mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-11-21 14:44:00 +00:00
9eb0c1fd86
### 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>
424 lines
12 KiB
Go
424 lines
12 KiB
Go
package stream
|
|
|
|
import (
|
|
"bytes"
|
|
"compress/gzip"
|
|
"fmt"
|
|
"reflect"
|
|
"sort"
|
|
"testing"
|
|
"time"
|
|
|
|
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
|
|
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
|
|
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/pb"
|
|
)
|
|
|
|
func TestParseStream(t *testing.T) {
|
|
f := func(samples []*pb.Metric, tssExpected []prompbmarshal.TimeSeries, usePromNaming bool) {
|
|
t.Helper()
|
|
|
|
prevPromNaming := *usePrometheusNaming
|
|
*usePrometheusNaming = usePromNaming
|
|
defer func() {
|
|
*usePrometheusNaming = prevPromNaming
|
|
}()
|
|
|
|
checkSeries := func(tss []prompbmarshal.TimeSeries) error {
|
|
if len(tss) != len(tssExpected) {
|
|
return fmt.Errorf("not expected tss count, got: %d, want: %d", len(tss), len(tssExpected))
|
|
}
|
|
sortByMetricName(tss)
|
|
sortByMetricName(tssExpected)
|
|
for i := 0; i < len(tss); i++ {
|
|
ts := tss[i]
|
|
tsExpected := tssExpected[i]
|
|
if len(ts.Labels) != len(tsExpected.Labels) {
|
|
return fmt.Errorf("idx: %d, not expected labels count, got: %d, want: %d", i, len(ts.Labels), len(tsExpected.Labels))
|
|
}
|
|
sortLabels(ts.Labels)
|
|
sortLabels(tsExpected.Labels)
|
|
for j, label := range ts.Labels {
|
|
labelExpected := tsExpected.Labels[j]
|
|
if !reflect.DeepEqual(label, labelExpected) {
|
|
return fmt.Errorf("idx: %d, label idx: %d, not equal label pairs, \ngot: \n%s, \nwant: \n%s",
|
|
i, j, prettifyLabel(label), prettifyLabel(labelExpected))
|
|
}
|
|
}
|
|
if len(ts.Samples) != len(tsExpected.Samples) {
|
|
return fmt.Errorf("idx: %d, not expected samples count, got: %d, want: %d", i, len(ts.Samples), len(tsExpected.Samples))
|
|
}
|
|
for j, sample := range ts.Samples {
|
|
sampleExpected := tsExpected.Samples[j]
|
|
if !reflect.DeepEqual(sample, sampleExpected) {
|
|
return fmt.Errorf("idx: %d, label idx: %d, not equal sample pairs, \ngot: \n%s,\nwant: \n%s",
|
|
i, j, prettifySample(sample), prettifySample(sampleExpected))
|
|
}
|
|
}
|
|
}
|
|
return nil
|
|
}
|
|
|
|
req := &pb.ExportMetricsServiceRequest{
|
|
ResourceMetrics: []*pb.ResourceMetrics{
|
|
generateOTLPSamples(samples),
|
|
},
|
|
}
|
|
|
|
// Verify protobuf parsing
|
|
pbData := req.MarshalProtobuf(nil)
|
|
if err := checkParseStream(pbData, checkSeries); err != nil {
|
|
t.Fatalf("cannot parse protobuf: %s", err)
|
|
}
|
|
}
|
|
|
|
jobLabelValue := prompbmarshal.Label{
|
|
Name: "job",
|
|
Value: "vm",
|
|
}
|
|
leLabel := func(value string) prompbmarshal.Label {
|
|
return prompbmarshal.Label{
|
|
Name: "le",
|
|
Value: value,
|
|
}
|
|
}
|
|
kvLabel := func(k, v string) prompbmarshal.Label {
|
|
return prompbmarshal.Label{
|
|
Name: k,
|
|
Value: v,
|
|
}
|
|
}
|
|
|
|
// Test all metric types
|
|
f(
|
|
[]*pb.Metric{
|
|
generateGauge("my-gauge", ""),
|
|
generateHistogram("my-histogram", ""),
|
|
generateSum("my-sum", "", false),
|
|
