mirror of
https://github.com/open-telemetry/opentelemetry-go.git
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01b8f15a72
* Add Exemplar to metricdata pkg * Update histogram Aggregator * Update opencensus bridge * Update prometheus exporter * Update OTLP exporter * Update stdoutmetric exporter * Add changes to changelog * Update fail tests * Add tests for IgnoreExemplars * Fix merge
203 lines
7.4 KiB
Go
203 lines
7.4 KiB
Go
// Copyright The OpenTelemetry Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package internal // import "go.opentelemetry.io/otel/bridge/opencensus/internal/ocmetric"
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import (
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"errors"
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"fmt"
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ocmetricdata "go.opencensus.io/metric/metricdata"
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"go.opentelemetry.io/otel/attribute"
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"go.opentelemetry.io/otel/sdk/metric/metricdata"
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)
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var (
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errConversion = errors.New("converting from OpenCensus to OpenTelemetry")
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errAggregationType = errors.New("unsupported OpenCensus aggregation type")
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errMismatchedValueTypes = errors.New("wrong value type for data point")
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errNumberDataPoint = errors.New("converting a number data point")
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errHistogramDataPoint = errors.New("converting a histogram data point")
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errNegativeDistributionCount = errors.New("distribution count is negative")
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errNegativeBucketCount = errors.New("distribution bucket count is negative")
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errMismatchedAttributeKeyValues = errors.New("mismatched number of attribute keys and values")
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)
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// ConvertMetrics converts metric data from OpenCensus to OpenTelemetry.
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func ConvertMetrics(ocmetrics []*ocmetricdata.Metric) ([]metricdata.Metrics, error) {
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otelMetrics := make([]metricdata.Metrics, 0, len(ocmetrics))
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var errInfo []string
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for _, ocm := range ocmetrics {
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if ocm == nil {
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continue
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}
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agg, err := convertAggregation(ocm)
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if err != nil {
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errInfo = append(errInfo, err.Error())
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continue
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}
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otelMetrics = append(otelMetrics, metricdata.Metrics{
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Name: ocm.Descriptor.Name,
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Description: ocm.Descriptor.Description,
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Unit: string(ocm.Descriptor.Unit),
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Data: agg,
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})
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}
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var aggregatedError error
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if len(errInfo) > 0 {
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aggregatedError = fmt.Errorf("%w: %q", errConversion, errInfo)
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}
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return otelMetrics, aggregatedError
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}
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// convertAggregation produces an aggregation based on the OpenCensus Metric.
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func convertAggregation(metric *ocmetricdata.Metric) (metricdata.Aggregation, error) {
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labelKeys := metric.Descriptor.LabelKeys
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switch metric.Descriptor.Type {
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case ocmetricdata.TypeGaugeInt64:
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return convertGauge[int64](labelKeys, metric.TimeSeries)
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case ocmetricdata.TypeGaugeFloat64:
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return convertGauge[float64](labelKeys, metric.TimeSeries)
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case ocmetricdata.TypeCumulativeInt64:
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return convertSum[int64](labelKeys, metric.TimeSeries)
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case ocmetricdata.TypeCumulativeFloat64:
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return convertSum[float64](labelKeys, metric.TimeSeries)
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case ocmetricdata.TypeCumulativeDistribution:
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return convertHistogram(labelKeys, metric.TimeSeries)
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// TODO: Support summaries, once it is in the OTel data types.
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}
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return nil, fmt.Errorf("%w: %q", errAggregationType, metric.Descriptor.Type)
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}
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// convertGauge converts an OpenCensus gauge to an OpenTelemetry gauge aggregation.
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func convertGauge[N int64 | float64](labelKeys []ocmetricdata.LabelKey, ts []*ocmetricdata.TimeSeries) (metricdata.Gauge[N], error) {
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points, err := convertNumberDataPoints[N](labelKeys, ts)
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return metricdata.Gauge[N]{DataPoints: points}, err
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}
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// convertSum converts an OpenCensus cumulative to an OpenTelemetry sum aggregation.
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func convertSum[N int64 | float64](labelKeys []ocmetricdata.LabelKey, ts []*ocmetricdata.TimeSeries) (metricdata.Sum[N], error) {
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points, err := convertNumberDataPoints[N](labelKeys, ts)
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// OpenCensus sums are always Cumulative
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return metricdata.Sum[N]{DataPoints: points, Temporality: metricdata.CumulativeTemporality, IsMonotonic: true}, err
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}
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// convertNumberDataPoints converts OpenCensus TimeSeries to OpenTelemetry DataPoints.
