github-mirrors/VictoriaMetrics
1
0
Fork 0
mirror of https://github.com/VictoriaMetrics/VictoriaMetrics.git synced 2024-11-21 14:44:00 +00:00
Code Issues Projects Releases Packages Wiki Activity

lib/protoparser/opentelemetry: use github.com/VictoriaMetrics/easyproto for protobuf message unmarshaling and marshaling

Browse source 
This reduces VictoriaMetrics binary size by 100KB.

Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/2570
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2424
This commit is contained in:
Aliaksandr Valialkin 2024-01-14 21:17:37 +02:00
parent 0597718435
commit dd25049858
No known key found for this signature in database
GPG key ID: 52C003EE2BCDB9EB
19 changed files with 1030 additions and 7588 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

1
lib/protoparser/opentelemetry/pb/README.md Normal file
View file

@ -0,0 +1 @@
The original protobuf definition is located at https://github.com/open-telemetry/opentelemetry-proto/tree/34d29fe5ad4689b5db0259d3750de2bfa195bc85/opentelemetry/proto

120
lib/protoparser/opentelemetry/pb/common.pb.go
View file

@ -1,120 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.12
// source: lib/protoparser/opentelemetry/proto/common.proto
package pb
// AnyValue is used to represent any type of attribute value. AnyValue may contain a
// primitive value such as a string or integer or it may contain an arbitrary nested
// object containing arrays, key-value lists and primitives.
type AnyValue struct {
unknownFields []byte
// The value is one of the listed fields. It is valid for all values to be unspecified
// in which case this AnyValue is considered to be "empty".
//
// Types that are assignable to Value:
//
// *AnyValue_StringValue
// *AnyValue_BoolValue
// *AnyValue_IntValue
// *AnyValue_DoubleValue
// *AnyValue_ArrayValue
// *AnyValue_KvlistValue
// *AnyValue_BytesValue
Value isAnyValue_Value `protobuf_oneof:"value"`
}
type isAnyValue_Value interface {
isAnyValue_Value()
}
type AnyValue_StringValue struct {
StringValue string `protobuf:"bytes,1,opt,name=string_value,json=stringValue,proto3,oneof"`
}
type AnyValue_BoolValue struct {
BoolValue bool `protobuf:"varint,2,opt,name=bool_value,json=boolValue,proto3,oneof"`
}
type AnyValue_IntValue struct {
IntValue int64 `protobuf:"varint,3,opt,name=int_value,json=intValue,proto3,oneof"`
}
type AnyValue_DoubleValue struct {
DoubleValue float64 `protobuf:"fixed64,4,opt,name=double_value,json=doubleValue,proto3,oneof"`
}
type AnyValue_ArrayValue struct {
ArrayValue *ArrayValue `protobuf:"bytes,5,opt,name=array_value,json=arrayValue,proto3,oneof"`
}
type AnyValue_KvlistValue struct {
KvlistValue *KeyValueList `protobuf:"bytes,6,opt,name=kvlist_value,json=kvlistValue,proto3,oneof"`
}
type AnyValue_BytesValue struct {
BytesValue []byte `protobuf:"bytes,7,opt,name=bytes_value,json=bytesValue,proto3,oneof"`
}
func (*AnyValue_StringValue) isAnyValue_Value() {}
func (*AnyValue_BoolValue) isAnyValue_Value() {}
func (*AnyValue_IntValue) isAnyValue_Value() {}
func (*AnyValue_DoubleValue) isAnyValue_Value() {}
func (*AnyValue_ArrayValue) isAnyValue_Value() {}
func (*AnyValue_KvlistValue) isAnyValue_Value() {}
func (*AnyValue_BytesValue) isAnyValue_Value() {}
// ArrayValue is a list of AnyValue messages. We need ArrayValue as a message
// since oneof in AnyValue does not allow repeated fields.
type ArrayValue struct {
unknownFields []byte
// Array of values. The array may be empty (contain 0 elements).
Values []*AnyValue `protobuf:"bytes,1,rep,name=values,proto3" json:"values,omitempty"`
}
// KeyValueList is a list of KeyValue messages. We need KeyValueList as a message
// since `oneof` in AnyValue does not allow repeated fields. Everywhere else where we need
// a list of KeyValue messages (e.g. in Span) we use `repeated KeyValue` directly to
// avoid unnecessary extra wrapping (which slows down the protocol). The 2 approaches
// are semantically equivalent.
type KeyValueList struct {
unknownFields []byte
// A collection of key/value pairs of key-value pairs. The list may be empty (may
// contain 0 elements).
// The keys MUST be unique (it is not allowed to have more than one
// value with the same key).
Values []*KeyValue `protobuf:"bytes,1,rep,name=values,proto3" json:"values,omitempty"`
}
// KeyValue is a key-value pair that is used to store Span attributes, Link
// attributes, etc.
type KeyValue struct {
unknownFields []byte
Key string `protobuf:"bytes,1,opt,name=key,proto3" json:"key,omitempty"`
Value *AnyValue `protobuf:"bytes,2,opt,name=value,proto3" json:"value,omitempty"`
}