generateSummary("my-summary", ""),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my-gauge", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
newPromPBTs("my-histogram_count", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2")),
|
|
newPromPBTs("my-histogram_sum", 30000, 30.0, jobLabelValue, kvLabel("label2", "value2")),
|
|
newPromPBTs("my-histogram_bucket", 30000, 0.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("0.1")),
|
|
newPromPBTs("my-histogram_bucket", 30000, 5.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("0.5")),
|
|
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("1")),
|
|
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("5")),
|
|
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("+Inf")),
|
|
newPromPBTs("my-sum", 150000, 15.5, jobLabelValue, kvLabel("label5", "value5")),
|
|
newPromPBTs("my-summary_sum", 35000, 32.5, jobLabelValue, kvLabel("label6", "value6")),
|
|
newPromPBTs("my-summary_count", 35000, 5.0, jobLabelValue, kvLabel("label6", "value6")),
|
|
newPromPBTs("my-summary", 35000, 7.5, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "0.1")),
|
|
newPromPBTs("my-summary", 35000, 10.0, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "0.5")),
|
|
newPromPBTs("my-summary", 35000, 15.0, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "1")),
|
|
},
|
|
false,
|
|
)
|
|
|
|
// Test gauge
|
|
f(
|
|
[]*pb.Metric{
|
|
generateGauge("my-gauge", ""),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my-gauge", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
},
|
|
false,
|
|
)
|
|
|
|
// Test gauge with unit and prometheus naming
|
|
f(
|
|
[]*pb.Metric{
|
|
generateGauge("my-gauge", "ms"),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_gauge_milliseconds", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test gauge with unit inside metric
|
|
f(
|
|
[]*pb.Metric{
|
|
generateGauge("my-gauge-milliseconds", "ms"),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_gauge_milliseconds", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test gauge with ratio suffix
|
|
f(
|
|
[]*pb.Metric{
|
|
generateGauge("my-gauge-milliseconds", "1"),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_gauge_milliseconds_ratio", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test sum with total suffix
|
|
f(
|
|
[]*pb.Metric{
|
|
generateSum("my-sum", "ms", true),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_sum_milliseconds_total", 150000, 15.5, jobLabelValue, kvLabel("label5", "value5")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test sum with total suffix, which exists in a metric name
|
|
f(
|
|
[]*pb.Metric{
|
|
generateSum("my-total-sum", "ms", true),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_sum_milliseconds_total", 150000, 15.5, jobLabelValue, kvLabel("label5", "value5")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test sum with total and complex suffix
|
|
f(
|
|
[]*pb.Metric{
|
|
generateSum("my-total-sum", "m/s", true),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("my_sum_meters_per_second_total", 150000, 15.5, jobLabelValue, kvLabel("label5", "value5")),
|
|
},
|
|
true,
|
|
)
|
|
|
|
