2016-08-19 15:03:53 +00:00
|
|
|
// Copyright 2015 The Go Authors. All rights reserved.
|
|
|
|
// Use of this source code is governed by a BSD-style
|
|
|
|
// license that can be found in the LICENSE file.
|
|
|
|
|
|
|
|
// Package timeseries implements a time series structure for stats collection.
|
|
|
|
package timeseries // import "golang.org/x/net/internal/timeseries"
|
|
|
|
|
|
|
|
import (
|
|
|
|
"fmt"
|
|
|
|
"log"
|
|
|
|
"time"
|
|
|
|
)
|
|
|
|
|
|
|
|
const (
|
|
|
|
timeSeriesNumBuckets = 64
|
|
|
|
minuteHourSeriesNumBuckets = 60
|
|
|
|
)
|
|
|
|
|
|
|
|
var timeSeriesResolutions = []time.Duration{
|
|
|
|
1 * time.Second,
|
|
|
|
10 * time.Second,
|
|
|
|
1 * time.Minute,
|
|
|
|
10 * time.Minute,
|
|
|
|
1 * time.Hour,
|
|
|
|
6 * time.Hour,
|
|
|
|
24 * time.Hour, // 1 day
|
|
|
|
7 * 24 * time.Hour, // 1 week
|
|
|
|
4 * 7 * 24 * time.Hour, // 4 weeks
|
|
|
|
16 * 7 * 24 * time.Hour, // 16 weeks
|
|
|
|
}
|
|
|
|
|
|
|
|
var minuteHourSeriesResolutions = []time.Duration{
|
|
|
|
1 * time.Second,
|
|
|
|
1 * time.Minute,
|
|
|
|
}
|
|
|
|
|
|
|
|
// An Observable is a kind of data that can be aggregated in a time series.
|
|
|
|
type Observable interface {
|
|
|
|
Multiply(ratio float64) // Multiplies the data in self by a given ratio
|
|
|
|
Add(other Observable) // Adds the data from a different observation to self
|
|
|
|
Clear() // Clears the observation so it can be reused.
|
|
|
|
CopyFrom(other Observable) // Copies the contents of a given observation to self
|
|
|
|
}
|
|
|
|
|
|
|
|
// Float attaches the methods of Observable to a float64.
|
|
|
|
type Float float64
|
|
|
|
|
|
|
|
// NewFloat returns a Float.
|
|
|
|
func NewFloat() Observable {
|
|
|
|
f := Float(0)
|
|
|
|
return &f
|
|
|
|
}
|
|
|
|
|
|
|
|
// String returns the float as a string.
|
|
|
|
func (f *Float) String() string { return fmt.Sprintf("%g", f.Value()) }
|
|
|
|
|
|
|
|
// Value returns the float's value.
|
|
|
|
func (f *Float) Value() float64 { return float64(*f) }
|
|
|
|
|
|
|
|
func (f *Float) Multiply(ratio float64) { *f *= Float(ratio) }
|
|
|
|
|
|
|
|
func (f *Float) Add(other Observable) {
|
|
|
|
o := other.(*Float)
|
|
|
|
*f += *o
|
|
|
|
}
|
|
|
|
|
|
|
|
func (f *Float) Clear() { *f = 0 }
|
|
|
|
|
|
|
|
func (f *Float) CopyFrom(other Observable) {
|
|
|
|
o := other.(*Float)
|
|
|
|
*f = *o
|
|
|
|
}
|
|
|
|
|
|
|
|
// A Clock tells the current time.
|
|
|
|
type Clock interface {
|
|
|
|
Time() time.Time
|
|
|
|
}
|
|
|
|
|
|
|
|
type defaultClock int
|
|
|
|
|
|
|
|
var defaultClockInstance defaultClock
|
|
|
|
|
|
|
|
func (defaultClock) Time() time.Time { return time.Now() }
|
|
|
|
|
|
|
|
// Information kept per level. Each level consists of a circular list of
|
|
|
|
// observations. The start of the level may be derived from end and the
|
|
|
|
// len(buckets) * sizeInMillis.
