etcd/tools/benchmark/cmd/report.go
Xiang Li c6430b3292 tools/benchmark: add watch subcommand.
Watch command run benchmark tests for watch releated operations:
1. watch keys 2. sending events to watchers.

To test 2, this test also puts keys into etcd cluster to trigger
event sending.

Besides the benchmark results showed at client side, the tester
can also monitor the server-side mem/cpu usage and also check
the metrics of slow watchers. If there are a lot of slow watchers,
it means etcd server is over-loaded by watchers.
2015-12-03 15:56:17 -08:00

167 lines
3.6 KiB
Go

// Copyright 2014 Google Inc. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// the file is borrowed from github.com/rakyll/boom/boomer/print.go
package cmd
import (
"fmt"
"sort"
"strings"
"time"
)
const (
barChar = "∎"
)
type result struct {
errStr string
duration time.Duration
}
type report struct {
avgTotal float64
fastest float64
slowest float64
average float64
rps float64
results chan *result
total time.Duration
errorDist map[string]int
lats []float64
}
func printReport(size int, results chan *result, total time.Duration) {
r := &report{
results: results,
total: total,
errorDist: make(map[string]int),
}
r.finalize()
r.print()
}
func printRate(size int, results chan *result, total time.Duration) {
r := &report{
results: results,
total: total,
errorDist: make(map[string]int),
}
r.finalize()
fmt.Printf(" Requests/sec:\t%4.4f\n", r.rps)
}
func (r *report) finalize() {
for {
select {
case res := <-r.results:
if res.errStr != "" {
r.errorDist[res.errStr]++
} else {
r.lats = append(r.lats, res.duration.Seconds())
r.avgTotal += res.duration.Seconds()
}
default:
r.rps = float64(len(r.lats)) / r.total.Seconds()
r.average = r.avgTotal / float64(len(r.lats))
return
}
}
}
func (r *report) print() {
sort.Float64s(r.lats)
if len(r.lats) > 0 {
r.fastest = r.lats[0]
r.slowest = r.lats[len(r.lats)-1]
fmt.Printf("\nSummary:\n")
fmt.Printf(" Total:\t%4.4f secs.\n", r.total.Seconds())
fmt.Printf(" Slowest:\t%4.4f secs.\n", r.slowest)
fmt.Printf(" Fastest:\t%4.4f secs.\n", r.fastest)
fmt.Printf(" Average:\t%4.4f secs.\n", r.average)
fmt.Printf(" Requests/sec:\t%4.4f\n", r.rps)
r.printHistogram()
r.printLatencies()
}
if len(r.errorDist) > 0 {
r.printErrors()
}
}
// Prints percentile latencies.
func (r *report) printLatencies() {
pctls := []int{10, 25, 50, 75, 90, 95, 99}
data := make([]float64, len(pctls))
j := 0
for i := 0; i < len(r.lats) && j < len(pctls); i++ {
current := i * 100 / len(r.lats)
if current >= pctls[j] {
data[j] = r.lats[i]
j++
}
}
fmt.Printf("\nLatency distribution:\n")
for i := 0; i < len(pctls); i++ {
if data[i] > 0 {
fmt.Printf(" %v%% in %4.4f secs.\n", pctls[i], data[i])
}
}
}
func (r *report) printHistogram() {
bc := 10
buckets := make([]float64, bc+1)
counts := make([]int, bc+1)
bs := (r.slowest - r.fastest) / float64(bc)
for i := 0; i < bc; i++ {
buckets[i] = r.fastest + bs*float64(i)
}
buckets[bc] = r.slowest
var bi int
var max int
for i := 0; i < len(r.lats); {
if r.lats[i] <= buckets[bi] {
i++
counts[bi]++
if max < counts[bi] {
max = counts[bi]
}
} else if bi < len(buckets)-1 {
bi++
}
}
fmt.Printf("\nResponse time histogram:\n")
for i := 0; i < len(buckets); i++ {
// Normalize bar lengths.
var barLen int
if max > 0 {
barLen = counts[i] * 40 / max
}
fmt.Printf(" %4.3f [%v]\t|%v\n", buckets[i], counts[i], strings.Repeat(barChar, barLen))
}
}
func (r *report) printErrors() {
fmt.Printf("\nError distribution:\n")
for err, num := range r.errorDist {
fmt.Printf(" [%d]\t%s\n", num, err)
}
}