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3f96458782
prometheus/model/textparse/protobufparse_test.go
Piotr 3f96458782 Add reproducer for metric name label corruption 
Signed-off-by: Piotr <17101802+thampiotr@users.noreply.github.com>
2025-08-05 12:53:10 +01:00

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// Copyright 2021 The Prometheus 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 textparse
import (
"bytes"
"encoding/binary"
"errors"
"fmt"
"io"
"math/rand"
"strings"
"testing"
"github.com/gogo/protobuf/proto"
"github.com/gogo/protobuf/types"
"github.com/prometheus/common/model"
"github.com/stretchr/testify/require"
"github.com/prometheus/prometheus/model/exemplar"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/labels"
dto "github.com/prometheus/prometheus/prompb/io/prometheus/client"
"github.com/prometheus/prometheus/util/pool"
)
func createTestProtoBuf(t testing.TB) *bytes.Buffer {
t.Helper()
testMetricFamilies := []string{
`name: "go_build_info"
help: "Build information about the main Go module."
type: GAUGE
metric: <
label: <
name: "checksum"
value: ""
>
label: <
name: "path"
value: "github.com/prometheus/client_golang"
>
label: <
name: "version"
value: "(devel)"
>
gauge: <
value: 1
>
>
`,
`name: "go_memstats_alloc_bytes_total"
help: "Total number of bytes allocated, even if freed."
type: COUNTER
unit: "bytes"
metric: <
counter: <
value: 1.546544e+06
exemplar: <
label: <
name: "dummyID"
value: "42"
>
value: 12
timestamp: <
seconds: 1625851151
nanos: 233181499
>
>
>
>
`,
`name: "something_untyped"
help: "Just to test the untyped type."
type: UNTYPED
metric: <
untyped: <
value: 42
>
timestamp_ms: 1234567
>
`,
`name: "test_histogram"
help: "Test histogram with many buckets removed to keep it manageable in size."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count: 2
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count: 4
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count: 2
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_delta: 1
negative_delta: 3
negative_delta: -2
negative_delta: -1
negative_delta: 1
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_delta: 1
positive_delta: 2
positive_delta: -1
positive_delta: -1
>
timestamp_ms: 1234568
>
`,
`name: "test_gauge_histogram"
help: "Like test_histogram but as gauge histogram."
type: GAUGE_HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count: 2
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count: 4
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count: 2
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_delta: 1
negative_delta: 3
negative_delta: -2
negative_delta: -1
negative_delta: 1
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_delta: 1
positive_delta: 2
positive_delta: -1
positive_delta: -1
>
timestamp_ms: 1234568
>
`,
`name: "test_float_histogram"
help: "Test float histogram with many buckets removed to keep it manageable in size."
type: HISTOGRAM
metric: <
histogram: <
sample_count_float: 175.0
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count_float: 2.0
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count_float: 4.0
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count_float: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count_float: 2.0
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_count: 1.0
negative_count: 3.0
negative_count: -2.0
negative_count: -1.0
negative_count: 1.0
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_count: 1.0
positive_count: 2.0
positive_count: -1.0
positive_count: -1.0
>
timestamp_ms: 1234568
>
`,
`name: "test_gauge_float_histogram"
help: "Like test_float_histogram but as gauge histogram."
type: GAUGE_HISTOGRAM
metric: <
histogram: <
sample_count_float: 175.0
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count_float: 2.0
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count_float: 4.0
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count_float: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count_float: 2.0
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_count: 1.0
negative_count: 3.0
negative_count: -2.0
negative_count: -1.0
negative_count: 1.0
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_count: 1.0
positive_count: 2.0
positive_count: -1.0
positive_count: -1.0
>
timestamp_ms: 1234568
>
`,
`name: "test_histogram2"
help: "Similar histogram as before but now without sparse buckets."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.000828
bucket: <
cumulative_count: 2
upper_bound: -0.00048
>
bucket: <
cumulative_count: 4
upper_bound: -0.00038
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00038
timestamp: <
seconds: 1625851153
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 16
upper_bound: 1
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.000295
>
>
schema: 0
zero_threshold: 0
>
>
`,
`name: "test_histogram3"
help: "Similar histogram as before but now with integer buckets."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 6
sample_sum: 50
bucket: <
cumulative_count: 2
upper_bound: -20
>
bucket: <
cumulative_count: 4
upper_bound: 20
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: 15
timestamp: <
seconds: 1625851153
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 6
upper_bound: 30
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: 25
>
>
schema: 0
zero_threshold: 0
>
>
`,
`name: "test_histogram_family"
help: "Test histogram metric family with two very simple histograms."
type: HISTOGRAM
metric: <
label: <
name: "foo"
value: "bar"
>
histogram: <
sample_count: 5
sample_sum: 12.1
bucket: <
cumulative_count: 2
upper_bound: 1.1
>
bucket: <
cumulative_count: 3
upper_bound: 2.2
>
schema: 3
positive_span: <
offset: 8
length: 2
>
positive_delta: 2
positive_delta: 1
>
>
metric: <
label: <
name: "foo"
value: "baz"
>
histogram: <
sample_count: 6
sample_sum: 13.1
bucket: <
cumulative_count: 1
upper_bound: 1.1
>
bucket: <
cumulative_count: 5
upper_bound: 2.2
>
schema: 3
positive_span: <
offset: 8
length: 2
>
positive_delta: 1
positive_delta: 4
>
>
`,
`name: "test_float_histogram_with_zerothreshold_zero"
help: "Test float histogram with a zero threshold of zero."
type: HISTOGRAM
metric: <
histogram: <
sample_count_float: 5.0
sample_sum: 12.1
schema: 3
positive_span: <
offset: 8
length: 2
>
positive_count: 2.0
positive_count: 3.0
>
>
`,
`name: "rpc_durations_seconds"
help: "RPC latency distributions."
