mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-12-01 14:47:38 +00:00
68b6834542
### Describe Your Changes
added opentelemetry exponential histograms support. Such histograms are automatically converted into
VictoriaMetrics histogram with `vmrange` buckets.
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
(cherry picked from commit 9eb0c1fd86
)
362 lines
12 KiB
Go
362 lines
12 KiB
Go
package stream
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import (
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"fmt"
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"io"
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"math"
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"strconv"
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"sync"
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"github.com/VictoriaMetrics/metrics"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/decimal"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/pb"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/writeconcurrencylimiter"
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)
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// ParseStream parses OpenTelemetry protobuf or json data from r and calls callback for the parsed rows.
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//
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// callback shouldn't hold tss items after returning.
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//
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// optional processBody can be used for pre-processing the read request body from r before parsing it in OpenTelemetry format.
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func ParseStream(r io.Reader, isGzipped bool, processBody func([]byte) ([]byte, error), callback func(tss []prompbmarshal.TimeSeries) error) error {
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wcr := writeconcurrencylimiter.GetReader(r)
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defer writeconcurrencylimiter.PutReader(wcr)
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r = wcr
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if isGzipped {
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zr, err := common.GetGzipReader(r)
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if err != nil {
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return fmt.Errorf("cannot read gzip-compressed OpenTelemetry protocol data: %w", err)
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}
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defer common.PutGzipReader(zr)
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r = zr
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}
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wr := getWriteContext()
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defer putWriteContext(wr)
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req, err := wr.readAndUnpackRequest(r, processBody)
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if err != nil {
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return fmt.Errorf("cannot unpack OpenTelemetry metrics: %w", err)
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}
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wr.parseRequestToTss(req)
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if err := callback(wr.tss); err != nil {
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return fmt.Errorf("error when processing OpenTelemetry samples: %w", err)
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}
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return nil
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}
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func (wr *writeContext) appendSamplesFromScopeMetrics(sc *pb.ScopeMetrics) {
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for _, m := range sc.Metrics {
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if len(m.Name) == 0 {
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// skip metrics without names
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continue
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}
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metricName := sanitizeMetricName(m)
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switch {
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case m.Gauge != nil:
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for _, p := range m.Gauge.DataPoints {
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wr.appendSampleFromNumericPoint(metricName, p)
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}
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case m.Sum != nil:
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if m.Sum.AggregationTemporality != pb.AggregationTemporalityCumulative {
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rowsDroppedUnsupportedSum.Inc()
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continue
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}
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for _, p := range m.Sum.DataPoints {
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wr.appendSampleFromNumericPoint(metricName, p)
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}
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case m.Summary != nil:
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for _, p := range m.Summary.DataPoints {
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wr.appendSamplesFromSummary(metricName, p)
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}
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case m.Histogram != nil:
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if m.Histogram.AggregationTemporality != pb.AggregationTemporalityCumulative {
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rowsDroppedUnsupportedHistogram.Inc()
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continue
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}
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for _, p := range m.Histogram.DataPoints {
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wr.appendSamplesFromHistogram(metricName, p)
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}
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case m.ExponentialHistogram != nil:
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if m.ExponentialHistogram.AggregationTemporality != pb.AggregationTemporalityCumulative {
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rowsDroppedUnsupportedExponentialHistogram.Inc()
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continue
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}
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for _, p := range m.ExponentialHistogram.DataPoints {
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wr.appendSamplesFromExponentialHistogram(metricName, p)
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}
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default:
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rowsDroppedUnsupportedMetricType.Inc()
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logger.Warnf("unsupported type for metric %q", metricName)
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}
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}
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}
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// appendSampleFromNumericPoint appends p to wr.tss
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func (wr *writeContext) appendSampleFromNumericPoint(metricName string, p *pb.NumberDataPoint) {
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var v float64
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switch {
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case p.IntValue != nil:
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v = float64(*p.IntValue)
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case p.DoubleValue != nil:
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v = *p.DoubleValue
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}
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t := int64(p.TimeUnixNano / 1e6)
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isStale := (p.Flags)&uint32(1) != 0
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wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
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wr.appendSample(metricName, t, v, isStale)
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}
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// appendSamplesFromSummary appends summary p to wr.tss
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func (wr *writeContext) appendSamplesFromSummary(metricName string, p *pb.SummaryDataPoint) {
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t := int64(p.TimeUnixNano / 1e6)
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isStale := (p.Flags)&uint32(1) != 0
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wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
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wr.appendSample(metricName+"_sum", t, p.Sum, isStale)
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wr.appendSample(metricName+"_count", t, float64(p.Count), isStale)
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for _, q := range p.QuantileValues {
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qValue := strconv.FormatFloat(q.Quantile, 'f', -1, 64)
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wr.appendSampleWithExtraLabel(metricName, "quantile", qValue, t, q.Value, isStale)
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}
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}
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// appendSamplesFromHistogram appends histogram p to wr.tss
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func (wr *writeContext) appendSamplesFromHistogram(metricName string, p *pb.HistogramDataPoint) {
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if len(p.BucketCounts) == 0 {
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// nothing to append
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return
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}
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if len(p.BucketCounts) != len(p.ExplicitBounds)+1 {
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// fast path, broken data format
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logger.Warnf("opentelemetry bad histogram format: %q, size of buckets: %d, size of bounds: %d", metricName, len(p.BucketCounts), len(p.ExplicitBounds))
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return
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}
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t := int64(p.TimeUnixNano / 1e6)
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isStale := (p.Flags)&uint32(1) != 0
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wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
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wr.appendSample(metricName+"_count", t, float64(p.Count), isStale)
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if p.Sum == nil {
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// fast path, convert metric as simple counter.