1079
lib/protoparser/opentelemetry/pb/common_vtproto.pb.go
View file

File diff suppressed because it is too large Load diff

41
lib/protoparser/opentelemetry/pb/helpers.go
View file

@ -8,32 +8,25 @@ import (
"strconv" "strconv"
) )
// FormatString formats strings // FormatString returns string reperesentation for av.
func (x *AnyValue) FormatString() string { func (av *AnyValue) FormatString() string {
switch v := x.Value.(type) { switch {
case *AnyValue_StringValue: case av.StringValue != nil:
return v.StringValue return *av.StringValue
case av.BoolValue != nil:
case *AnyValue_BoolValue: return strconv.FormatBool(*av.BoolValue)
return strconv.FormatBool(v.BoolValue) case av.IntValue != nil:
return strconv.FormatInt(*av.IntValue, 10)
case *AnyValue_DoubleValue: case av.DoubleValue != nil:
return float64AsString(v.DoubleValue) return float64AsString(*av.DoubleValue)
case av.ArrayValue != nil:
case *AnyValue_IntValue: jsonStr, _ := json.Marshal(av.ArrayValue.Values)
return strconv.FormatInt(v.IntValue, 10)
case *AnyValue_KvlistValue:
jsonStr, _ := json.Marshal(v.KvlistValue.Values)
return string(jsonStr) return string(jsonStr)
case av.KeyValueList != nil:
case *AnyValue_BytesValue: jsonStr, _ := json.Marshal(av.KeyValueList.Values)
return base64.StdEncoding.EncodeToString(v.BytesValue)
case *AnyValue_ArrayValue:
jsonStr, _ := json.Marshal(v.ArrayValue.Values)
return string(jsonStr) return string(jsonStr)
case av.BytesValue != nil:
return base64.StdEncoding.EncodeToString(*av.BytesValue)
default: default:
return "" return ""
} }

