File: timeseries.go

package info (click to toggle)
golang-golang-x-net-dev 1%3A0.0%2Bgit20181201.351d144%2Bdfsg-3
  • links: PTS, VCS
  • area: main
  • in suites: buster, buster-backports, experimental
  • size: 5,676 kB
  • sloc: makefile: 53; asm: 18
file content (525 lines) | stat: -rw-r--r-- 14,934 bytes parent folder | download | duplicates (6)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
// 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
		}
	}

	// Failed to find a level that covers the desired range. So just
	// 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) {
		advance := dstStart.Sub(srcStart) / srcInterval
		srcIndex += int(advance)
		srcStart = srcStart.Add(advance * srcInterval)
	}

	// 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
}