|
|
|
|
type tsLevel struct {
|
|
|
|
oldest int // index to oldest bucketed Observable
|
|
|
|
newest int // index to newest bucketed Observable
|
|
|
|
end time.Time // end timestamp for this level
|
|
|
|
size time.Duration // duration of the bucketed Observable
|
|
|
|
buckets []Observable // collections of observations
|
|
|
|
provider func() Observable // used for creating new Observable
|
|
|
|
}
|
|
|
|
|
|
|
|
func (l *tsLevel) Clear() {
|
|
|
|
l.oldest = 0
|
|
|
|
l.newest = len(l.buckets) - 1
|
|
|
|
l.end = time.Time{}
|
|
|
|
for i := range l.buckets {
|
|
|
|
if l.buckets[i] != nil {
|
|
|
|
l.buckets[i].Clear()
|
|
|
|
l.buckets[i] = nil
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func (l *tsLevel) InitLevel(size time.Duration, numBuckets int, f func() Observable) {
|
|
|
|
l.size = size
|
|
|
|
l.provider = f
|
|
|
|
l.buckets = make([]Observable, numBuckets)
|
|
|
|
}
|
|
|
|
|
|
|
|
// Keeps a sequence of levels. Each level is responsible for storing data at
|
|
|
|
// a given resolution. For example, the first level stores data at a one
|
|
|
|
// minute resolution while the second level stores data at a one hour
|
|
|
|
// resolution.
|
|
|
|
|
|
|
|
// Each level is represented by a sequence of buckets. Each bucket spans an
|
|
|
|
// interval equal to the resolution of the level. New observations are added
|
|
|
|
// to the last bucket.
|
|
|
|
type timeSeries struct {
|
|
|
|
provider func() Observable // make more Observable
|
|
|
|
numBuckets int // number of buckets in each level
|
|
|
|
levels []*tsLevel // levels of bucketed Observable
|
|
|
|
lastAdd time.Time // time of last Observable tracked
|
|
|
|
total Observable // convenient aggregation of all Observable
|
|
|
|
clock Clock // Clock for getting current time
|
|
|
|
pending Observable // observations not yet bucketed
|
|
|
|
pendingTime time.Time // what time are we keeping in pending
|
|
|
|
dirty bool // if there are pending observations
|
|
|
|
}
|
|
|
|
|
|
|
|
// init initializes a level according to the supplied criteria.
|
|
|
|
func (ts *timeSeries) init(resolutions []time.Duration, f func() Observable, numBuckets int, clock Clock) {
|
|
|
|
ts.provider = f
|
|
|
|
ts.numBuckets = numBuckets
|
|
|
|
ts.clock = clock
|
|
|
|
ts.levels = make([]*tsLevel, len(resolutions))
|
|
|
|
|
|
|
|
for i := range resolutions {
|
|
|
|
if i > 0 && resolutions[i-1] >= resolutions[i] {
|
|
|
|
log.Print("timeseries: resolutions must be monotonically increasing")
|
|
|
|
break
|
|
|
|
}
|
|
|
|
newLevel := new(tsLevel)
|
|
|
|
newLevel.InitLevel(resolutions[i], ts.numBuckets, ts.provider)
|
|
|
|
ts.levels[i] = newLevel
|
|
|
|
}
|
|
|
|
|
|
|
|
ts.Clear()
|
|
|
|
}
|
|
|
|
|
|
|
|
// Clear removes all observations from the time series.
|
|
|
|
func (ts *timeSeries) Clear() {
|
|
|
|
ts.lastAdd = time.Time{}
|
|
|
|
ts.total = ts.resetObservation(ts.total)
|
|
|
|
ts.pending = ts.resetObservation(ts.pending)
|
|
|
|
ts.pendingTime = time.Time{}
|
|
|
|
ts.dirty = false
|
|
|
|
|
|
|
|
for i := range ts.levels {
|
|
|
|
ts.levels[i].Clear()
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Add records an observation at the current time.
|
|
|
|
func (ts *timeSeries) Add(observation Observable) {
|
|
|
|
ts.AddWithTime(observation, ts.clock.Time())
|
|
|
|
}
|
|
|
|
|
|
|
|
// AddWithTime records an observation at the specified time.