type: SUMMARY
metric: <
label: <
name: "service"
value: "exponential"
>
summary: <
sample_count: 262
sample_sum: 0.00025551262820703587
quantile: <
quantile: 0.5
value: 6.442786329648548e-07
>
quantile: <
quantile: 0.9
value: 1.9435742936658396e-06
>
quantile: <
quantile: 0.99
value: 4.0471608667037015e-06
>
>
>
`,
`name: "without_quantiles"
help: "A summary without quantiles."
type: SUMMARY
metric: <
summary: <
sample_count: 42
sample_sum: 1.234
>
>
`,
`name: "empty_histogram"
help: "A histogram without observations and with a zero threshold of zero but with a no-op span to identify it as a native histogram."
type: HISTOGRAM
metric: <
histogram: <
positive_span: <
offset: 0
length: 0
>
>
>
`,
`name: "test_counter_with_createdtimestamp"
help: "A counter with a created timestamp."
type: COUNTER
metric: <
counter: <
value: 42
created_timestamp: <
seconds: 1625851153
nanos: 146848499
>
>
>
`,
`name: "test_summary_with_createdtimestamp"
help: "A summary with a created timestamp."
type: SUMMARY
metric: <
summary: <
sample_count: 42
sample_sum: 1.234
created_timestamp: <
seconds: 1625851153
nanos: 146848499
>
>
>
`,
`name: "test_histogram_with_createdtimestamp"
help: "A histogram with a created timestamp."
type: HISTOGRAM
metric: <
histogram: <
created_timestamp: <
seconds: 1625851153
nanos: 146848499
>
positive_span: <
offset: 0
length: 0
>
>
>
`,
`name: "test_gaugehistogram_with_createdtimestamp"
help: "A gauge histogram with a created timestamp."
type: GAUGE_HISTOGRAM
metric: <
histogram: <
created_timestamp: <
seconds: 1625851153
nanos: 146848499
>
positive_span: <
offset: 0
length: 0
>
>
>
`,
`name: "test_histogram_with_native_histogram_exemplars"
help: "A histogram with native histogram exemplars."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count: 2
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count: 4
upper_bound: -0.0003899999999999998
exemplar: <
label: <
name: "dummyID"
value: "59727"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
bucket: <
cumulative_count: 16
upper_bound: -0.0002899999999999998
exemplar: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count: 2
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_delta: 1
negative_delta: 3
negative_delta: -2
negative_delta: -1
negative_delta: 1
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_delta: 1
positive_delta: 2
positive_delta: -1
positive_delta: -1
exemplars: <
label: <
name: "dummyID"
value: "59780"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
exemplars: <
label: <
name: "dummyID"
value: "5617"
>
value: -0.00029
>
exemplars: <
label: <
name: "dummyID"
value: "59772"
>
value: -0.00052
timestamp: <
seconds: 1625851160
nanos: 156848499
>
>
>
timestamp_ms: 1234568
>
`,
`name: "test_histogram_with_native_histogram_exemplars2"
help: "Another histogram with native histogram exemplars."
type: HISTOGRAM
metric: <
histogram: <
sample_count: 175
sample_sum: 0.0008280461746287094
bucket: <
cumulative_count: 2
upper_bound: -0.0004899999999999998
>
bucket: <
cumulative_count: 4
upper_bound: -0.0003899999999999998
>
bucket: <
cumulative_count: 16
upper_bound: -0.0002899999999999998
>
schema: 3
zero_threshold: 2.938735877055719e-39
zero_count: 2
negative_span: <
offset: -162
length: 1
>
negative_span: <
offset: 23
length: 4
>
negative_delta: 1
negative_delta: 3
negative_delta: -2
negative_delta: -1
negative_delta: 1
positive_span: <
offset: -161
length: 1
>
positive_span: <
offset: 8
length: 3
>
positive_delta: 1
positive_delta: 2
positive_delta: -1
positive_delta: -1
exemplars: <
label: <
name: "dummyID"
value: "59780"
>
value: -0.00039
timestamp: <
seconds: 1625851155
nanos: 146848499
>
>
>
timestamp_ms: 1234568
>
`,
}
varintBuf := make([]byte, binary.MaxVarintLen32)
buf := &bytes.Buffer{}
for _, tmf := range testMetricFamilies {
pb := &dto.MetricFamily{}
// From text to proto message.
require.NoError(t, proto.UnmarshalText(tmf, pb))
// From proto message to binary protobuf.
protoBuf, err := proto.Marshal(pb)
require.NoError(t, err)
// Write first length, then binary protobuf.