736
lib/protoparser/opentelemetry/pb/metrics.pb.go
View file

@ -1,736 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.12
// source: lib/protoparser/opentelemetry/proto/metrics.proto
package pb
// AggregationTemporality defines how a metric aggregator reports aggregated
// values. It describes how those values relate to the time interval over
// which they are aggregated.
type AggregationTemporality int32
const (
// UNSPECIFIED is the default AggregationTemporality, it MUST not be used.
AggregationTemporality_AGGREGATION_TEMPORALITY_UNSPECIFIED AggregationTemporality = 0
// DELTA is an AggregationTemporality for a metric aggregator which reports
// changes since last report time. Successive metrics contain aggregation of
// values from continuous and non-overlapping intervals.
//
// The values for a DELTA metric are based only on the time interval
// associated with one measurement cycle. There is no dependency on
// previous measurements like is the case for CUMULATIVE metrics.
//
// For example, consider a system measuring the number of requests that
// it receives and reports the sum of these requests every second as a
// DELTA metric:
//
// 1. The system starts receiving at time=t_0.
// 2. A request is received, the system measures 1 request.
// 3. A request is received, the system measures 1 request.
// 4. A request is received, the system measures 1 request.
// 5. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+1 with a value of 3.
// 6. A request is received, the system measures 1 request.
// 7. A request is received, the system measures 1 request.
// 8. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0+1 to
// t_0+2 with a value of 2.
AggregationTemporality_AGGREGATION_TEMPORALITY_DELTA AggregationTemporality = 1
// CUMULATIVE is an AggregationTemporality for a metric aggregator which
// reports changes since a fixed start time. This means that current values
// of a CUMULATIVE metric depend on all previous measurements since the
// start time. Because of this, the sender is required to retain this state
// in some form. If this state is lost or invalidated, the CUMULATIVE metric
// values MUST be reset and a new fixed start time following the last
// reported measurement time sent MUST be used.
//
// For example, consider a system measuring the number of requests that
// it receives and reports the sum of these requests every second as a
// CUMULATIVE metric:
//
// 1. The system starts receiving at time=t_0.
// 2. A request is received, the system measures 1 request.
// 3. A request is received, the system measures 1 request.
// 4. A request is received, the system measures 1 request.
// 5. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+1 with a value of 3.
// 6. A request is received, the system measures 1 request.
// 7. A request is received, the system measures 1 request.
// 8. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+2 with a value of 5.
// 9. The system experiences a fault and loses state.
// 10. The system recovers and resumes receiving at time=t_1.
// 11. A request is received, the system measures 1 request.
// 12. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_1 to
// t_0+1 with a value of 1.
//
// Note: Even though, when reporting changes since last report time, using
// CUMULATIVE is valid, it is not recommended. This may cause problems for
// systems that do not use start_time to determine when the aggregation
// value was reset (e.g. Prometheus).
AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE AggregationTemporality = 2
)
// Enum value maps for AggregationTemporality.
var (
AggregationTemporality_name = map[int32]string{
0: "AGGREGATION_TEMPORALITY_UNSPECIFIED",
1: "AGGREGATION_TEMPORALITY_DELTA",
2: "AGGREGATION_TEMPORALITY_CUMULATIVE",
}
AggregationTemporality_value = map[string]int32{
"AGGREGATION_TEMPORALITY_UNSPECIFIED": 0,
"AGGREGATION_TEMPORALITY_DELTA": 1,
"AGGREGATION_TEMPORALITY_CUMULATIVE": 2,
}
)
func (x AggregationTemporality) Enum() *AggregationTemporality {
p := new(AggregationTemporality)
*p = x
return p
}
// DataPointFlags is defined as a protobuf 'uint32' type and is to be used as a
// bit-field representing 32 distinct boolean flags. Each flag defined in this
// enum is a bit-mask. To test the presence of a single flag in the flags of
// a data point, for example, use an expression like:
//
// (point.flags & FLAG_NO_RECORDED_VALUE) == FLAG_NO_RECORDED_VALUE
type DataPointFlags int32
const (
DataPointFlags_FLAG_NONE DataPointFlags = 0
// This DataPoint is valid but has no recorded value. This value
// SHOULD be used to reflect explicitly missing data in a series, as
// for an equivalent to the Prometheus "staleness marker".
DataPointFlags_FLAG_NO_RECORDED_VALUE DataPointFlags = 1
)
// Enum value maps for DataPointFlags.
var (
DataPointFlags_name = map[int32]string{
0: "FLAG_NONE",
1: "FLAG_NO_RECORDED_VALUE",
}
DataPointFlags_value = map[string]int32{
"FLAG_NONE": 0,
"FLAG_NO_RECORDED_VALUE": 1,
}
)
func (x DataPointFlags) Enum() *DataPointFlags {
p := new(DataPointFlags)
*p = x
return p
}
// MetricsData represents the metrics data that can be stored in a persistent
// storage, OR can be embedded by other protocols that transfer OTLP metrics
// data but do not implement the OTLP protocol.
//
