ref: beb6c03bc8f476b753e5f3e3bc7a4a2e3f8ad355
dir: /metrics/metrics.go/
// Copyright 2017 The Hugo Authors. 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.
// Package metrics provides simple metrics tracking features.
package metrics
import (
"reflect"
"github.com/gohugoio/hugo/helpers"
"github.com/gohugoio/hugo/common/types"
"fmt"
"io"
"math"
"sort"
"strconv"
"strings"
"sync"
"time"
"github.com/gohugoio/hugo/compare"
)
// The Provider interface defines an interface for measuring metrics.
type Provider interface {
// MeasureSince adds a measurement for key to the metric store.
// Used with defer and time.Now().
MeasureSince(key string, start time.Time)
// WriteMetrics will write a summary of the metrics to w.
WriteMetrics(w io.Writer)
// TrackValue tracks the value for diff calculations etc.
TrackValue(key string, value interface{})
// Reset clears the metric store.
Reset()
}
type diff struct {
baseline interface{}
count int
simSum int
}
var counter = 0
func (d *diff) add(v interface{}) *diff {
if types.IsNil(d.baseline) {
d.baseline = v
d.count = 1
d.simSum = 100 // If we get only one it is very cache friendly.
return d
}
adder := howSimilar(v, d.baseline)
d.simSum += adder
d.count++
return d
}
// Store provides storage for a set of metrics.
type Store struct {
calculateHints bool
metrics map[string][]time.Duration
mu sync.Mutex
diffs map[string]*diff
diffmu sync.Mutex
}
// NewProvider returns a new instance of a metric store.
func NewProvider(calculateHints bool) Provider {
return &Store{
calculateHints: calculateHints,
metrics: make(map[string][]time.Duration),
diffs: make(map[string]*diff),
}
}
// Reset clears the metrics store.
func (s *Store) Reset() {
s.mu.Lock()
s.metrics = make(map[string][]time.Duration)
s.mu.Unlock()
s.diffmu.Lock()
s.diffs = make(map[string]*diff)
s.diffmu.Unlock()
}
// TrackValue tracks the value for diff calculations etc.
func (s *Store) TrackValue(key string, value interface{}) {
if !s.calculateHints {
return
}
s.diffmu.Lock()
var (
d *diff
found bool
)
d, found = s.diffs[key]
if !found {
d = &diff{}
s.diffs[key] = d
}
d.add(value)
s.diffmu.Unlock()
}
// MeasureSince adds a measurement for key to the metric store.
func (s *Store) MeasureSince(key string, start time.Time) {
s.mu.Lock()
s.metrics[key] = append(s.metrics[key], time.Since(start))
s.mu.Unlock()
}
// WriteMetrics writes a summary of the metrics to w.
func (s *Store) WriteMetrics(w io.Writer) {
s.mu.Lock()
results := make([]result, len(s.metrics))
var i int
for k, v := range s.metrics {
var sum time.Duration
var max time.Duration
diff, found := s.diffs[k]
cacheFactor := 0
if found {
cacheFactor = int(math.Floor(float64(diff.simSum) / float64(diff.count)))
}
for _, d := range v {
sum += d
if d > max {
max = d
}
}
avg := time.Duration(int(sum) / len(v))
results[i] = result{key: k, count: len(v), max: max, sum: sum, avg: avg, cacheFactor: cacheFactor}
i++
}
s.mu.Unlock()
if s.calculateHints {
fmt.Fprintf(w, " %9s %13s %12s %12s %5s %s\n", "cache", "cumulative", "average", "maximum", "", "")
fmt.Fprintf(w, " %9s %13s %12s %12s %5s %s\n", "potential", "duration", "duration", "duration", "count", "template")
fmt.Fprintf(w, " %9s %13s %12s %12s %5s %s\n", "-----", "----------", "--------", "--------", "-----", "--------")
} else {
fmt.Fprintf(w, " %13s %12s %12s %5s %s\n", "cumulative", "average", "maximum", "", "")
fmt.Fprintf(w, " %13s %12s %12s %5s %s\n", "duration", "duration", "duration", "count", "template")
fmt.Fprintf(w, " %13s %12s %12s %5s %s\n", "----------", "--------", "--------", "-----", "--------")
}
sort.Sort(bySum(results))
for _, v := range results {
if s.calculateHints {
fmt.Fprintf(w, " %9d %13s %12s %12s %5d %s\n", v.cacheFactor, v.sum, v.avg, v.max, v.count, v.key)
} else {
fmt.Fprintf(w, " %13s %12s %12s %5d %s\n", v.sum, v.avg, v.max, v.count, v.key)
}
}
}
// A result represents the calculated results for a given metric.
type result struct {
key string
count int
cacheFactor int
sum time.Duration
max time.Duration
avg time.Duration
}
type bySum []result
func (b bySum) Len() int { return len(b) }
func (b bySum) Swap(i, j int) { b[i], b[j] = b[j], b[i] }
func (b bySum) Less(i, j int) bool { return b[i].sum > b[j].sum }
// howSimilar is a naive diff implementation that returns
// a number between 0-100 indicating how similar a and b are.
func howSimilar(a, b interface{}) int {
t1, t2 := reflect.TypeOf(a), reflect.TypeOf(b)
if t1 != t2 {
return 0
}
if t1.Comparable() && t2.Comparable() {
if a == b {
return 100
}
}
as, ok1 := types.TypeToString(a)
bs, ok2 := types.TypeToString(b)
if ok1 && ok2 {
return howSimilarStrings(as, bs)
}
if ok1 != ok2 {
return 0
}
e1, ok1 := a.(compare.Eqer)
e2, ok2 := b.(compare.Eqer)
if ok1 && ok2 && e1.Eq(e2) {
return 100
}
pe1, pok1 := a.(compare.ProbablyEqer)
pe2, pok2 := b.(compare.ProbablyEqer)
if pok1 && pok2 && pe1.ProbablyEq(pe2) {
return 90
}
h1, h2 := helpers.HashString(a), helpers.HashString(b)
if h1 == h2 {
return 100
}
return 0
}
// howSimilar is a naive diff implementation that returns
// a number between 0-100 indicating how similar a and b are.
// 100 is when all words in a also exists in b.
func howSimilarStrings(a, b string) int {
if a == b {
return 100
}
// Give some weight to the word positions.
const partitionSize = 4
af, bf := strings.Fields(a), strings.Fields(b)
if len(bf) > len(af) {
af, bf = bf, af
}
m1 := make(map[string]bool)
for i, x := range bf {
partition := partition(i, partitionSize)
key := x + "/" + strconv.Itoa(partition)
m1[key] = true
}
common := 0
for i, x := range af {
partition := partition(i, partitionSize)
key := x + "/" + strconv.Itoa(partition)
if m1[key] {
common++
}
}
return int(math.Floor((float64(common) / float64(len(af)) * 100)))
}
func partition(d, scale int) int {
return int(math.Floor((float64(d) / float64(scale)))) * scale
}