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func convertNumberDataPoints[N int64 | float64](labelKeys []ocmetricdata.LabelKey, ts []*ocmetricdata.TimeSeries) ([]metricdata.DataPoint[N], error) {
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var points []metricdata.DataPoint[N]
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var errInfo []string
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for _, t := range ts {
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attrs, err := convertAttrs(labelKeys, t.LabelValues)
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if err != nil {
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errInfo = append(errInfo, err.Error())
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continue
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}
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for _, p := range t.Points {
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v, ok := p.Value.(N)
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if !ok {
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errInfo = append(errInfo, fmt.Sprintf("%v: %q", errMismatchedValueTypes, p.Value))
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continue
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}
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points = append(points, metricdata.DataPoint[N]{
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Attributes: attrs,
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StartTime: t.StartTime,
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Time: p.Time,
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Value: v,
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})
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}
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}
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var aggregatedError error
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if len(errInfo) > 0 {
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aggregatedError = fmt.Errorf("%w: %v", errNumberDataPoint, errInfo)
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}
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return points, aggregatedError
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}
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// convertHistogram converts OpenCensus Distribution timeseries to an
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// OpenTelemetry Histogram aggregation.
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func convertHistogram(labelKeys []ocmetricdata.LabelKey, ts []*ocmetricdata.TimeSeries) (metricdata.Histogram[float64], error) {
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points := make([]metricdata.HistogramDataPoint[float64], 0, len(ts))
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var errInfo []string
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for _, t := range ts {
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attrs, err := convertAttrs(labelKeys, t.LabelValues)
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if err != nil {
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errInfo = append(errInfo, err.Error())
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continue
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}
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for _, p := range t.Points {
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dist, ok := p.Value.(*ocmetricdata.Distribution)
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if !ok {
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errInfo = append(errInfo, fmt.Sprintf("%v: %d", errMismatchedValueTypes, p.Value))
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continue
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}
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bucketCounts, err := convertBucketCounts(dist.Buckets)
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if err != nil {
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errInfo = append(errInfo, err.Error())
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continue
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}
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if dist.Count < 0 {
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errInfo = append(errInfo, fmt.Sprintf("%v: %d", errNegativeDistributionCount, dist.Count))
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continue
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}
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// TODO: handle exemplars
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points = append(points, metricdata.HistogramDataPoint[float64]{
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Attributes: attrs,
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StartTime: t.StartTime,
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Time: p.Time,
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Count: uint64(dist.Count),
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Sum: dist.Sum,
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Bounds: dist.BucketOptions.Bounds,
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BucketCounts: bucketCounts,
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})
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}
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}
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var aggregatedError error
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if len(errInfo) > 0 {
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aggregatedError = fmt.Errorf("%w: %v", errHistogramDataPoint, errInfo)
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}
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return metricdata.Histogram[float64]{DataPoints: points, Temporality: metricdata.CumulativeTemporality}, aggregatedError
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}
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// convertBucketCounts converts from OpenCensus bucket counts to slice of uint64.
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func convertBucketCounts(buckets []ocmetricdata.Bucket) ([]uint64, error) {
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bucketCounts := make([]uint64, len(buckets))
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for i, bucket := range buckets {
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if bucket.Count < 0 {
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return nil, fmt.Errorf("%w: %q", errNegativeBucketCount, bucket.Count)
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}
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bucketCounts[i] = uint64(bucket.Count)
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}
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return bucketCounts, nil
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}
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// convertAttrs converts from OpenCensus attribute keys and values to an
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// OpenTelemetry attribute Set.
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func convertAttrs(keys []ocmetricdata.LabelKey, values []ocmetricdata.LabelValue) (attribute.Set, error) {
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if len(keys) != len(values) {
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return attribute.NewSet(), fmt.Errorf("%w: keys(%q) values(%q)", errMismatchedAttributeKeyValues, len(keys), len(values))
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}
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attrs := []attribute.KeyValue{}
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for i, lv := range values {
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if !lv.Present {
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continue
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}
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attrs = append(attrs, attribute.KeyValue{
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Key: attribute.Key(keys[i].Key),
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Value: attribute.StringValue(lv.Value),
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})
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}
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return attribute.NewSet(attrs...), nil
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}
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