// The main difference between this message and collector protocol is that
// in this message there will not be any "control" or "metadata" specific to
// OTLP protocol.
//
// When new fields are added into this message, the OTLP request MUST be updated
// as well.
type MetricsData struct {
unknownFields []byte
// An array of ResourceMetrics.
// For data coming from a single resource this array will typically contain
// one element. Intermediary nodes that receive data from multiple origins
// typically batch the data before forwarding further and in that case this
// array will contain multiple elements.
ResourceMetrics []*ResourceMetrics `protobuf:"bytes,1,rep,name=resource_metrics,json=resourceMetrics,proto3" json:"resource_metrics,omitempty"`
}
// A collection of ScopeMetrics from a Resource.
type ResourceMetrics struct {
unknownFields []byte
// The resource for the metrics in this message.
// If this field is not set then no resource info is known.
Resource *Resource `protobuf:"bytes,1,opt,name=resource,proto3" json:"resource,omitempty"`
// A list of metrics that originate from a resource.
ScopeMetrics []*ScopeMetrics `protobuf:"bytes,2,rep,name=scope_metrics,json=scopeMetrics,proto3" json:"scope_metrics,omitempty"`
// This schema_url applies to the data in the "resource" field. It does not apply
// to the data in the "scope_metrics" field which have their own schema_url field.
SchemaUrl string `protobuf:"bytes,3,opt,name=schema_url,json=schemaUrl,proto3" json:"schema_url,omitempty"`
}
// A collection of Metrics produced by an Scope.
type ScopeMetrics struct {
unknownFields []byte
// A list of metrics that originate from an instrumentation library.
Metrics []*Metric `protobuf:"bytes,2,rep,name=metrics,proto3" json:"metrics,omitempty"`
// This schema_url applies to all metrics in the "metrics" field.
SchemaUrl string `protobuf:"bytes,3,opt,name=schema_url,json=schemaUrl,proto3" json:"schema_url,omitempty"`
}
// Defines a Metric which has one or more timeseries. The following is a
// brief summary of the Metric data model. For more details, see:
//
// https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md
//
// The data model and relation between entities is shown in the
// diagram below. Here, "DataPoint" is the term used to refer to any
// one of the specific data point value types, and "points" is the term used
// to refer to any one of the lists of points contained in the Metric.
//
// - Metric is composed of a metadata and data.
//
// - Metadata part contains a name, description, unit.
//
// - Data is one of the possible types (Sum, Gauge, Histogram, Summary).
//
// - DataPoint contains timestamps, attributes, and one of the possible value type
// fields.
//
// Metric
// +------------+
// |name |
// |description |
// |unit | +------------------------------------+
// |data |---> |Gauge, Sum, Histogram, Summary, ... |
// +------------+ +------------------------------------+
//
// Data [One of Gauge, Sum, Histogram, Summary, ...]
// +-----------+
// |... | // Metadata about the Data.
// |points |--+
// +-----------+ |
// | +---------------------------+
// | |DataPoint 1 |
// v |+------+------+ +------+ |
// +-----+ ||label |label |...|label | |
// | 1 |-->||value1|value2|...|valueN| |
// +-----+ |+------+------+ +------+ |
// | . | |+-----+ |
// | . | ||value| |
// | . | |+-----+ |
// | . | +---------------------------+
// | . | .
// | . | .
// | . | .
// | . | +---------------------------+
// | . | |DataPoint M |
// +-----+ |+------+------+ +------+ |
// | M |-->||label |label |...|label | |
// +-----+ ||value1|value2|...|valueN| |
// |+------+------+ +------+ |
// |+-----+ |
// ||value| |
// |+-----+ |
// +---------------------------+
//
// Each distinct type of DataPoint represents the output of a specific
// aggregation function, the result of applying the DataPoint's
// associated function of to one or more measurements.
//
// All DataPoint types have three common fields:
// - Attributes includes key-value pairs associated with the data point
// - TimeUnixNano is required, set to the end time of the aggregation
// - StartTimeUnixNano is optional, but strongly encouraged for DataPoints
// having an AggregationTemporality field, as discussed below.
//
// Both TimeUnixNano and StartTimeUnixNano values are expressed as
// UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.
//
// # TimeUnixNano
//
// This field is required, having consistent interpretation across
// DataPoint types. TimeUnixNano is the moment corresponding to when
// the data point's aggregate value was captured.
//
// Data points with the 0 value for TimeUnixNano SHOULD be rejected
// by consumers.
//
// # StartTimeUnixNano
//
// StartTimeUnixNano in general allows detecting when a sequence of
// observations is unbroken. This field indicates to consumers the
// start time for points with cumulative and delta
// AggregationTemporality, and it should be included whenever possible
// to support correct rate calculation. Although it may be omitted
// when the start time is truly unknown, setting StartTimeUnixNano is
// strongly encouraged.
type Metric struct {
unknownFields []byte
// name of the metric, including its DNS name prefix. It must be unique.
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