|
|
|
|
func (ts *timeSeries) AddWithTime(observation Observable, t time.Time) {
|
|
|
|
|
|
|
|
smallBucketDuration := ts.levels[0].size
|
|
|
|
|
|
|
|
if t.After(ts.lastAdd) {
|
|
|
|
ts.lastAdd = t
|
|
|
|
}
|
|
|
|
|
|
|
|
if t.After(ts.pendingTime) {
|
|
|
|
ts.advance(t)
|
|
|
|
ts.mergePendingUpdates()
|
|
|
|
ts.pendingTime = ts.levels[0].end
|
|
|
|
ts.pending.CopyFrom(observation)
|
|
|
|
ts.dirty = true
|
|
|
|
} else if t.After(ts.pendingTime.Add(-1 * smallBucketDuration)) {
|
|
|
|
// The observation is close enough to go into the pending bucket.
|
|
|
|
// This compensates for clock skewing and small scheduling delays
|
|
|
|
// by letting the update stay in the fast path.
|
|
|
|
ts.pending.Add(observation)
|
|
|
|
ts.dirty = true
|
|
|
|
} else {
|
|
|
|
ts.mergeValue(observation, t)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// mergeValue inserts the observation at the specified time in the past into all levels.
|
|
|
|
func (ts *timeSeries) mergeValue(observation Observable, t time.Time) {
|
|
|
|
for _, level := range ts.levels {
|
|
|
|
index := (ts.numBuckets - 1) - int(level.end.Sub(t)/level.size)
|
|
|
|
if 0 <= index && index < ts.numBuckets {
|
|
|
|
bucketNumber := (level.oldest + index) % ts.numBuckets
|
|
|
|
if level.buckets[bucketNumber] == nil {
|
|
|
|
level.buckets[bucketNumber] = level.provider()
|
|
|
|
}
|
|
|
|
level.buckets[bucketNumber].Add(observation)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
ts.total.Add(observation)
|
|
|
|
}
|
|
|
|
|
|
|
|
// mergePendingUpdates applies the pending updates into all levels.
|
|
|
|
func (ts *timeSeries) mergePendingUpdates() {
|
|
|
|
if ts.dirty {
|
|
|
|
ts.mergeValue(ts.pending, ts.pendingTime)
|
|
|
|
ts.pending = ts.resetObservation(ts.pending)
|
|
|
|
ts.dirty = false
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// advance cycles the buckets at each level until the latest bucket in
|
|
|
|
// each level can hold the time specified.
|
|
|
|
func (ts *timeSeries) advance(t time.Time) {
|
|
|
|
if !t.After(ts.levels[0].end) {
|
|
|
|
return
|
|
|
|
}
|
|
|
|
for i := 0; i < len(ts.levels); i++ {
|
|
|
|
level := ts.levels[i]
|
|
|
|
if !level.end.Before(t) {
|
|
|
|
break
|
|
|
|
}
|
|
|
|
|
|
|
|
// If the time is sufficiently far, just clear the level and advance
|
|
|
|
// directly.
|
|
|
|
if !t.Before(level.end.Add(level.size * time.Duration(ts.numBuckets))) {
|
|
|
|
for _, b := range level.buckets {
|
|
|
|
ts.resetObservation(b)
|
|
|
|
}
|
|
|
|
level.end = time.Unix(0, (t.UnixNano()/level.size.Nanoseconds())*level.size.Nanoseconds())
|
|
|
|
}
|
|
|
|
|
|
|
|
for t.After(level.end) {
|
|
|
|
level.end = level.end.Add(level.size)
|
|
|
|
level.newest = level.oldest
|
|
|
|
level.oldest = (level.oldest + 1) % ts.numBuckets
|
|
|
|
ts.resetObservation(level.buckets[level.newest])
|
|
|
|
}
|
|
|
|
|
|
|
|
t = level.end
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Latest returns the sum of the num latest buckets from the level.