varintLength := binary.PutUvarint(varintBuf, uint64(len(protoBuf)))
buf.Write(varintBuf[:varintLength])
buf.Write(protoBuf)
}
return buf
}
func TestProtobufParse(t *testing.T) {
inputBuf := createTestProtoBuf(t)
scenarios := []struct {
name string
parser Parser
expected []parsedEntry
}{
{
name: "parseClassicHistograms=false/enableTypeAndUnitLabels=false",
parser: NewProtobufParser(inputBuf.Bytes(), false, false, labels.NewSymbolTable()),
expected: []parsedEntry{
{
m: "go_build_info",
help: "Build information about the main Go module.",
},
{
m: "go_build_info",
typ: model.MetricTypeGauge,
},
{
m: "go_build_info\xffchecksum\xff\xffpath\xffgithub.com/prometheus/client_golang\xffversion\xff(devel)",
v: 1,
lset: labels.FromStrings(
"__name__", "go_build_info",
"checksum", "",
"path", "github.com/prometheus/client_golang",
"version", "(devel)",
),
},
{
m: "go_memstats_alloc_bytes_total",
help: "Total number of bytes allocated, even if freed.",
},
{
m: "go_memstats_alloc_bytes_total",
unit: "bytes",
},
{
m: "go_memstats_alloc_bytes_total",
typ: model.MetricTypeCounter,
},
{
m: "go_memstats_alloc_bytes_total",
v: 1.546544e+06,
lset: labels.FromStrings(
"__name__", "go_memstats_alloc_bytes_total",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "42"), Value: 12, HasTs: true, Ts: 1625851151233},
},
},
{
m: "something_untyped",
help: "Just to test the untyped type.",
},
{
m: "something_untyped",
typ: model.MetricTypeUnknown,
},
{
m: "something_untyped",
t: int64p(1234567),
v: 42,
lset: labels.FromStrings(
"__name__", "something_untyped",
),
},
{
m: "test_histogram",
help: "Test histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_histogram",
help: "Like test_histogram but as gauge histogram.",
},
{
m: "test_gauge_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_histogram",
t: int64p(1234568),
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_gauge_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_float_histogram",
help: "Test float histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_float_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_float_histogram",
help: "Like test_float_histogram but as gauge histogram.",
},
{
m: "test_gauge_float_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_float_histogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram2",
help: "Similar histogram as before but now without sparse buckets.",
},
{
m: "test_histogram2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram2_count",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_count",
),
},
{
m: "test_histogram2_sum",
v: 0.000828,
lset: labels.FromStrings(
"__name__", "test_histogram2_sum",
),
},
{
m: "test_histogram2_bucket\xffle\xff-0.00048",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "-0.00048",
),
},
{
m: "test_histogram2_bucket\xffle\xff-0.00038",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "-0.00038",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00038, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram2_bucket\xffle\xff1.0",
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "1.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.000295, HasTs: false},
},
},
{
m: "test_histogram2_bucket\xffle\xff+Inf",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram3",
help: "Similar histogram as before but now with integer buckets.",
},
{
m: "test_histogram3",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram3_count",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_count",
),
},
{
m: "test_histogram3_sum",
v: 50,
lset: labels.FromStrings(
"__name__", "test_histogram3_sum",
),
},
{
m: "test_histogram3_bucket\xffle\xff-20.0",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "-20.0",
),
},
{
m: "test_histogram3_bucket\xffle\xff20.0",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "20.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: 15, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram3_bucket\xffle\xff30.0",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "30.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: 25, HasTs: false},
},
},
{
m: "test_histogram3_bucket\xffle\xff+Inf",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram_family",
help: "Test histogram metric family with two very simple histograms.",
},
{
m: "test_histogram_family",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_family\xfffoo\xffbar",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 5,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{2, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"foo", "bar",
),
},
{
m: "test_histogram_family\xfffoo\xffbaz",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 6,
Sum: 13.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{1, 4},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"foo", "baz",
),
},
{
m: "test_float_histogram_with_zerothreshold_zero",
help: "Test float histogram with a zero threshold of zero.",
},
{
m: "test_float_histogram_with_zerothreshold_zero",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram_with_zerothreshold_zero",
fhs: &histogram.FloatHistogram{
Count: 5.0,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
PositiveBuckets: []float64{2.0, 3.0},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram_with_zerothreshold_zero",
),
},
{
m: "rpc_durations_seconds",
help: "RPC latency distributions.",
},
{
m: "rpc_durations_seconds",
typ: model.MetricTypeSummary,
},
{
m: "rpc_durations_seconds_count\xffservice\xffexponential",
v: 262,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_count",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds_sum\xffservice\xffexponential",
v: 0.00025551262820703587,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_sum",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.5\xffservice\xffexponential",
v: 6.442786329648548e-07,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.5",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.9\xffservice\xffexponential",
v: 1.9435742936658396e-06,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.9",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.99\xffservice\xffexponential",
v: 4.0471608667037015e-06,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.99",
"service", "exponential",
),
},
{
m: "without_quantiles",
help: "A summary without quantiles.",
},
{
m: "without_quantiles",
typ: model.MetricTypeSummary,
},
{
m: "without_quantiles_count",
v: 42,
lset: labels.FromStrings(
"__name__", "without_quantiles_count",
),
},
{
m: "without_quantiles_sum",
v: 1.234,
lset: labels.FromStrings(
"__name__", "without_quantiles_sum",
),
},
{
m: "empty_histogram",
help: "A histogram without observations and with a zero threshold of zero but with a no-op span to identify it as a native histogram.",
},
{
m: "empty_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "empty_histogram",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "empty_histogram",
),
},
{
m: "test_counter_with_createdtimestamp",
help: "A counter with a created timestamp.",
},
{
m: "test_counter_with_createdtimestamp",
typ: model.MetricTypeCounter,
},
{
m: "test_counter_with_createdtimestamp",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_counter_with_createdtimestamp",
),
},
{
m: "test_summary_with_createdtimestamp",
help: "A summary with a created timestamp.",
},
{
m: "test_summary_with_createdtimestamp",