// description of the metric, which can be used in documentation.
Description string `protobuf:"bytes,2,opt,name=description,proto3" json:"description,omitempty"`
// unit in which the metric value is reported. Follows the format
// described by http://unitsofmeasure.org/ucum.html.
Unit string `protobuf:"bytes,3,opt,name=unit,proto3" json:"unit,omitempty"`
// Data determines the aggregation type (if any) of the metric, what is the
// reported value type for the data points, as well as the relatationship to
// the time interval over which they are reported.
//
// Types that are assignable to Data:
//
// *Metric_Gauge
// *Metric_Sum
// *Metric_Histogram
// *Metric_ExponentialHistogram
// *Metric_Summary
Data isMetric_Data `protobuf_oneof:"data"`
}
type isMetric_Data interface {
isMetric_Data()
}
type Metric_Gauge struct {
Gauge *Gauge `protobuf:"bytes,5,opt,name=gauge,proto3,oneof"`
}
type Metric_Sum struct {
Sum *Sum `protobuf:"bytes,7,opt,name=sum,proto3,oneof"`
}
type Metric_Histogram struct {
Histogram *Histogram `protobuf:"bytes,9,opt,name=histogram,proto3,oneof"`
}
type Metric_ExponentialHistogram struct {
ExponentialHistogram *ExponentialHistogram `protobuf:"bytes,10,opt,name=exponential_histogram,json=exponentialHistogram,proto3,oneof"`
}
type Metric_Summary struct {
Summary *Summary `protobuf:"bytes,11,opt,name=summary,proto3,oneof"`
}
func (*Metric_Gauge) isMetric_Data() {}
func (*Metric_Sum) isMetric_Data() {}
func (*Metric_Histogram) isMetric_Data() {}
func (*Metric_ExponentialHistogram) isMetric_Data() {}
func (*Metric_Summary) isMetric_Data() {}
// Gauge represents the type of a scalar metric that always exports the
// "current value" for every data point. It should be used for an "unknown"
// aggregation.
//
// A Gauge does not support different aggregation temporalities. Given the
// aggregation is unknown, points cannot be combined using the same
// aggregation, regardless of aggregation temporalities. Therefore,
// AggregationTemporality is not included. Consequently, this also means
// "StartTimeUnixNano" is ignored for all data points.
type Gauge struct {
unknownFields []byte
DataPoints []*NumberDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
}
// Sum represents the type of a scalar metric that is calculated as a sum of all
// reported measurements over a time interval.
type Sum struct {
unknownFields []byte
DataPoints []*NumberDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
// If "true" means that the sum is monotonic.
IsMonotonic bool `protobuf:"varint,3,opt,name=is_monotonic,json=isMonotonic,proto3" json:"is_monotonic,omitempty"`
}
// Histogram represents the type of a metric that is calculated by aggregating
// as a Histogram of all reported measurements over a time interval.
type Histogram struct {
unknownFields []byte
DataPoints []*HistogramDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
}
// ExponentialHistogram represents the type of a metric that is calculated by aggregating
// as a ExponentialHistogram of all reported double measurements over a time interval.
type ExponentialHistogram struct {
unknownFields []byte
DataPoints []*ExponentialHistogramDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
}
// Summary metric data are used to convey quantile summaries,
// a Prometheus (see: https://prometheus.io/docs/concepts/metric_types/#summary)
// and OpenMetrics (see: https://github.com/OpenObservability/OpenMetrics/blob/4dbf6075567ab43296eed941037c12951faafb92/protos/prometheus.proto#L45)
// data type. These data points cannot always be merged in a meaningful way.
// While they can be useful in some applications, histogram data points are
// recommended for new applications.
type Summary struct {
unknownFields []byte
DataPoints []*SummaryDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
}
// NumberDataPoint is a single data point in a timeseries that describes the
// time-varying scalar value of a metric.
type NumberDataPoint struct {
unknownFields []byte
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
Attributes []*KeyValue `protobuf:"bytes,7,rep,name=attributes,proto3" json:"attributes,omitempty"`
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
// The value itself. A point is considered invalid when one of the recognized
// value fields is not present inside this oneof.
//
// Types that are assignable to Value:
//
// *NumberDataPoint_AsDouble
// *NumberDataPoint_AsInt
Value isNumberDataPoint_Value `protobuf_oneof:"value"`
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
Exemplars []*Exemplar `protobuf:"bytes,5,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
Flags uint32 `protobuf:"varint,8,opt,name=flags,proto3" json:"flags,omitempty"`
}
type isNumberDataPoint_Value interface {
isNumberDataPoint_Value()
}
type NumberDataPoint_AsDouble struct {
AsDouble float64 `protobuf:"fixed64,4,opt,name=as_double,json=asDouble,proto3,oneof"`
}
type NumberDataPoint_AsInt struct {
AsInt int64 `protobuf:"fixed64,6,opt,name=as_int,json=asInt,proto3,oneof"`
}
func (*NumberDataPoint_AsDouble) isNumberDataPoint_Value() {}
func (*NumberDataPoint_AsInt) isNumberDataPoint_Value() {}
// HistogramDataPoint is a single data point in a timeseries that describes the
// time-varying values of a Histogram. A Histogram contains summary statistics