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// given buckets cannot be used for histogram functions.
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// Negative threshold buckets MAY be used, but then the Histogram MetricPoint MUST NOT contain a sum value as it would no longer be a counter semantically.
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// https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
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return
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}
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wr.appendSample(metricName+"_sum", t, *p.Sum, isStale)
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var cumulative uint64
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for index, bound := range p.ExplicitBounds {
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cumulative += p.BucketCounts[index]
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boundLabelValue := strconv.FormatFloat(bound, 'f', -1, 64)
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wr.appendSampleWithExtraLabel(metricName+"_bucket", "le", boundLabelValue, t, float64(cumulative), isStale)
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}
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cumulative += p.BucketCounts[len(p.BucketCounts)-1]
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wr.appendSampleWithExtraLabel(metricName+"_bucket", "le", "+Inf", t, float64(cumulative), isStale)
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}
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// appendSamplesFromExponentialHistogram appends histogram p to wr.tss
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func (wr *writeContext) appendSamplesFromExponentialHistogram(metricName string, p *pb.ExponentialHistogramDataPoint) {
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t := int64(p.TimeUnixNano / 1e6)
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isStale := (p.Flags)&uint32(1) != 0
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wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
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wr.appendSample(metricName+"_count", t, float64(p.Count), isStale)
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if p.Sum == nil {
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// fast path, convert metric as simple counter.
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// given buckets cannot be used for histogram functions.
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// Negative threshold buckets MAY be used, but then the Histogram MetricPoint MUST NOT contain a sum value as it would no longer be a counter semantically.
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// https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
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return
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}
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wr.appendSample(metricName+"_sum", t, *p.Sum, isStale)
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if p.ZeroCount > 0 {
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vmRange := fmt.Sprintf("%.3e...%.3e", 0.0, p.ZeroThreshold)
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wr.appendSampleWithExtraLabel(metricName+"_bucket", "vmrange", vmRange, t, float64(p.ZeroCount), isStale)
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}
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ratio := math.Pow(2, -float64(p.Scale))
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base := math.Pow(2, ratio)
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if p.Positive != nil {
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bound := math.Pow(2, float64(p.Positive.Offset)*ratio)
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for i, s := range p.Positive.BucketCounts {
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if s > 0 {
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lowerBound := bound * math.Pow(base, float64(i))
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upperBound := lowerBound * base
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vmRange := fmt.Sprintf("%.3e...%.3e", lowerBound, upperBound)
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wr.appendSampleWithExtraLabel(metricName+"_bucket", "vmrange", vmRange, t, float64(s), isStale)
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}
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}
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}
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if p.Negative != nil {
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bound := math.Pow(2, -float64(p.Negative.Offset)*ratio)
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for i, s := range p.Negative.BucketCounts {
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if s > 0 {
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upperBound := bound * math.Pow(base, float64(i))
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lowerBound := upperBound / base
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vmRange := fmt.Sprintf("%.3e...%.3e", lowerBound, upperBound)
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wr.appendSampleWithExtraLabel(metricName+"_bucket", "vmrange", vmRange, t, float64(s), isStale)
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}
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}
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}
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}
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// appendSample appends sample with the given metricName to wr.tss
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func (wr *writeContext) appendSample(metricName string, t int64, v float64, isStale bool) {
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wr.appendSampleWithExtraLabel(metricName, "", "", t, v, isStale)
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}
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// appendSampleWithExtraLabel appends sample with the given metricName and the given (labelName=labelValue) extra label to wr.tss
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func (wr *writeContext) appendSampleWithExtraLabel(metricName, labelName, labelValue string, t int64, v float64, isStale bool) {
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if isStale {
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v = decimal.StaleNaN
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}
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if t <= 0 {
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// Set the current timestamp if t isn't set.