typ: model.MetricTypeSummary,
},
{
m: "test_summary_with_createdtimestamp_count",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_count",
),
},
{
m: "test_summary_with_createdtimestamp_sum",
v: 1.234,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_sum",
),
},
{
m: "test_histogram_with_createdtimestamp",
help: "A histogram with a created timestamp.",
},
{
m: "test_histogram_with_createdtimestamp",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_createdtimestamp",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_createdtimestamp",
),
},
{
m: "test_gaugehistogram_with_createdtimestamp",
help: "A gauge histogram with a created timestamp.",
},
{
m: "test_gaugehistogram_with_createdtimestamp",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gaugehistogram_with_createdtimestamp",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_gaugehistogram_with_createdtimestamp",
),
},
{
m: "test_histogram_with_native_histogram_exemplars",
help: "A histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
{Labels: labels.FromStrings("dummyID", "59772"), Value: -0.00052, HasTs: true, Ts: 1625851160156},
},
},
{
m: "test_histogram_with_native_histogram_exemplars2",
help: "Another histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars2",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
},
},
{
name: "parseClassicHistograms=false/enableTypeAndUnitLabels=true",
parser: NewProtobufParser(inputBuf.Bytes(), false, true, labels.NewSymbolTable()),
expected: []parsedEntry{
{
m: "go_build_info",
help: "Build information about the main Go module.",
},
{
m: "go_build_info",
typ: model.MetricTypeGauge,
},
{
m: "go_build_info\xff__type__\xffgauge\xffchecksum\xff\xffpath\xffgithub.com/prometheus/client_golang\xffversion\xff(devel)",
v: 1,
lset: labels.FromStrings(
"__name__", "go_build_info",
"__type__", string(model.MetricTypeGauge),
"checksum", "",
"path", "github.com/prometheus/client_golang",
"version", "(devel)",
),
},
{
m: "go_memstats_alloc_bytes_total",
help: "Total number of bytes allocated, even if freed.",
},
{
m: "go_memstats_alloc_bytes_total",
unit: "bytes",
},
{
m: "go_memstats_alloc_bytes_total",
typ: model.MetricTypeCounter,
},
{
m: "go_memstats_alloc_bytes_total\xff__type__\xffcounter\xff__unit__\xffbytes",
v: 1.546544e+06,
lset: labels.FromStrings(
"__name__", "go_memstats_alloc_bytes_total",
"__type__", string(model.MetricTypeCounter),
"__unit__", "bytes",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "42"), Value: 12, HasTs: true, Ts: 1625851151233},
},
},
{
m: "something_untyped",
help: "Just to test the untyped type.",
},
{
m: "something_untyped",
typ: model.MetricTypeUnknown,
},
{
m: "something_untyped",
t: int64p(1234567),
v: 42,
lset: labels.FromStrings(
"__name__", "something_untyped",
),
},
{
m: "test_histogram",
help: "Test histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram\xff__type__\xffhistogram",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram",
"__type__", string(model.MetricTypeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_histogram",
help: "Like test_histogram but as gauge histogram.",
},
{
m: "test_gauge_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_histogram\xff__type__\xffgaugehistogram",
t: int64p(1234568),
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_gauge_histogram",
"__type__", string(model.MetricTypeGaugeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_float_histogram",
help: "Test float histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_float_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram\xff__type__\xffhistogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram",
"__type__", string(model.MetricTypeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_float_histogram",
help: "Like test_float_histogram but as gauge histogram.",
},
{
m: "test_gauge_float_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_float_histogram\xff__type__\xffgaugehistogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram",
"__type__", string(model.MetricTypeGaugeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram2",
help: "Similar histogram as before but now without sparse buckets.",
},
{
m: "test_histogram2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram2_count\xff__type__\xffhistogram",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_count",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_histogram2_sum\xff__type__\xffhistogram",
v: 0.000828,
lset: labels.FromStrings(
"__name__", "test_histogram2_sum",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_histogram2_bucket\xff__type__\xffhistogram\xffle\xff-0.00048",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "-0.00048",
),
},
{
m: "test_histogram2_bucket\xff__type__\xffhistogram\xffle\xff-0.00038",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "-0.00038",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00038, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram2_bucket\xff__type__\xffhistogram\xffle\xff1.0",
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "1.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.000295, HasTs: false},
},
},
{
m: "test_histogram2_bucket\xff__type__\xffhistogram\xffle\xff+Inf",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "+Inf",
),
},
{
m: "test_histogram3",
help: "Similar histogram as before but now with integer buckets.",
},
{
m: "test_histogram3",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram3_count\xff__type__\xffhistogram",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_count",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_histogram3_sum\xff__type__\xffhistogram",
v: 50,
lset: labels.FromStrings(
"__name__", "test_histogram3_sum",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_histogram3_bucket\xff__type__\xffhistogram\xffle\xff-20.0",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "-20.0",
),
},
{
m: "test_histogram3_bucket\xff__type__\xffhistogram\xffle\xff20.0",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "20.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: 15, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram3_bucket\xff__type__\xffhistogram\xffle\xff30.0",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "30.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: 25, HasTs: false},
},
},
{
m: "test_histogram3_bucket\xff__type__\xffhistogram\xffle\xff+Inf",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"__type__", string(model.MetricTypeHistogram),
"le", "+Inf",
),
},
{
m: "test_histogram_family",
help: "Test histogram metric family with two very simple histograms.",
},
{
m: "test_histogram_family",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_family\xff__type__\xffhistogram\xfffoo\xffbar",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 5,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{2, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"__type__", string(model.MetricTypeHistogram),
"foo", "bar",
),
},
{
m: "test_histogram_family\xff__type__\xffhistogram\xfffoo\xffbaz",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 6,
Sum: 13.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{1, 4},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"__type__", string(model.MetricTypeHistogram),
"foo", "baz",
),
},
{
m: "test_float_histogram_with_zerothreshold_zero",