// for a population of values, it may optionally contain the distribution of
// those values across a set of buckets.
//
// If the histogram contains the distribution of values, then both
// "explicit_bounds" and "bucket counts" fields must be defined.
// If the histogram does not contain the distribution of values, then both
// "explicit_bounds" and "bucket_counts" must be omitted and only "count" and
// "sum" are known.
type HistogramDataPoint struct {
unknownFields []byte
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
Attributes []*KeyValue `protobuf:"bytes,9,rep,name=attributes,proto3" json:"attributes,omitempty"`
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
// count is the number of values in the population. Must be non-negative. This
// value must be equal to the sum of the "count" fields in buckets if a
// histogram is provided.
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
Sum *float64 `protobuf:"fixed64,5,opt,name=sum,proto3,oneof" json:"sum,omitempty"`
// bucket_counts is an optional field contains the count values of histogram
// for each bucket.
//
// The sum of the bucket_counts must equal the value in the count field.
//
// The number of elements in bucket_counts array must be by one greater than
// the number of elements in explicit_bounds array.
BucketCounts []uint64 `protobuf:"fixed64,6,rep,packed,name=bucket_counts,json=bucketCounts,proto3" json:"bucket_counts,omitempty"`
// explicit_bounds specifies buckets with explicitly defined bounds for values.
//
// The boundaries for bucket at index i are:
//
// (-infinity, explicit_bounds[i]] for i == 0
// (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds)
// (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds)
//
// The values in the explicit_bounds array must be strictly increasing.
//
// Histogram buckets are inclusive of their upper boundary, except the last
// bucket where the boundary is at infinity. This format is intentionally
// compatible with the OpenMetrics histogram definition.
ExplicitBounds []float64 `protobuf:"fixed64,7,rep,packed,name=explicit_bounds,json=explicitBounds,proto3" json:"explicit_bounds,omitempty"`
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
Exemplars []*Exemplar `protobuf:"bytes,8,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
Flags uint32 `protobuf:"varint,10,opt,name=flags,proto3" json:"flags,omitempty"`
// min is the minimum value over (start_time, end_time].
Min *float64 `protobuf:"fixed64,11,opt,name=min,proto3,oneof" json:"min,omitempty"`
// max is the maximum value over (start_time, end_time].
Max *float64 `protobuf:"fixed64,12,opt,name=max,proto3,oneof" json:"max,omitempty"`
}
// ExponentialHistogramDataPoint is a single data point in a timeseries that describes the
// time-varying values of a ExponentialHistogram of double values. A ExponentialHistogram contains
// summary statistics for a population of values, it may optionally contain the
// distribution of those values across a set of buckets.
type ExponentialHistogramDataPoint struct {
unknownFields []byte
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
Attributes []*KeyValue `protobuf:"bytes,1,rep,name=attributes,proto3" json:"attributes,omitempty"`
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
// count is the number of values in the population. Must be
// non-negative. This value must be equal to the sum of the "bucket_counts"
// values in the positive and negative Buckets plus the "zero_count" field.
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
Sum *float64 `protobuf:"fixed64,5,opt,name=sum,proto3,oneof" json:"sum,omitempty"`
// scale describes the resolution of the histogram. Boundaries are
// located at powers of the base, where:
//
// base = (2^(2^-scale))
//
// The histogram bucket identified by `index`, a signed integer,
// contains values that are greater than (base^index) and
// less than or equal to (base^(index+1)).
//
// The positive and negative ranges of the histogram are expressed
// separately. Negative values are mapped by their absolute value
// into the negative range using the same scale as the positive range.
//
// scale is not restricted by the protocol, as the permissible
// values depend on the range of the data.
Scale int32 `protobuf:"zigzag32,6,opt,name=scale,proto3" json:"scale,omitempty"`
// zero_count is the count of values that are either exactly zero or
// within the region considered zero by the instrumentation at the
// tolerated degree of precision. This bucket stores values that
// cannot be expressed using the standard exponential formula as
// well as values that have been rounded to zero.
//
// Implementations MAY consider the zero bucket to have probability
// mass equal to (zero_count / count).
ZeroCount uint64 `protobuf:"fixed64,7,opt,name=zero_count,json=zeroCount,proto3" json:"zero_count,omitempty"`
// positive carries the positive range of exponential bucket counts.
Positive *ExponentialHistogramDataPoint_Buckets `protobuf:"bytes,8,opt,name=positive,proto3" json:"positive,omitempty"`
// negative carries the negative range of exponential bucket counts.
Negative *ExponentialHistogramDataPoint_Buckets `protobuf:"bytes,9,opt,name=negative,proto3" json:"negative,omitempty"`
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