// Test exponential histograms
|
|
f(
|
|
[]*pb.Metric{
|
|
generateExpHistogram("test-histogram", "m/s"),
|
|
},
|
|
[]prompbmarshal.TimeSeries{
|
|
newPromPBTs("test_histogram_meters_per_second_bucket", 15000, 5.0, jobLabelValue, kvLabel("label1", "value1"), kvLabel("vmrange", "1.061e+00...1.067e+00")),
|
|
newPromPBTs("test_histogram_meters_per_second_bucket", 15000, 10.0, jobLabelValue, kvLabel("label1", "value1"), kvLabel("vmrange", "1.067e+00...1.073e+00")),
|
|
newPromPBTs("test_histogram_meters_per_second_bucket", 15000, 1.0, jobLabelValue, kvLabel("label1", "value1"), kvLabel("vmrange", "1.085e+00...1.091e+00")),
|
|
newPromPBTs("test_histogram_meters_per_second_count", 15000, 20.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
newPromPBTs("test_histogram_meters_per_second_sum", 15000, 4578.0, jobLabelValue, kvLabel("label1", "value1")),
|
|
},
|
|
true,
|
|
)
|
|
}
|
|
|
|
func checkParseStream(data []byte, checkSeries func(tss []prompbmarshal.TimeSeries) error) error {
|
|
// Verify parsing without compression
|
|
if err := ParseStream(bytes.NewBuffer(data), false, nil, checkSeries); err != nil {
|
|
return fmt.Errorf("error when parsing data: %w", err)
|
|
}
|
|
|
|
// Verify parsing with compression
|
|
var bb bytes.Buffer
|
|
zw := gzip.NewWriter(&bb)
|
|
if _, err := zw.Write(data); err != nil {
|
|
return fmt.Errorf("cannot compress data: %w", err)
|
|
}
|
|
if err := zw.Close(); err != nil {
|
|
return fmt.Errorf("cannot close gzip writer: %w", err)
|
|
}
|
|
if err := ParseStream(&bb, true, nil, checkSeries); err != nil {
|
|
return fmt.Errorf("error when parsing compressed data: %w", err)
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
func attributesFromKV(k, v string) []*pb.KeyValue {
|
|
return []*pb.KeyValue{
|
|
{
|
|
Key: k,
|
|
Value: &pb.AnyValue{
|
|
StringValue: &v,
|
|
},
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateExpHistogram(name, unit string) *pb.Metric {
|
|
sum := float64(4578)
|
|
return &pb.Metric{
|
|
Name: name,
|
|
Unit: unit,
|
|
ExponentialHistogram: &pb.ExponentialHistogram{
|
|
AggregationTemporality: pb.AggregationTemporalityCumulative,
|
|
DataPoints: []*pb.ExponentialHistogramDataPoint{
|
|
{
|
|
Attributes: attributesFromKV("label1", "value1"),
|
|
TimeUnixNano: uint64(15 * time.Second),
|
|
Count: 20,
|
|
Sum: &sum,
|
|
Scale: 7,
|
|
Positive: &pb.Buckets{
|
|
Offset: 7,
|
|
BucketCounts: []uint64{0, 0, 0, 0, 5, 10, 0, 0, 1},
|
|
},
|
|
},
|
|
},
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateGauge(name, unit string) *pb.Metric {
|
|
n := int64(15)
|
|
points := []*pb.NumberDataPoint{
|
|
{
|
|
Attributes: attributesFromKV("label1", "value1"),
|
|
IntValue: &n,
|
|
TimeUnixNano: uint64(15 * time.Second),
|
|
},
|
|
}
|
|
return &pb.Metric{
|
|
Name: name,
|
|
Unit: unit,
|
|
Gauge: &pb.Gauge{
|
|
DataPoints: points,
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateHistogram(name, unit string) *pb.Metric {
|
|
points := []*pb.HistogramDataPoint{
|
|
{
|
|
Attributes: attributesFromKV("label2", "value2"),
|
|
Count: 15,
|
|
Sum: func() *float64 { v := 30.0; return &v }(),
|
|
