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// Copyright 2017, OpenCensus Authors
//
// 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 view
import (
"math"
)
// AggregationData represents an aggregated value from a collection.
// They are reported on the view data during exporting.
// Mosts users won't directly access aggregration data.
type AggregationData interface {
isAggregationData() bool
addSample(v float64)
clone() AggregationData
equal(other AggregationData) bool
}
const epsilon = 1e-9
// CountData is the aggregated data for the Count aggregation.
// A count aggregation processes data and counts the recordings.
//
// Most users won't directly access count data.
type CountData struct {
Value int64
}
func (a *CountData) isAggregationData() bool { return true }
func (a *CountData) addSample(v float64) {
a.Value = a.Value + 1
}
func (a *CountData) clone() AggregationData {
return &CountData{Value: a.Value}
}
func (a *CountData) equal(other AggregationData) bool {
a2, ok := other.(*CountData)
if !ok {
return false
}
return a.Value == a2.Value
}
// SumData is the aggregated data for the Sum aggregation.
// A sum aggregation processes data and sums up the recordings.
//
// Most users won't directly access sum data.
type SumData struct {
Value float64
}
func (a *SumData) isAggregationData() bool { return true }
func (a *SumData) addSample(f float64) {
a.Value += f
}
func (a *SumData) clone() AggregationData {
return &SumData{Value: a.Value}
}
func (a *SumData) equal(other AggregationData) bool {
a2, ok := other.(*SumData)
if !ok {
return false
}
return math.Pow(a.Value-a2.Value, 2) < epsilon
}
// DistributionData is the aggregated data for the
// Distribution aggregation.
//
// Most users won't directly access distribution data.
type DistributionData struct {
Count int64 // number of data points aggregated
Min float64 // minimum value in the distribution
Max float64 // max value in the distribution
Mean float64 // mean of the distribution
SumOfSquaredDev float64 // sum of the squared deviation from the mean
CountPerBucket []int64 // number of occurrences per bucket
bounds []float64 // histogram distribution of the values
}
func newDistributionData(bounds []float64) *DistributionData {
return &DistributionData{
CountPerBucket: make([]int64, len(bounds)+1),
bounds: bounds,
Min: math.MaxFloat64,
Max: math.SmallestNonzeroFloat64,
}
}
// Sum returns the sum of all samples collected.
func (a *DistributionData) Sum() float64 { return a.Mean * float64(a.Count) }
func (a *DistributionData) variance() float64 {
if a.Count <= 1 {
return 0
}
return a.SumOfSquaredDev / float64(a.Count-1)
}
func (a *DistributionData) isAggregationData() bool { return true }
func (a *DistributionData) addSample(f float64) {
if f < a.Min {
a.Min = f
}
if f > a.Max {
a.Max = f
}
a.Count++
a.incrementBucketCount(f)
if a.Count == 1 {
a.Mean = f
return
}
oldMean := a.Mean
a.Mean = a.Mean + (f-a.Mean)/float64(a.Count)
a.SumOfSquaredDev = a.SumOfSquaredDev + (f-oldMean)*(f-a.Mean)
}
func (a *DistributionData) incrementBucketCount(f float64) {
if len(a.bounds) == 0 {
a.CountPerBucket[0]++
return
}
for i, b := range a.bounds {
if f < b {
a.CountPerBucket[i]++
return
}
}
a.CountPerBucket[len(a.bounds)]++
}
func (a *DistributionData) clone() AggregationData {
counts := make([]int64, len(a.CountPerBucket))
copy(counts, a.CountPerBucket)
c := *a
c.CountPerBucket = counts
return &c
}
func (a *DistributionData) equal(other AggregationData) bool {
a2, ok := other.(*DistributionData)
if !ok {
return false
}
if a2 == nil {
return false
}
if len(a.CountPerBucket) != len(a2.CountPerBucket) {
return false
}
for i := range a.CountPerBucket {
if a.CountPerBucket[i] != a2.CountPerBucket[i] {
return false
}
}
return a.Count == a2.Count && a.Min == a2.Min && a.Max == a2.Max && math.Pow(a.Mean-a2.Mean, 2) < epsilon && math.Pow(a.variance()-a2.variance(), 2) < epsilon
}
// LastValueData returns the last value recorded for LastValue aggregation.
type LastValueData struct {
Value float64
}
func (l *LastValueData) isAggregationData() bool {
return true
}
func (l *LastValueData) addSample(v float64) {
l.Value = v
}
func (l *LastValueData) clone() AggregationData {
return &LastValueData{l.Value}
}
func (l *LastValueData) equal(other AggregationData) bool {
a2, ok := other.(*LastValueData)
if !ok {
return false
}
return l.Value == a2.Value
}
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