, s)
|
||||
}
|
||||
}
|
||||
|
||||
func BenchmarkExpDecaySample257(b *testing.B) {
|
||||
benchmarkSample(b, NewExpDecaySample(257, 0.015))
|
||||
}
|
||||
|
||||
func BenchmarkExpDecaySample514(b *testing.B) {
|
||||
benchmarkSample(b, NewExpDecaySample(514, 0.015))
|
||||
}
|
||||
|
||||
func BenchmarkExpDecaySample1028(b *testing.B) {
|
||||
benchmarkSample(b, NewExpDecaySample(1028, 0.015))
|
||||
}
|
||||
|
||||
func BenchmarkUniformSample257(b *testing.B) {
|
||||
benchmarkSample(b, NewUniformSample(257))
|
||||
}
|
||||
|
||||
func BenchmarkUniformSample514(b *testing.B) {
|
||||
benchmarkSample(b, NewUniformSample(514))
|
||||
}
|
||||
|
||||
func BenchmarkUniformSample1028(b *testing.B) {
|
||||
benchmarkSample(b, NewUniformSample(1028))
|
||||
}
|
||||
|
||||
func TestExpDecaySample10(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(100, 0.99)
|
||||
for i := 0; i < 10; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
if size := s.Count(); 10 != size {
|
||||
t.Errorf("s.Count(): 10 != %v\n", size)
|
||||
}
|
||||
if size := s.Size(); 10 != size {
|
||||
t.Errorf("s.Size(): 10 != %v\n", size)
|
||||
}
|
||||
if l := len(s.Values()); 10 != l {
|
||||
t.Errorf("len(s.Values()): 10 != %v\n", l)
|
||||
}
|
||||
for _, v := range s.Values() {
|
||||
if v > 10 || v < 0 {
|
||||
t.Errorf("out of range [0, 10): %v\n", v)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestExpDecaySample100(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(1000, 0.01)
|
||||
for i := 0; i < 100; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
if size := s.Count(); 100 != size {
|
||||
t.Errorf("s.Count(): 100 != %v\n", size)
|
||||
}
|
||||
if size := s.Size(); 100 != size {
|
||||
t.Errorf("s.Size(): 100 != %v\n", size)
|
||||
}
|
||||
if l := len(s.Values()); 100 != l {
|
||||
t.Errorf("len(s.Values()): 100 != %v\n", l)
|
||||
}
|
||||
for _, v := range s.Values() {
|
||||
if v > 100 || v < 0 {
|
||||
t.Errorf("out of range [0, 100): %v\n", v)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestExpDecaySample1000(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(100, 0.99)
|
||||
for i := 0; i < 1000; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
if size := s.Count(); 1000 != size {
|
||||
t.Errorf("s.Count(): 1000 != %v\n", size)
|
||||
}
|
||||
if size := s.Size(); 100 != size {
|
||||
t.Errorf("s.Size(): 100 != %v\n", size)
|
||||
}
|
||||
if l := len(s.Values()); 100 != l {
|
||||
t.Errorf("len(s.Values()): 100 != %v\n", l)
|
||||
}
|
||||
for _, v := range s.Values() {
|
||||
if v > 1000 || v < 0 {
|
||||
t.Errorf("out of range [0, 1000): %v\n", v)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// This test makes sure that the sample's priority is not amplified by using
|
||||
// nanosecond duration since start rather than second duration since start.
|
||||
// The priority becomes +Inf quickly after starting if this is done,
|
||||
// effectively freezing the set of samples until a rescale step happens.