Flags uint32 `protobuf:"varint,10,opt,name=flags,proto3" json:"flags,omitempty"`
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
Exemplars []*Exemplar `protobuf:"bytes,11,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
// min is the minimum value over (start_time, end_time].
Min *float64 `protobuf:"fixed64,12,opt,name=min,proto3,oneof" json:"min,omitempty"`
// max is the maximum value over (start_time, end_time].
Max *float64 `protobuf:"fixed64,13,opt,name=max,proto3,oneof" json:"max,omitempty"`
}
// SummaryDataPoint is a single data point in a timeseries that describes the
// time-varying values of a Summary metric.
type SummaryDataPoint struct {
unknownFields []byte
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
Attributes []*KeyValue `protobuf:"bytes,7,rep,name=attributes,proto3" json:"attributes,omitempty"`
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
// count is the number of values in the population. Must be non-negative.
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#summary
Sum float64 `protobuf:"fixed64,5,opt,name=sum,proto3" json:"sum,omitempty"`
// (Optional) list of values at different quantiles of the distribution calculated
// from the current snapshot. The quantiles must be strictly increasing.
QuantileValues []*SummaryDataPoint_ValueAtQuantile `protobuf:"bytes,6,rep,name=quantile_values,json=quantileValues,proto3" json:"quantile_values,omitempty"`
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
Flags uint32 `protobuf:"varint,8,opt,name=flags,proto3" json:"flags,omitempty"`
}
// A representation of an exemplar, which is a sample input measurement.
// Exemplars also hold information about the environment when the measurement
// was recorded, for example the span and trace ID of the active span when the
// exemplar was recorded.
type Exemplar struct {
unknownFields []byte
// The set of key/value pairs that were filtered out by the aggregator, but
// recorded alongside the original measurement. Only key/value pairs that were
// filtered out by the aggregator should be included
FilteredAttributes []*KeyValue `protobuf:"bytes,7,rep,name=filtered_attributes,json=filteredAttributes,proto3" json:"filtered_attributes,omitempty"`
// time_unix_nano is the exact time when this exemplar was recorded
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
TimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
// The value of the measurement that was recorded. An exemplar is
// considered invalid when one of the recognized value fields is not present
// inside this oneof.
//
// Types that are assignable to Value:
//
// *Exemplar_AsDouble
// *Exemplar_AsInt
Value isExemplar_Value `protobuf_oneof:"value"`
// (Optional) Span ID of the exemplar trace.
// span_id may be missing if the measurement is not recorded inside a trace
// or if the trace is not sampled.
SpanId []byte `protobuf:"bytes,4,opt,name=span_id,json=spanId,proto3" json:"span_id,omitempty"`
// (Optional) Trace ID of the exemplar trace.
// trace_id may be missing if the measurement is not recorded inside a trace
// or if the trace is not sampled.
TraceId []byte `protobuf:"bytes,5,opt,name=trace_id,json=traceId,proto3" json:"trace_id,omitempty"`
}
type isExemplar_Value interface {
isExemplar_Value()
}
type Exemplar_AsDouble struct {
AsDouble float64 `protobuf:"fixed64,3,opt,name=as_double,json=asDouble,proto3,oneof"`
}
type Exemplar_AsInt struct {
AsInt int64 `protobuf:"fixed64,6,opt,name=as_int,json=asInt,proto3,oneof"`
}
func (*Exemplar_AsDouble) isExemplar_Value() {}
func (*Exemplar_AsInt) isExemplar_Value() {}
// Buckets are a set of bucket counts, encoded in a contiguous array
// of counts.
type ExponentialHistogramDataPoint_Buckets struct {
unknownFields []byte
// Offset is the bucket index of the first entry in the bucket_counts array.
//
// Note: This uses a varint encoding as a simple form of compression.
Offset int32 `protobuf:"zigzag32,1,opt,name=offset,proto3" json:"offset,omitempty"`
// Count is an array of counts, where count[i] carries the count
// of the bucket at index (offset+i). count[i] is the count of
// values greater than base^(offset+i) and less or equal to than
// base^(offset+i+1).
//
// Note: By contrast, the explicit HistogramDataPoint uses
// fixed64. This field is expected to have many buckets,
// especially zeros, so uint64 has been selected to ensure
// varint encoding.
BucketCounts []uint64 `protobuf:"varint,2,rep,packed,name=bucket_counts,json=bucketCounts,proto3" json:"bucket_counts,omitempty"`
}
// Represents the value at a given quantile of a distribution.
//
// To record Min and Max values following conventions are used:
// - The 1.0 quantile is equivalent to the maximum value observed.
// - The 0.0 quantile is equivalent to the minimum value observed.
//
// See the following issue for more context:
// https://github.com/open-telemetry/opentelemetry-proto/issues/125
type SummaryDataPoint_ValueAtQuantile struct {
unknownFields []byte
// The quantile of a distribution. Must be in the interval
// [0.0, 1.0].
Quantile float64 `protobuf:"fixed64,1,opt,name=quantile,proto3" json:"quantile,omitempty"`
// The value at the given quantile of a distribution.
//
// Quantile values must NOT be negative.
Value float64 `protobuf:"fixed64,2,opt,name=value,proto3" json:"value,omitempty"`
}