|
|
|
|
func (ts *timeSeries) Latest(level, num int) Observable {
|
|
|
|
now := ts.clock.Time()
|
|
|
|
if ts.levels[0].end.Before(now) {
|
|
|
|
ts.advance(now)
|
|
|
|
}
|
|
|
|
|
|
|
|
ts.mergePendingUpdates()
|
|
|
|
|
|
|
|
result := ts.provider()
|
|
|
|
l := ts.levels[level]
|
|
|
|
index := l.newest
|
|
|
|
|
|
|
|
for i := 0; i < num; i++ {
|
|
|
|
if l.buckets[index] != nil {
|
|
|
|
result.Add(l.buckets[index])
|
|
|
|
}
|
|
|
|
if index == 0 {
|
|
|
|
index = ts.numBuckets
|
|
|
|
}
|
|
|
|
index--
|
|
|
|
}
|
|
|
|
|
|
|
|
return result
|
|
|
|
}
|
|
|
|
|
|
|
|
// LatestBuckets returns a copy of the num latest buckets from level.
|
|
|
|
func (ts *timeSeries) LatestBuckets(level, num int) []Observable {
|
|
|
|
if level < 0 || level > len(ts.levels) {
|
|
|
|
log.Print("timeseries: bad level argument: ", level)
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
if num < 0 || num >= ts.numBuckets {
|
|
|
|
log.Print("timeseries: bad num argument: ", num)
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
results := make([]Observable, num)
|
|
|
|
now := ts.clock.Time()
|
|
|
|
if ts.levels[0].end.Before(now) {
|
|
|
|
ts.advance(now)
|
|
|
|
}
|
|
|
|
|
|
|
|
ts.mergePendingUpdates()
|
|
|
|
|
|
|
|
l := ts.levels[level]
|
|
|
|
index := l.newest
|
|
|
|
|
|
|
|
for i := 0; i < num; i++ {
|
|
|
|
result := ts.provider()
|
|
|
|
results[i] = result
|
|
|
|
if l.buckets[index] != nil {
|
|
|
|
result.CopyFrom(l.buckets[index])
|
|
|
|
}
|
|
|
|
|
|
|
|
if index == 0 {
|
|
|
|
index = ts.numBuckets
|
|
|
|
}
|
|
|
|
index -= 1
|
|
|
|
}
|
|
|
|
return results
|
|
|
|
}
|
|
|
|
|
|
|
|
// ScaleBy updates observations by scaling by factor.
|
|
|
|
func (ts *timeSeries) ScaleBy(factor float64) {
|
|
|
|
for _, l := range ts.levels {
|
|
|
|
for i := 0; i < ts.numBuckets; i++ {
|
|
|
|
l.buckets[i].Multiply(factor)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
ts.total.Multiply(factor)
|
|
|
|
ts.pending.Multiply(factor)
|
|
|
|
}
|
|
|
|
|
|
|
|
// Range returns the sum of observations added over the specified time range.
|
|
|
|
// If start or finish times don't fall on bucket boundaries of the same
|
|
|
|
// level, then return values are approximate answers.
|
|
|
|
func (ts *timeSeries) Range(start, finish time.Time) Observable {
|
|
|
|
return ts.ComputeRange(start, finish, 1)[0]
|
|
|
|
}
|
|
|
|
|
|
|
|
// Recent returns the sum of observations from the last delta.
|
|
|
|
func (ts *timeSeries) Recent(delta time.Duration) Observable {
|
|
|
|
now := ts.clock.Time()
|
|
|
|
return ts.Range(now.Add(-delta), now)
|
|
|
|
}
|
|
|
|
|
|
|
|
// Total returns the total of all observations.
|
|
|
|
func (ts *timeSeries) Total() Observable {
|
|
|
|
ts.mergePendingUpdates()
|
|
|
|
return ts.total
|
|
|
|
}
|
|
|
|
|
|
|
|
// ComputeRange computes a specified number of values into a slice using
|
|
|
|
// the observations recorded over the specified time period. The return
|
|
|
|
// values are approximate if the start or finish times don't fall on the
|
|
|
|
// bucket boundaries at the same level or if the number of buckets spanning
|
|
|
|
// the range is not an integral multiple of num.