|
||||
func TestExpDecaySampleNanosecondRegression(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(100, 0.99)
|
||||
for i := 0; i < 100; i++ {
|
||||
s.Update(10)
|
||||
}
|
||||
time.Sleep(1 * time.Millisecond)
|
||||
for i := 0; i < 100; i++ {
|
||||
s.Update(20)
|
||||
}
|
||||
v := s.Values()
|
||||
avg := float64(0)
|
||||
for i := 0; i < len(v); i++ {
|
||||
avg += float64(v[i])
|
||||
}
|
||||
avg /= float64(len(v))
|
||||
if avg > 16 || avg < 14 {
|
||||
t.Errorf("out of range [14, 16]: %v\n", avg)
|
||||
}
|
||||
}
|
||||
|
||||
func TestExpDecaySampleRescale(t *testing.T) {
|
||||
s := NewExpDecaySample(2, 0.001).(*ExpDecaySample)
|
||||
s.update(time.Now(), 1)
|
||||
s.update(time.Now().Add(time.Hour+time.Microsecond), 1)
|
||||
for _, v := range s.values.Values() {
|
||||
if v.k == 0.0 {
|
||||
t.Fatal("v.k == 0.0")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestExpDecaySampleSnapshot(t *testing.T) {
|
||||
now := time.Now()
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(100, 0.99)
|
||||
for i := 1; i <= 10000; i++ {
|
||||
s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i))
|
||||
}
|
||||
snapshot := s.Snapshot()
|
||||
s.Update(1)
|
||||
testExpDecaySampleStatistics(t, snapshot)
|
||||
}
|
||||
|
||||
func TestExpDecaySampleStatistics(t *testing.T) {
|
||||
now := time.Now()
|
||||
rand.Seed(1)
|
||||
s := NewExpDecaySample(100, 0.99)
|
||||
for i := 1; i <= 10000; i++ {
|
||||
s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i))
|
||||
}
|
||||
testExpDecaySampleStatistics(t, s)
|
||||
}
|
||||
|
||||
func TestUniformSample(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewUniformSample(100)
|
||||
for i := 0; i < 1000; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
if size := s.Count(); 1000 != size {
|
||||
t.Errorf("s.Count(): 1000 != %v\n", size)
|
||||
}
|
||||
if size := s.Size(); 100 != size {
|
||||
t.Errorf("s.Size(): 100 != %v\n", size)
|
||||
}
|
||||
if l := len(s.Values()); 100 != l {
|
||||
t.Errorf("len(s.Values()): 100 != %v\n", l)
|
||||
}
|
||||
for _, v := range s.Values() {
|
||||
if v > 1000 || v < 0 {
|
||||
t.Errorf("out of range [0, 100): %v\n", v)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestUniformSampleIncludesTail(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewUniformSample(100)
|
||||
max := 100
|
||||
for i := 0; i < max; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
v := s.Values()
|
||||
sum := 0
|
||||
exp := (max - 1) * max / 2
|
||||
for i := 0; i < len(v); i++ {
|
||||
sum += int(v[i])
|
||||
}
|
||||
if exp != sum {
|
||||
t.Errorf("sum: %v != %v\n", exp, sum)
|
||||
}
|
||||
}
|
||||
|
||||
func TestUniformSampleSnapshot(t *testing.T) {
|
||||
s := NewUniformSample(100)
|
||||
for i := 1; i <= 10000; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
snapshot := s.Snapshot()
|
||||
s.Update(1)
|
||||
testUniformSampleStatistics(t, snapshot)
|
||||
}
|
||||
|
||||
func TestUniformSampleStatistics(t *testing.T) {
|
||||
rand.Seed(1)
|
||||
s := NewUniformSample(100)
|
||||
for i := 1; i <= 10000; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
testUniformSampleStatistics(t, s)
|
||||
}
|
||||
|
||||
