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