|
|
|
|
func (ts *timeSeries) ComputeRange(start, finish time.Time, num int) []Observable {
|
|
|
|
if start.After(finish) {
|
|
|
|
log.Printf("timeseries: start > finish, %v>%v", start, finish)
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
if num < 0 {
|
|
|
|
log.Printf("timeseries: num < 0, %v", num)
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
results := make([]Observable, num)
|
|
|
|
|
|
|
|
for _, l := range ts.levels {
|
|
|
|
if !start.Before(l.end.Add(-l.size * time.Duration(ts.numBuckets))) {
|
|
|
|
ts.extract(l, start, finish, num, results)
|
|
|
|
return results
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2017-02-02 21:19:55 +00:00
|
|
|
// Failed to find a level that covers the desired range. So just
|
2016-08-19 15:03:53 +00:00
|
|
|
// extract from the last level, even if it doesn't cover the entire
|
|
|
|
// desired range.
|
|
|
|
ts.extract(ts.levels[len(ts.levels)-1], start, finish, num, results)
|
|
|
|
|
|
|
|
return results
|
|
|
|
}
|
|
|
|
|
|
|
|
// RecentList returns the specified number of values in slice over the most
|
|
|
|
// recent time period of the specified range.
|
|
|
|
func (ts *timeSeries) RecentList(delta time.Duration, num int) []Observable {
|
|
|
|
if delta < 0 {
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
now := ts.clock.Time()
|
|
|
|
return ts.ComputeRange(now.Add(-delta), now, num)
|
|
|
|
}
|
|
|
|
|
|
|
|
// extract returns a slice of specified number of observations from a given
|
|
|
|
// level over a given range.
|
|
|
|
func (ts *timeSeries) extract(l *tsLevel, start, finish time.Time, num int, results []Observable) {
|
|
|
|
ts.mergePendingUpdates()
|
|
|
|
|
|
|
|
srcInterval := l.size
|
|
|
|
dstInterval := finish.Sub(start) / time.Duration(num)
|
|
|
|
dstStart := start
|
|
|
|
srcStart := l.end.Add(-srcInterval * time.Duration(ts.numBuckets))
|
|
|
|
|
|
|
|
srcIndex := 0
|
|
|
|
|
|
|
|
// Where should scanning start?
|
|
|
|
if dstStart.After(srcStart) {
|
2020-02-05 22:23:22 +00:00
|
|
|
advance := int(dstStart.Sub(srcStart) / srcInterval)
|
|
|
|
srcIndex += advance
|
|
|
|
srcStart = srcStart.Add(time.Duration(advance) * srcInterval)
|
2016-08-19 15:03:53 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
// The i'th value is computed as show below.
|
|
|
|
// interval = (finish/start)/num
|
|
|
|
// i'th value = sum of observation in range
|
|
|
|
// [ start + i * interval,
|
|
|
|
// start + (i + 1) * interval )
|
|
|
|
for i := 0; i < num; i++ {
|
|
|
|
results[i] = ts.resetObservation(results[i])
|
|
|
|
dstEnd := dstStart.Add(dstInterval)
|
|
|
|
for srcIndex < ts.numBuckets && srcStart.Before(dstEnd) {
|
|
|
|
srcEnd := srcStart.Add(srcInterval)
|
|
|
|
if srcEnd.After(ts.lastAdd) {
|
|
|
|
srcEnd = ts.lastAdd
|
|
|
|
}
|
|
|
|
|
|
|
|
if !srcEnd.Before(dstStart) {
|
|
|
|
srcValue := l.buckets[(srcIndex+l.oldest)%ts.numBuckets]
|
|
|
|
if !srcStart.Before(dstStart) && !srcEnd.After(dstEnd) {
|
|
|
|
// dst completely contains src.
|
|
|
|
if srcValue != nil {
|
|
|
|
results[i].Add(srcValue)
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
// dst partially overlaps src.