func benchmarkSample(b *testing.B, s Sample) {
|
||||
var memStats runtime.MemStats
|
||||
runtime.ReadMemStats(&memStats)
|
||||
pauseTotalNs := memStats.PauseTotalNs
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
s.Update(1)
|
||||
}
|
||||
b.StopTimer()
|
||||
runtime.GC()
|
||||
runtime.ReadMemStats(&memStats)
|
||||
b.Logf("GC cost: %d ns/op", int(memStats.PauseTotalNs-pauseTotalNs)/b.N)
|
||||
}
|
||||
|
||||
func testExpDecaySampleStatistics(t *testing.T, s Sample) {
|
||||
if count := s.Count(); 10000 != count {
|
||||
t.Errorf("s.Count(): 10000 != %v\n", count)
|
||||
}
|
||||
if min := s.Min(); 107 != min {
|
||||
t.Errorf("s.Min(): 107 != %v\n", min)
|
||||
}
|
||||
if max := s.Max(); 10000 != max {
|
||||
t.Errorf("s.Max(): 10000 != %v\n", max)
|
||||
}
|
||||
if mean := s.Mean(); 4965.98 != mean {
|
||||
t.Errorf("s.Mean(): 4965.98 != %v\n", mean)
|
||||
}
|
||||
if stdDev := s.StdDev(); 2959.825156930727 != stdDev {
|
||||
t.Errorf("s.StdDev(): 2959.825156930727 != %v\n", stdDev)
|
||||
}
|
||||
ps := s.Percentiles([]float64{0.5, 0.75, 0.99})
|
||||
if 4615 != ps[0] {
|
||||
t.Errorf("median: 4615 != %v\n", ps[0])
|
||||
}
|
||||
if 7672 != ps[1] {
|
||||
t.Errorf("75th percentile: 7672 != %v\n", ps[1])
|
||||
}
|
||||
if 9998.99 != ps[2] {
|
||||
t.Errorf("99th percentile: 9998.99 != %v\n", ps[2])
|
||||
}
|
||||
}
|
||||
|
||||
func testUniformSampleStatistics(t *testing.T, s Sample) {
|
||||
if count := s.Count(); 10000 != count {
|
||||
t.Errorf("s.Count(): 10000 != %v\n", count)
|
||||
}
|
||||
if min := s.Min(); 37 != min {
|
||||
t.Errorf("s.Min(): 37 != %v\n", min)
|
||||
}
|
||||
if max := s.Max(); 9989 != max {
|
||||
t.Errorf("s.Max(): 9989 != %v\n", max)
|
||||
}
|
||||
if mean := s.Mean(); 4748.14 != mean {
|
||||
t.Errorf("s.Mean(): 4748.14 != %v\n", mean)
|
||||
}
|
||||
if stdDev := s.StdDev(); 2826.684117548333 != stdDev {
|
||||
t.Errorf("s.StdDev(): 2826.684117548333 != %v\n", stdDev)
|
||||
}
|
||||
ps := s.Percentiles([]float64{0.5, 0.75, 0.99})
|
||||
if 4599 != ps[0] {
|
||||
t.Errorf("median: 4599 != %v\n", ps[0])
|
||||
}
|
||||
if 7380.5 != ps[1] {
|
||||
t.Errorf("75th percentile: 7380.5 != %v\n", ps[1])
|
||||
}
|
||||
if 9986.429999999998 != ps[2] {
|
||||
t.Errorf("99th percentile: 9986.429999999998 != %v\n", ps[2])
|
||||
}
|
||||
}
|
||||
|
||||
// TestUniformSampleConcurrentUpdateCount would expose data race problems with
|
||||
// concurrent Update and Count calls on Sample when test is called with -race
|
||||
// argument
|
||||
func TestUniformSampleConcurrentUpdateCount(t *testing.T) {
|
||||
if testing.Short() {
|
||||
t.Skip("skipping in short mode")
|
||||
}
|
||||
s := NewUniformSample(100)
|
||||
for i := 0; i < 100; i++ {
|
||||
s.Update(int64(i))
|
||||
}
|
||||
quit := make(chan struct{})
|
||||
go func() {
|
||||
t := time.NewTicker(10 * time.Millisecond)
|
||||
for {
|
||||
select {
|
||||
case <-t.C:
|
||||
s.Update(rand.Int63())
|
||||
case <-quit:
|
||||
t.Stop()
|
||||
return
|
||||
}
|
||||
}
|
||||
}()
|
||||
for i := 0; i < 1000; i++ {
|
||||
s.Count()
|
||||
time.Sleep(5 * time.Millisecond)
|
||||
}
|
||||
quit <- struct{}{}
|
||||
}
|
||||
Reference in New Issue
Block a user