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t = int64(fasttime.UnixTimestamp()) * 1000
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}
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labelsPool := wr.labelsPool
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labelsLen := len(labelsPool)
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labelsPool = append(labelsPool, prompbmarshal.Label{
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Name: "__name__",
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Value: metricName,
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})
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labelsPool = append(labelsPool, wr.baseLabels...)
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labelsPool = append(labelsPool, wr.pointLabels...)
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if labelName != "" && labelValue != "" {
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labelsPool = append(labelsPool, prompbmarshal.Label{
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Name: labelName,
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Value: labelValue,
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})
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}
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samplesPool := wr.samplesPool
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samplesLen := len(samplesPool)
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samplesPool = append(samplesPool, prompbmarshal.Sample{
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Timestamp: t,
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Value: v,
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})
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wr.tss = append(wr.tss, prompbmarshal.TimeSeries{
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Labels: labelsPool[labelsLen:],
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Samples: samplesPool[samplesLen:],
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})
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wr.labelsPool = labelsPool
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wr.samplesPool = samplesPool
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rowsRead.Inc()
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}
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// appendAttributesToPromLabels appends attributes to dst and returns the result.
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func appendAttributesToPromLabels(dst []prompbmarshal.Label, attributes []*pb.KeyValue) []prompbmarshal.Label {
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for _, at := range attributes {
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dst = append(dst, prompbmarshal.Label{
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Name: sanitizeLabelName(at.Key),
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Value: at.Value.FormatString(),
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})
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}
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return dst
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}
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type writeContext struct {
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// bb holds the original data (json or protobuf), which must be parsed.
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bb bytesutil.ByteBuffer
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// tss holds parsed time series
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tss []prompbmarshal.TimeSeries
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// baseLabels are labels, which must be added to all the ingested samples
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baseLabels []prompbmarshal.Label
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// pointLabels are labels, which must be added to the ingested OpenTelemetry points
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pointLabels []prompbmarshal.Label
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// pools are used for reducing memory allocations when parsing time series
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labelsPool []prompbmarshal.Label
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samplesPool []prompbmarshal.Sample
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}
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func (wr *writeContext) reset() {
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wr.bb.Reset()
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clear(wr.tss)
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wr.tss = wr.tss[:0]
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wr.baseLabels = resetLabels(wr.baseLabels)
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wr.pointLabels = resetLabels(wr.pointLabels)
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wr.labelsPool = resetLabels(wr.labelsPool)
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wr.samplesPool = wr.samplesPool[:0]
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}
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func resetLabels(labels []prompbmarshal.Label) []prompbmarshal.Label {
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clear(labels)
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return labels[:0]
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}
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func (wr *writeContext) readAndUnpackRequest(r io.Reader, processBody func([]byte) ([]byte, error)) (*pb.ExportMetricsServiceRequest, error) {
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if _, err := wr.bb.ReadFrom(r); err != nil {
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return nil, fmt.Errorf("cannot read request: %w", err)
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}
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var req pb.ExportMetricsServiceRequest
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if processBody != nil {
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data, err := processBody(wr.bb.B)
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if err != nil {
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return nil, fmt.Errorf("cannot process request body: %w", err)
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}
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wr.bb.B = append(wr.bb.B[:0], data...)
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}
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if err := req.UnmarshalProtobuf(wr.bb.B); err != nil {
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return nil, fmt.Errorf("cannot unmarshal request from %d bytes: %w", len(wr.bb.B), err)
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}
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return &req, nil
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}
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func (wr *writeContext) parseRequestToTss(req *pb.ExportMetricsServiceRequest) {
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for _, rm := range req.ResourceMetrics {
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var attributes []*pb.KeyValue
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if rm.Resource != nil {
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attributes = rm.Resource.Attributes
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}
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wr.baseLabels = appendAttributesToPromLabels(wr.baseLabels[:0], attributes)
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for _, sc := range rm.ScopeMetrics {
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wr.appendSamplesFromScopeMetrics(sc)
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}
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}
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}
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var wrPool sync.Pool
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func getWriteContext() *writeContext {
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v := wrPool.Get()
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if v == nil {
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return &writeContext{}
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}
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return v.(*writeContext)
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}
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func putWriteContext(wr *writeContext) {
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wr.reset()
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wrPool.Put(wr)
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}
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var (
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rowsRead = metrics.NewCounter(`vm_protoparser_rows_read_total{type="opentelemetry"}`)
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rowsDroppedUnsupportedHistogram = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_histogram_aggregation"}`)
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rowsDroppedUnsupportedExponentialHistogram = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_exponential_histogram_aggregation"}`)
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rowsDroppedUnsupportedSum = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_sum_aggregation"}`)
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rowsDroppedUnsupportedMetricType = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_metric_type"}`)
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)
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