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// Copyright 2019, 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 (
"time"
"go.opencensus.io/metric/metricdata"
"go.opencensus.io/stats"
)
func getUnit(unit string) metricdata.Unit {
switch unit {
case "1":
return metricdata.UnitDimensionless
case "ms":
return metricdata.UnitMilliseconds
case "By":
return metricdata.UnitBytes
}
return metricdata.UnitDimensionless
}
func getType(v *View) metricdata.Type {
m := v.Measure
agg := v.Aggregation
switch agg.Type {
case AggTypeSum:
switch m.(type) {
case *stats.Int64Measure:
return metricdata.TypeCumulativeInt64
case *stats.Float64Measure:
return metricdata.TypeCumulativeFloat64
default:
panic("unexpected measure type")
}
case AggTypeDistribution:
return metricdata.TypeCumulativeDistribution
case AggTypeLastValue:
switch m.(type) {
case *stats.Int64Measure:
return metricdata.TypeGaugeInt64
case *stats.Float64Measure:
return metricdata.TypeGaugeFloat64
default:
panic("unexpected measure type")
}
case AggTypeCount:
switch m.(type) {
case *stats.Int64Measure:
return metricdata.TypeCumulativeInt64
case *stats.Float64Measure:
return metricdata.TypeCumulativeInt64
default:
panic("unexpected measure type")
}
default:
panic("unexpected aggregation type")
}
}
func getLabelKeys(v *View) []metricdata.LabelKey {
labelKeys := []metricdata.LabelKey{}
for _, k := range v.TagKeys {
labelKeys = append(labelKeys, metricdata.LabelKey{Key: k.Name()})
}
return labelKeys
}
func viewToMetricDescriptor(v *View) *metricdata.Descriptor {
return &metricdata.Descriptor{
Name: v.Name,
Description: v.Description,
Unit: convertUnit(v),
Type: getType(v),
LabelKeys: getLabelKeys(v),
}
}
func convertUnit(v *View) metricdata.Unit {
switch v.Aggregation.Type {
case AggTypeCount:
return metricdata.UnitDimensionless
default:
return getUnit(v.Measure.Unit())
}
}
func toLabelValues(row *Row, expectedKeys []metricdata.LabelKey) []metricdata.LabelValue {
labelValues := []metricdata.LabelValue{}
tagMap := make(map[string]string)
for _, tag := range row.Tags {
tagMap[tag.Key.Name()] = tag.Value
}
for _, key := range expectedKeys {
if val, ok := tagMap[key.Key]; ok {
labelValues = append(labelValues, metricdata.NewLabelValue(val))
} else {
labelValues = append(labelValues, metricdata.LabelValue{})
}
}
return labelValues
}
func rowToTimeseries(v *viewInternal, row *Row, now time.Time, startTime time.Time) *metricdata.TimeSeries {
return &metricdata.TimeSeries{
Points: []metricdata.Point{row.Data.toPoint(v.metricDescriptor.Type, now)},
LabelValues: toLabelValues(row, v.metricDescriptor.LabelKeys),
StartTime: startTime,
}
}
func viewToMetric(v *viewInternal, now time.Time, startTime time.Time) *metricdata.Metric {
if v.metricDescriptor.Type == metricdata.TypeGaugeInt64 ||
v.metricDescriptor.Type == metricdata.TypeGaugeFloat64 {
startTime = time.Time{}
}
rows := v.collectedRows()
if len(rows) == 0 {
return nil
}
ts := []*metricdata.TimeSeries{}
for _, row := range rows {
ts = append(ts, rowToTimeseries(v, row, now, startTime))
}
m := &metricdata.Metric{
Descriptor: *v.metricDescriptor,
TimeSeries: ts,
}
return m
}
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