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stats worker as metric producer. (#1078)
* stats worker as metric producer. * fixed the conversion based on measure type in addition to aggregation type. fixed test. Specifically removed json comparision. * fixed review comments related to count float64. * add check for metricType in toPoint func for distribution Also replaced reflect.DeepEqual with cmp.Equal
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,131 @@ | ||
| // 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 getLableKeys(v *View) []string { | ||
| labelKeys := []string{} | ||
| for _, k := range v.TagKeys { | ||
| labelKeys = append(labelKeys, k.Name()) | ||
| } | ||
| return labelKeys | ||
| } | ||
|
|
||
| func viewToMetricDescriptor(v *View) *metricdata.Descriptor { | ||
| return &metricdata.Descriptor{ | ||
| Name: v.Name, | ||
| Description: v.Description, | ||
| Unit: getUnit(v.Measure.Unit()), | ||
| Type: getType(v), | ||
| LabelKeys: getLableKeys(v), | ||
| } | ||
| } | ||
|
|
||
| func toLabelValues(row *Row) []metricdata.LabelValue { | ||
| labelValues := []metricdata.LabelValue{} | ||
| for _, tag := range row.Tags { | ||
| labelValues = append(labelValues, metricdata.NewLabelValue(tag.Value)) | ||
| } | ||
| 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), | ||
| 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 | ||
| } | ||
|
|
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| 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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