help: "Test float histogram with a zero threshold of zero.",
},
{
m: "test_float_histogram_with_zerothreshold_zero",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram_with_zerothreshold_zero\xff__type__\xffhistogram",
fhs: &histogram.FloatHistogram{
Count: 5.0,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
PositiveBuckets: []float64{2.0, 3.0},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram_with_zerothreshold_zero",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "rpc_durations_seconds",
help: "RPC latency distributions.",
},
{
m: "rpc_durations_seconds",
typ: model.MetricTypeSummary,
},
{
m: "rpc_durations_seconds_count\xff__type__\xffsummary\xffservice\xffexponential",
v: 262,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_count",
"__type__", string(model.MetricTypeSummary),
"service", "exponential",
),
},
{
m: "rpc_durations_seconds_sum\xff__type__\xffsummary\xffservice\xffexponential",
v: 0.00025551262820703587,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_sum",
"__type__", string(model.MetricTypeSummary),
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xff__type__\xffsummary\xffquantile\xff0.5\xffservice\xffexponential",
v: 6.442786329648548e-07,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"__type__", string(model.MetricTypeSummary),
"quantile", "0.5",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xff__type__\xffsummary\xffquantile\xff0.9\xffservice\xffexponential",
v: 1.9435742936658396e-06,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"__type__", string(model.MetricTypeSummary),
"quantile", "0.9",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xff__type__\xffsummary\xffquantile\xff0.99\xffservice\xffexponential",
v: 4.0471608667037015e-06,
lset: labels.FromStrings(
"__type__", string(model.MetricTypeSummary),
"__name__", "rpc_durations_seconds",
"quantile", "0.99",
"service", "exponential",
),
},
{
m: "without_quantiles",
help: "A summary without quantiles.",
},
{
m: "without_quantiles",
typ: model.MetricTypeSummary,
},
{
m: "without_quantiles_count\xff__type__\xffsummary",
v: 42,
lset: labels.FromStrings(
"__name__", "without_quantiles_count",
"__type__", string(model.MetricTypeSummary),
),
},
{
m: "without_quantiles_sum\xff__type__\xffsummary",
v: 1.234,
lset: labels.FromStrings(
"__name__", "without_quantiles_sum",
"__type__", string(model.MetricTypeSummary),
),
},
{
m: "empty_histogram",
help: "A histogram without observations and with a zero threshold of zero but with a no-op span to identify it as a native histogram.",
},
{
m: "empty_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "empty_histogram\xff__type__\xffhistogram",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "empty_histogram",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_counter_with_createdtimestamp",
help: "A counter with a created timestamp.",
},
{
m: "test_counter_with_createdtimestamp",
typ: model.MetricTypeCounter,
},
{
m: "test_counter_with_createdtimestamp\xff__type__\xffcounter",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_counter_with_createdtimestamp",
"__type__", string(model.MetricTypeCounter),
),
},
{
m: "test_summary_with_createdtimestamp",
help: "A summary with a created timestamp.",
},
{
m: "test_summary_with_createdtimestamp",
typ: model.MetricTypeSummary,
},
{
m: "test_summary_with_createdtimestamp_count\xff__type__\xffsummary",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_count",
"__type__", string(model.MetricTypeSummary),
),
},
{
m: "test_summary_with_createdtimestamp_sum\xff__type__\xffsummary",
v: 1.234,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_sum",
"__type__", string(model.MetricTypeSummary),
),
},
{
m: "test_histogram_with_createdtimestamp",
help: "A histogram with a created timestamp.",
},
{
m: "test_histogram_with_createdtimestamp",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_createdtimestamp\xff__type__\xffhistogram",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_createdtimestamp",
"__type__", string(model.MetricTypeHistogram),
),
},
{
m: "test_gaugehistogram_with_createdtimestamp",
help: "A gauge histogram with a created timestamp.",
},
{
m: "test_gaugehistogram_with_createdtimestamp",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gaugehistogram_with_createdtimestamp\xff__type__\xffgaugehistogram",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_gaugehistogram_with_createdtimestamp",
"__type__", string(model.MetricTypeGaugeHistogram),
),
},
{
m: "test_histogram_with_native_histogram_exemplars",
help: "A histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars\xff__type__\xffhistogram",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars",
"__type__", string(model.MetricTypeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
{Labels: labels.FromStrings("dummyID", "59772"), Value: -0.00052, HasTs: true, Ts: 1625851160156},
},
},
{
m: "test_histogram_with_native_histogram_exemplars2",
help: "Another histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars2\xff__type__\xffhistogram",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2",
"__type__", string(model.MetricTypeHistogram),
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
},
},
{
name: "parseClassicHistograms=true/enableTypeAndUnitLabels=false",
parser: NewProtobufParser(inputBuf.Bytes(), true, false, labels.NewSymbolTable()),
expected: []parsedEntry{
{
m: "go_build_info",
help: "Build information about the main Go module.",
},
{
m: "go_build_info",
typ: model.MetricTypeGauge,
},
{
m: "go_build_info\xffchecksum\xff\xffpath\xffgithub.com/prometheus/client_golang\xffversion\xff(devel)",
v: 1,
lset: labels.FromStrings(
"__name__", "go_build_info",
"checksum", "",
"path", "github.com/prometheus/client_golang",
"version", "(devel)",
),
},
{
m: "go_memstats_alloc_bytes_total",
help: "Total number of bytes allocated, even if freed.",
},
{
m: "go_memstats_alloc_bytes_total",
unit: "bytes",
},
{
m: "go_memstats_alloc_bytes_total",
typ: model.MetricTypeCounter,
},
{
m: "go_memstats_alloc_bytes_total",
v: 1.546544e+06,
lset: labels.FromStrings(
"__name__", "go_memstats_alloc_bytes_total",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "42"), Value: 12, HasTs: true, Ts: 1625851151233},
},
},
{
m: "something_untyped",
help: "Just to test the untyped type.",
},
{
m: "something_untyped",
typ: model.MetricTypeUnknown,
},
{
m: "something_untyped",
t: int64p(1234567),
v: 42,
lset: labels.FromStrings(
"__name__", "something_untyped",
),
},
{
m: "test_histogram",
help: "Test histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_count",
),
},
{
m: "test_histogram_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_histogram_sum",
),
},
{
m: "test_histogram_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_histogram_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram_bucket",
"le", "-0.0003899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram_bucket",
"le", "-0.0002899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, HasTs: false},
},
},
{
m: "test_histogram_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_bucket",
"le", "+Inf",
),
},
{
m: "test_gauge_histogram",
help: "Like test_histogram but as gauge histogram.",
},
{
m: "test_gauge_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_histogram",
t: int64p(1234568),
