VictoriaMetrics/lib/protoparser/opentelemetry/stream/streamparser_test.go
Nikolay 46ecbbea26
lib/protoparser: adds opentelemetry parser (#2570)
* lib/protoparser: adds opentelemetry parser
app/{vmagent,vminsert}: adds opentelemetry ingestion path

Adds ability to ingest data with opentelemetry protocol
protobuf and json encoding is supported
data converted into prometheus protobuf timeseries
each data type has own converter and it may produce multiple timeseries
from single datapoint (for summary and histogram).
only cumulative aggregationFamily is supported for sum(prometheus
counter) and histogram.

Apply suggestions from code review

Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>

updates deps

fixes tests

wip

wip

wip

wip

lib/protoparser/opentelemetry: moves to vtprotobuf generator

go mod vendor

lib/protoparse/opentelemetry: reduce memory allocations

* wip

- Remove support for JSON parsing, since it is too fragile and is rarely used in practice.
  The most clients send OpenTelemetry metrics in protobuf.
  The JSON parser can be added in the future if needed.
- Remove unused code from lib/protoparser/opentelemetry/pb and lib/protoparser/opentelemetry/proto
- Do not re-use protobuf message between ParseStream() calls, since there is high chance
  of high fragmentation of the re-used message because of too complex nested structure of the message.

* wip

* wip

* wip

---------

Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-27 13:26:45 -07:00

317 lines
8.7 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) {
t.Helper()
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, err := req.MarshalVT()
if err != nil {
t.Fatalf("cannot marshal to protobuf: %s", err)
}
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"),
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")),
})
// Test gauge
f(
[]*pb.Metric{
generateGauge("my-gauge"),
},
[]prompbmarshal.TimeSeries{
newPromPBTs("my-gauge", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
},
)
}
func checkParseStream(data []byte, checkSeries func(tss []prompbmarshal.TimeSeries) error) error {
// Verify parsing without compression
if err := ParseStream(bytes.NewBuffer(data), false, 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: %s", err)
}
if err := zw.Close(); err != nil {
return fmt.Errorf("cannot close gzip writer: %s", err)
}
if err := ParseStream(&bb, true, 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{
Value: &pb.AnyValue_StringValue{
StringValue: v,
},
},
},
}
}
func generateGauge(name string) *pb.Metric {
points := []*pb.NumberDataPoint{
{
Attributes: attributesFromKV("label1", "value1"),
Value: &pb.NumberDataPoint_AsInt{AsInt: 15},
TimeUnixNano: uint64(15 * time.Second),
},
}
return &pb.Metric{
Name: name,
Data: &pb.Metric_Gauge{
Gauge: &pb.Gauge{
DataPoints: points,
},
},
}
}
func generateHistogram(name 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,
Data: &pb.Metric_Histogram{
Histogram: &pb.Histogram{
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE,
DataPoints: points,
},
},
}
}
func generateSum(name string) *pb.Metric {
points := []*pb.NumberDataPoint{
{
Attributes: attributesFromKV("label5", "value5"),
Value: &pb.NumberDataPoint_AsDouble{AsDouble: 15.5},
TimeUnixNano: uint64(150 * time.Second),
},
}
return &pb.Metric{
Name: name,
Data: &pb.Metric_Sum{
Sum: &pb.Sum{
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE,
DataPoints: points,
},
},
}
}
func generateSummary(name string) *pb.Metric {
points := []*pb.SummaryDataPoint{
{
Attributes: attributesFromKV("label6", "value6"),
TimeUnixNano: uint64(35 * time.Second),
Sum: 32.5,
Count: 5,
QuantileValues: []*pb.SummaryDataPoint_ValueAtQuantile{
{
Quantile: 0.1,
Value: 7.5,
},
{
Quantile: 0.5,
Value: 10.0,
},
{
Quantile: 1.0,
Value: 15.0,
},
},
},
}
return &pb.Metric{
Name: name,
Data: &pb.Metric_Summary{
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
})
}