|
|
|
|
overlapStart := maxTime(srcStart, dstStart)
|
|
|
|
overlapEnd := minTime(srcEnd, dstEnd)
|
|
|
|
base := srcEnd.Sub(srcStart)
|
|
|
|
fraction := overlapEnd.Sub(overlapStart).Seconds() / base.Seconds()
|
|
|
|
|
|
|
|
used := ts.provider()
|
|
|
|
if srcValue != nil {
|
|
|
|
used.CopyFrom(srcValue)
|
|
|
|
}
|
|
|
|
used.Multiply(fraction)
|
|
|
|
results[i].Add(used)
|
|
|
|
}
|
|
|
|
|
|
|
|
if srcEnd.After(dstEnd) {
|
|
|
|
break
|
|
|
|
}
|
|
|
|
}
|
|
|
|
srcIndex++
|
|
|
|
srcStart = srcStart.Add(srcInterval)
|
|
|
|
}
|
|
|
|
dstStart = dstStart.Add(dstInterval)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// resetObservation clears the content so the struct may be reused.
|
|
|
|
func (ts *timeSeries) resetObservation(observation Observable) Observable {
|
|
|
|
if observation == nil {
|
|
|
|
observation = ts.provider()
|
|
|
|
} else {
|
|
|
|
observation.Clear()
|
|
|
|
}
|
|
|
|
return observation
|
|
|
|
}
|
|
|
|
|
|
|
|
// TimeSeries tracks data at granularities from 1 second to 16 weeks.
|
|
|
|
type TimeSeries struct {
|
|
|
|
timeSeries
|
|
|
|
}
|
|
|
|
|
|
|
|
// NewTimeSeries creates a new TimeSeries using the function provided for creating new Observable.
|
|
|
|
func NewTimeSeries(f func() Observable) *TimeSeries {
|
|
|
|
return NewTimeSeriesWithClock(f, defaultClockInstance)
|
|
|
|
}
|
|
|
|
|
|
|
|
// NewTimeSeriesWithClock creates a new TimeSeries using the function provided for creating new Observable and the clock for
|
|
|
|
// assigning timestamps.
|
|
|
|
func NewTimeSeriesWithClock(f func() Observable, clock Clock) *TimeSeries {
|
|
|
|
ts := new(TimeSeries)
|
|
|
|
ts.timeSeries.init(timeSeriesResolutions, f, timeSeriesNumBuckets, clock)
|
|
|
|
return ts
|
|
|
|
}
|
|
|
|
|
|
|
|
// MinuteHourSeries tracks data at granularities of 1 minute and 1 hour.
|
|
|
|
type MinuteHourSeries struct {
|
|
|
|
timeSeries
|
|
|
|
}
|
|
|
|
|
|
|
|
// NewMinuteHourSeries creates a new MinuteHourSeries using the function provided for creating new Observable.
|
|
|
|
func NewMinuteHourSeries(f func() Observable) *MinuteHourSeries {
|
|
|
|
return NewMinuteHourSeriesWithClock(f, defaultClockInstance)
|
|
|
|
}
|
|
|
|
|
|
|
|
// NewMinuteHourSeriesWithClock creates a new MinuteHourSeries using the function provided for creating new Observable and the clock for
|
|
|
|
// assigning timestamps.
|
|
|
|
func NewMinuteHourSeriesWithClock(f func() Observable, clock Clock) *MinuteHourSeries {
|
|
|
|
ts := new(MinuteHourSeries)
|
|
|
|
ts.timeSeries.init(minuteHourSeriesResolutions, f,
|
|
|
|
minuteHourSeriesNumBuckets, clock)
|
|
|
|
return ts
|
|
|
|
}
|
|
|
|
|
|
|
|
func (ts *MinuteHourSeries) Minute() Observable {
|
|
|
|
return ts.timeSeries.Latest(0, 60)
|
|
|
|
}
|
|
|
|
|
|
|
|
func (ts *MinuteHourSeries) Hour() Observable {
|
|
|
|
return ts.timeSeries.Latest(1, 60)
|
|
|
|
}
|
|
|
|
|
|
|
|
func minTime(a, b time.Time) time.Time {
|
|
|
|
if a.Before(b) {
|
|
|
|
return a
|
|
|
|
}
|
|
|
|
return b
|
|
|
|
}
|
|
|
|
|
|
|
|
func maxTime(a, b time.Time) time.Time {
|
|
|
|
if a.After(b) {
|
|
|
|
return a
|
|
|
|
}
|
|
|
|
return b
|
|
|
|
}
|