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_gauge_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_histogram_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_count",
),
},
{
m: "test_gauge_histogram_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_sum",
),
},
{
m: "test_gauge_histogram_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_gauge_histogram_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_bucket",
"le", "-0.0003899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_histogram_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_bucket",
"le", "-0.0002899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, HasTs: false},
},
},
{
m: "test_gauge_histogram_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_gauge_histogram_bucket",
"le", "+Inf",
),
},
{
m: "test_float_histogram",
help: "Test float histogram with many buckets removed to keep it manageable in size.",
},
{
m: "test_float_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_float_histogram_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_float_histogram_count",
),
},
{
m: "test_float_histogram_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_float_histogram_sum",
),
},
{
m: "test_float_histogram_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_float_histogram_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_float_histogram_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_float_histogram_bucket",
"le", "-0.0003899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_float_histogram_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_float_histogram_bucket",
"le", "-0.0002899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, HasTs: false},
},
},
{
m: "test_float_histogram_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_float_histogram_bucket",
"le", "+Inf",
),
},
{
m: "test_gauge_float_histogram",
help: "Like test_float_histogram but as gauge histogram.",
},
{
m: "test_gauge_float_histogram",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gauge_float_histogram",
t: int64p(1234568),
fhs: &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Count: 175.0,
ZeroCount: 2.0,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []float64{1.0, 2.0, -1.0, -1.0},
NegativeBuckets: []float64{1.0, 3.0, -2.0, -1.0, 1.0},
},
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_float_histogram_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_count",
),
},
{
m: "test_gauge_float_histogram_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_sum",
),
},
{
m: "test_gauge_float_histogram_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_gauge_float_histogram_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_bucket",
"le", "-0.0003899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_gauge_float_histogram_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_bucket",
"le", "-0.0002899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, HasTs: false},
},
},
{
m: "test_gauge_float_histogram_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_gauge_float_histogram_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram2",
help: "Similar histogram as before but now without sparse buckets.",
},
{
m: "test_histogram2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram2_count",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_count",
),
},
{
m: "test_histogram2_sum",
v: 0.000828,
lset: labels.FromStrings(
"__name__", "test_histogram2_sum",
),
},
{
m: "test_histogram2_bucket\xffle\xff-0.00048",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "-0.00048",
),
},
{
m: "test_histogram2_bucket\xffle\xff-0.00038",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "-0.00038",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00038, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram2_bucket\xffle\xff1.0",
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "1.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.000295, HasTs: false},
},
},
{
m: "test_histogram2_bucket\xffle\xff+Inf",
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram2_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram3",
help: "Similar histogram as before but now with integer buckets.",
},
{
m: "test_histogram3",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram3_count",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_count",
),
},
{
m: "test_histogram3_sum",
v: 50,
lset: labels.FromStrings(
"__name__", "test_histogram3_sum",
),
},
{
m: "test_histogram3_bucket\xffle\xff-20.0",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "-20.0",
),
},
{
m: "test_histogram3_bucket\xffle\xff20.0",
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "20.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: 15, HasTs: true, Ts: 1625851153146},
},
},
{
m: "test_histogram3_bucket\xffle\xff30.0",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "30.0",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: 25, HasTs: false},
},
},
{
m: "test_histogram3_bucket\xffle\xff+Inf",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram3_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram_family",
help: "Test histogram metric family with two very simple histograms.",
},
{
m: "test_histogram_family",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_family\xfffoo\xffbar",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 5,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{2, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"foo", "bar",
),
},
{
m: "test_histogram_family_count\xfffoo\xffbar",
v: 5,
lset: labels.FromStrings(
"__name__", "test_histogram_family_count",
"foo", "bar",
),
},
{
m: "test_histogram_family_sum\xfffoo\xffbar",
v: 12.1,
lset: labels.FromStrings(
"__name__", "test_histogram_family_sum",
"foo", "bar",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbar\xffle\xff1.1",
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "bar",
"le", "1.1",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbar\xffle\xff2.2",
v: 3,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "bar",
"le", "2.2",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbar\xffle\xff+Inf",
v: 5,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "bar",
"le", "+Inf",
),
},
{
m: "test_histogram_family\xfffoo\xffbaz",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
Count: 6,
Sum: 13.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
NegativeSpans: []histogram.Span{},
PositiveBuckets: []int64{1, 4},
},
lset: labels.FromStrings(
"__name__", "test_histogram_family",
"foo", "baz",
),
},
{
m: "test_histogram_family_count\xfffoo\xffbaz",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram_family_count",
"foo", "baz",
),
},
{
m: "test_histogram_family_sum\xfffoo\xffbaz",
v: 13.1,
lset: labels.FromStrings(
"__name__", "test_histogram_family_sum",
"foo", "baz",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbaz\xffle\xff1.1",
v: 1,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "baz",
"le", "1.1",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbaz\xffle\xff2.2",
v: 5,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "baz",
"le", "2.2",
),
},
{
m: "test_histogram_family_bucket\xfffoo\xffbaz\xffle\xff+Inf",
v: 6,
lset: labels.FromStrings(
"__name__", "test_histogram_family_bucket",
"foo", "baz",
"le", "+Inf",
),
},
{
m: "test_float_histogram_with_zerothreshold_zero",
help: "Test float histogram with a zero threshold of zero.",
},
{
