// 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 }