ExplicitBounds: []float64{0.1, 0.5, 1.0, 5.0},
|
|
BucketCounts: []uint64{0, 5, 10, 0, 0},
|
|
TimeUnixNano: uint64(30 * time.Second),
|
|
},
|
|
}
|
|
return &pb.Metric{
|
|
Name: name,
|
|
Unit: unit,
|
|
Histogram: &pb.Histogram{
|
|
AggregationTemporality: pb.AggregationTemporalityCumulative,
|
|
DataPoints: points,
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateSum(name, unit string, isMonotonic bool) *pb.Metric {
|
|
d := float64(15.5)
|
|
points := []*pb.NumberDataPoint{
|
|
{
|
|
Attributes: attributesFromKV("label5", "value5"),
|
|
DoubleValue: &d,
|
|
TimeUnixNano: uint64(150 * time.Second),
|
|
},
|
|
}
|
|
return &pb.Metric{
|
|
Name: name,
|
|
Unit: unit,
|
|
Sum: &pb.Sum{
|
|
AggregationTemporality: pb.AggregationTemporalityCumulative,
|
|
DataPoints: points,
|
|
IsMonotonic: isMonotonic,
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateSummary(name, unit string) *pb.Metric {
|
|
points := []*pb.SummaryDataPoint{
|
|
{
|
|
Attributes: attributesFromKV("label6", "value6"),
|
|
TimeUnixNano: uint64(35 * time.Second),
|
|
Sum: 32.5,
|
|
Count: 5,
|
|
QuantileValues: []*pb.ValueAtQuantile{
|
|
{
|
|
Quantile: 0.1,
|
|
Value: 7.5,
|
|
},
|
|
{
|
|
Quantile: 0.5,
|
|
Value: 10.0,
|
|
},
|
|
{
|
|
Quantile: 1.0,
|
|
Value: 15.0,
|
|
},
|
|
},
|
|
},
|
|
}
|
|
return &pb.Metric{
|
|
Name: name,
|
|
Unit: unit,
|
|
Summary: &pb.Summary{
|
|
DataPoints: points,
|
|
},
|
|
}
|
|
}
|
|
|
|
func generateOTLPSamples(srcs []*pb.Metric) *pb.ResourceMetrics {
|
|
otlpMetrics := &pb.ResourceMetrics{
|
|
Resource: &pb.Resource{
|
|
Attributes: attributesFromKV("job", "vm"),
|
|
},
|
|
}
|
|
otlpMetrics.ScopeMetrics = []*pb.ScopeMetrics{
|
|
{
|
|
Metrics: append([]*pb.Metric{}, srcs...),
|
|
},
|
|
}
|
|
return otlpMetrics
|
|
}
|
|
|
|
func newPromPBTs(metricName string, t int64, v float64, extraLabels ...prompbmarshal.Label) prompbmarshal.TimeSeries {
|
|
if t <= 0 {
|
|
// Set the current timestamp if t isn't set.
|
|
t = int64(fasttime.UnixTimestamp()) * 1000
|
|
}
|
|
ts := prompbmarshal.TimeSeries{
|
|
Labels: []prompbmarshal.Label{
|
|
{
|
|
Name: "__name__",
|
|
Value: metricName,
|
|
},
|
|
},
|
|
Samples: []prompbmarshal.Sample{
|
|
{
|
|
Value: v,
|
|
Timestamp: t,
|
|
},
|
|
},
|
|
}
|
|
ts.Labels = append(ts.Labels, extraLabels...)
|
|
return ts
|
|
}
|
|
|
|
func prettifyLabel(label prompbmarshal.Label) string {
|
|
return fmt.Sprintf("name=%q value=%q", label.Name, label.Value)
|
|
}
|
|
|
|
func prettifySample(sample prompbmarshal.Sample) string {
|
|
return fmt.Sprintf("sample=%f timestamp: %d", sample.Value, sample.Timestamp)
|
|
}
|
|
|
|
func sortByMetricName(tss []prompbmarshal.TimeSeries) {
|
|
sort.Slice(tss, func(i, j int) bool {
|
|
return getMetricName(tss[i].Labels) < getMetricName(tss[j].Labels)
|
|
})
|
|
}
|
|
|
|
func getMetricName(labels []prompbmarshal.Label) string {
|
|
for _, l := range labels {
|
|
if l.Name == "__name__" {
|
|
return l.Value
|
|
}
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func sortLabels(labels []prompbmarshal.Label) {
|
|
sort.Slice(labels, func(i, j int) bool {
|
|
return labels[i].Name < labels[j].Name
|
|
})
|
|
}
|