m: "test_float_histogram_with_zerothreshold_zero",
typ: model.MetricTypeHistogram,
},
{
m: "test_float_histogram_with_zerothreshold_zero",
fhs: &histogram.FloatHistogram{
Count: 5.0,
Sum: 12.1,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 8, Length: 2},
},
PositiveBuckets: []float64{2.0, 3.0},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_float_histogram_with_zerothreshold_zero",
),
},
{
m: "rpc_durations_seconds",
help: "RPC latency distributions.",
},
{
m: "rpc_durations_seconds",
typ: model.MetricTypeSummary,
},
{
m: "rpc_durations_seconds_count\xffservice\xffexponential",
v: 262,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_count",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds_sum\xffservice\xffexponential",
v: 0.00025551262820703587,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds_sum",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.5\xffservice\xffexponential",
v: 6.442786329648548e-07,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.5",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.9\xffservice\xffexponential",
v: 1.9435742936658396e-06,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.9",
"service", "exponential",
),
},
{
m: "rpc_durations_seconds\xffquantile\xff0.99\xffservice\xffexponential",
v: 4.0471608667037015e-06,
lset: labels.FromStrings(
"__name__", "rpc_durations_seconds",
"quantile", "0.99",
"service", "exponential",
),
},
{
m: "without_quantiles",
help: "A summary without quantiles.",
},
{
m: "without_quantiles",
typ: model.MetricTypeSummary,
},
{
m: "without_quantiles_count",
v: 42,
lset: labels.FromStrings(
"__name__", "without_quantiles_count",
),
},
{
m: "without_quantiles_sum",
v: 1.234,
lset: labels.FromStrings(
"__name__", "without_quantiles_sum",
),
},
{
m: "empty_histogram",
help: "A histogram without observations and with a zero threshold of zero but with a no-op span to identify it as a native histogram.",
},
{
m: "empty_histogram",
typ: model.MetricTypeHistogram,
},
{
m: "empty_histogram",
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "empty_histogram",
),
},
{
m: "test_counter_with_createdtimestamp",
help: "A counter with a created timestamp.",
},
{
m: "test_counter_with_createdtimestamp",
typ: model.MetricTypeCounter,
},
{
m: "test_counter_with_createdtimestamp",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_counter_with_createdtimestamp",
),
},
{
m: "test_summary_with_createdtimestamp",
help: "A summary with a created timestamp.",
},
{
m: "test_summary_with_createdtimestamp",
typ: model.MetricTypeSummary,
},
{
m: "test_summary_with_createdtimestamp_count",
v: 42,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_count",
),
},
{
m: "test_summary_with_createdtimestamp_sum",
v: 1.234,
ct: 1625851153146,
lset: labels.FromStrings(
"__name__", "test_summary_with_createdtimestamp_sum",
),
},
{
m: "test_histogram_with_createdtimestamp",
help: "A histogram with a created timestamp.",
},
{
m: "test_histogram_with_createdtimestamp",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_createdtimestamp",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.UnknownCounterReset,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_createdtimestamp",
),
},
{
m: "test_gaugehistogram_with_createdtimestamp",
help: "A gauge histogram with a created timestamp.",
},
{
m: "test_gaugehistogram_with_createdtimestamp",
typ: model.MetricTypeGaugeHistogram,
},
{
m: "test_gaugehistogram_with_createdtimestamp",
ct: 1625851153146,
shs: &histogram.Histogram{
CounterResetHint: histogram.GaugeType,
PositiveSpans: []histogram.Span{},
NegativeSpans: []histogram.Span{},
},
lset: labels.FromStrings(
"__name__", "test_gaugehistogram_with_createdtimestamp",
),
},
{
m: "test_histogram_with_native_histogram_exemplars",
help: "A histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
{Labels: labels.FromStrings("dummyID", "59772"), Value: -0.00052, HasTs: true, Ts: 1625851160156},
},
},
{
m: "test_histogram_with_native_histogram_exemplars_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_count",
),
},
{
m: "test_histogram_with_native_histogram_exemplars_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_sum",
),
},
{
m: "test_histogram_with_native_histogram_exemplars_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_histogram_with_native_histogram_exemplars_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_bucket",
"le", "-0.0003899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59727"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram_with_native_histogram_exemplars_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_bucket",
"le", "-0.0002899999999999998",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "5617"), Value: -0.00029, HasTs: false},
},
},
{
m: "test_histogram_with_native_histogram_exemplars_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars_bucket",
"le", "+Inf",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2",
help: "Another histogram with native histogram exemplars.",
},
{
m: "test_histogram_with_native_histogram_exemplars2",
typ: model.MetricTypeHistogram,
},
{
m: "test_histogram_with_native_histogram_exemplars2",
t: int64p(1234568),
shs: &histogram.Histogram{
Count: 175,
ZeroCount: 2,
Sum: 0.0008280461746287094,
ZeroThreshold: 2.938735877055719e-39,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -161, Length: 1},
{Offset: 8, Length: 3},
},
NegativeSpans: []histogram.Span{
{Offset: -162, Length: 1},
{Offset: 23, Length: 4},
},
PositiveBuckets: []int64{1, 2, -1, -1},
NegativeBuckets: []int64{1, 3, -2, -1, 1},
},
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2",
),
es: []exemplar.Exemplar{
{Labels: labels.FromStrings("dummyID", "59780"), Value: -0.00039, HasTs: true, Ts: 1625851155146},
},
},
{
m: "test_histogram_with_native_histogram_exemplars2_count",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_count",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2_sum",
t: int64p(1234568),
v: 0.0008280461746287094,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_sum",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2_bucket\xffle\xff-0.0004899999999999998",
t: int64p(1234568),
v: 2,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_bucket",
"le", "-0.0004899999999999998",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2_bucket\xffle\xff-0.0003899999999999998",
t: int64p(1234568),
v: 4,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_bucket",
"le", "-0.0003899999999999998",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2_bucket\xffle\xff-0.0002899999999999998",
t: int64p(1234568),
v: 16,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_bucket",
"le", "-0.0002899999999999998",
),
},
{
m: "test_histogram_with_native_histogram_exemplars2_bucket\xffle\xff+Inf",
t: int64p(1234568),
v: 175,
lset: labels.FromStrings(
"__name__", "test_histogram_with_native_histogram_exemplars2_bucket",
"le", "+Inf",
),
},
},
},
}
for _, scenario := range scenarios {
t.Run(scenario.name, func(t *testing.T) {
var (
p = scenario.parser
exp = scenario.expected
)
got := testParse(t, p)
requireEntries(t, exp, got)
})
}
}
func FuzzProtobufParser_Labels(f *testing.F) {
// Add to the "seed corpus" the values that are known to reproduce issues
// which this test has found in the past. These cases run during regular
// testing, as well as the first step of the fuzzing process.
f.Add(true, true, int64(123))
f.Add(true, false, int64(129))
f.Add(false, true, int64(159))
f.Add(false, true, int64(-127))
f.Fuzz(func(
t *testing.T,
parseClassicHistogram bool,
enableTypeAndUnitLabels bool,
randSeed int64,
) {
var (
r = rand.New(rand.NewSource(randSeed))
buffers = pool.New(1+r.Intn(128), 128+r.Intn(1024), 2, func(sz int) interface{} { return make([]byte, 0, sz) })
lastScrapeSize = 0
observedLabels []labels.Labels
st = labels.NewSymbolTable()
)
for i := 0; i < 20; i++ { // run multiple iterations to encounter memory corruptions
// Get buffer from pool like in scrape.go
b := buffers.Get(lastScrapeSize).([]byte)
buf := bytes.NewBuffer(b)
// Generate some scraped data to parse
mf := generateFuzzMetricFamily(r)
protoBuf, err := proto.Marshal(mf)
require.NoError(t, err)
sizeBuf := make([]byte, binary.MaxVarintLen32)
sizeBufSize := binary.PutUvarint(sizeBuf, uint64(len(protoBuf)))
buf.Write(sizeBuf[:sizeBufSize])
buf.Write(protoBuf)
// Use protobuf parser to parse like in real usage
b = buf.Bytes()
p := NewProtobufParser(b, parseClassicHistogram, enableTypeAndUnitLabels, st)
for {
entry, err := p.Next()
if errors.Is(err, io.EOF) {
break
}
require.NoError(t, err)
switch entry {
case EntryHelp:
name, help := p.Help()
require.Equal(t, mf.Name, string(name))
require.Equal(t, mf.Help, string(help))
case EntryType:
name, _ := p.Type()
require.Equal(t, mf.Name, string(name))
case EntryUnit:
name, unit := p.Unit()
require.Equal(t, mf.Name, string(name))
require.Equal(t, mf.Unit, string(unit))
case EntrySeries, EntryHistogram:
var lbs labels.Labels
p.Labels(&lbs)
observedLabels = append(observedLabels, lbs)
}
// Get labels from exemplars
for {
var e exemplar.Exemplar
if !p.Exemplar(&e) {
break
}
observedLabels = append(observedLabels, e.Labels)
}
}
// Validate all labels seen so far remain valid. This can find memory corruption issues.
for _, l := range observedLabels {
require.True(t, l.IsValid(model.LegacyValidation), "encountered corrupted labels: %v", l)
}
lastScrapeSize = len(b)
buffers.Put(b)
}
})
}
func generateFuzzMetricFamily(
r *rand.Rand,
) *dto.MetricFamily {
unit := generateValidLabelName(r)
metricName := fmt.Sprintf("%s_%s", generateValidMetricName(r), unit)
metricTypeProto := dto.MetricType(r.Intn(len(dto.MetricType_name)))
metricFamily := &dto.MetricFamily{
Name: metricName,
Help: generateHelp(r),
Type: metricTypeProto,
Unit: unit,
}
metricsCount := r.Intn(20)
for i := 0; i < metricsCount; i++ {
metric := dto.Metric{
Label: generateFuzzLabels(r),
}
switch metricTypeProto {
case dto.MetricType_GAUGE:
metric.Gauge = &dto.Gauge{Value: r.Float64()}
case dto.MetricType_COUNTER:
metric.Counter = &dto.Counter{Value: r.Float64()}
case dto.MetricType_SUMMARY:
metric.Summary = &dto.Summary{Quantile: []dto.Quantile{{Quantile: 0.5, Value: r.Float64()}}}
case dto.MetricType_HISTOGRAM:
metric.Histogram = &dto.Histogram{Exemplars: generateExemplars(r)}
}
metricFamily.Metric = append(metricFamily.Metric, metric)
}
return metricFamily
}
func generateExemplars(r *rand.Rand) []*dto.Exemplar {
exemplarsCount := r.Intn(5)
exemplars := make([]*dto.Exemplar, 0, exemplarsCount)
for i := 0; i < exemplarsCount; i++ {
exemplars = append(exemplars, &dto.Exemplar{
Label: generateFuzzLabels(r),
Value: r.Float64(),
Timestamp: &types.Timestamp{
Seconds: int64(r.Intn(1000000000)),
Nanos: int32(r.Intn(1000000000)),
},
})
}
return exemplars
}
func generateFuzzLabels(r *rand.Rand) []dto.LabelPair {
labelsCount := r.Intn(10)
ls := make([]dto.LabelPair, 0, labelsCount)
for i := 0; i < labelsCount; i++ {
ls = append(ls, dto.LabelPair{
Name: generateValidLabelName(r),
Value: generateValidLabelName(r),
})
}
return ls
}
func generateHelp(r *rand.Rand) string {
result := make([]string, 1+r.Intn(20))
for i := 0; i < len(result); i++ {
result[i] = generateValidLabelName(r)
}
return strings.Join(result, "_")
}
func generateValidLabelName(r *rand.Rand) string {
return generateString(r, validFirstRunes, validLabelNameRunes)
}
func generateValidMetricName(r *rand.Rand) string {
return generateString(r, validFirstRunes, validMetricNameRunes)
}
func generateString(r *rand.Rand, firstRunes, restRunes []rune) string {
result := make([]rune, 1+r.Intn(20))
for i := range result {
if i == 0 {
result[i] = firstRunes[r.Intn(len(firstRunes))]
} else {
result[i] = restRunes[r.Intn(len(restRunes))]
}
}
return string(result)
}
var (
validMetricNameRunes = []rune{
'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z',
'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z',
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9',
'_', ':',
}
validLabelNameRunes = validMetricNameRunes[:len(validMetricNameRunes)-1] // skip the colon
validFirstRunes = validMetricNameRunes[:52] // only the letters
)
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