32
lib/protoparser/opentelemetry/pb/metrics_service.pb.go
View file

@ -1,32 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.12
// source: lib/protoparser/opentelemetry/proto/metrics_service.proto
package pb
type ExportMetricsServiceRequest struct {
unknownFields []byte
// An array of ResourceMetrics.
// For data coming from a single resource this array will typically contain one
// element. Intermediary nodes (such as OpenTelemetry Collector) that receive
// data from multiple origins typically batch the data before forwarding further and
// in that case this array will contain multiple elements.
ResourceMetrics []*ResourceMetrics `protobuf:"bytes,1,rep,name=resource_metrics,json=resourceMetrics,proto3" json:"resource_metrics,omitempty"`
}

157
lib/protoparser/opentelemetry/pb/metrics_service_vtproto.pb.go
View file

@ -1,157 +0,0 @@
// Code generated by protoc-gen-go-vtproto. DO NOT EDIT.
// protoc-gen-go-vtproto version: v0.4.0
// source: lib/protoparser/opentelemetry/proto/metrics_service.proto
package pb
import (
fmt "fmt"
io "io"
)
func (m *ExportMetricsServiceRequest) MarshalVT() (dAtA []byte, err error) {
if m == nil {
return nil, nil
}
size := m.SizeVT()
dAtA = make([]byte, size)
n, err := m.MarshalToSizedBufferVT(dAtA[:size])
if err != nil {
return nil, err
}
return dAtA[:n], nil
}
func (m *ExportMetricsServiceRequest) MarshalToVT(dAtA []byte) (int, error) {
size := m.SizeVT()
return m.MarshalToSizedBufferVT(dAtA[:size])
}
func (m *ExportMetricsServiceRequest) MarshalToSizedBufferVT(dAtA []byte) (int, error) {
if m == nil {
return 0, nil
}
i := len(dAtA)
_ = i
var l int
_ = l
if m.unknownFields != nil {
i -= len(m.unknownFields)
copy(dAtA[i:], m.unknownFields)
}
if len(m.ResourceMetrics) > 0 {
for iNdEx := len(m.ResourceMetrics) - 1; iNdEx >= 0; iNdEx-- {
size, err := m.ResourceMetrics[iNdEx].MarshalToSizedBufferVT(dAtA[:i])
if err != nil {
return 0, err
}
i -= size
i = encodeVarint(dAtA, i, uint64(size))
i--
dAtA[i] = 0xa
}
}
return len(dAtA) - i, nil
}
func (m *ExportMetricsServiceRequest) SizeVT() (n int) {
if m == nil {
return 0
}
var l int
_ = l
if len(m.ResourceMetrics) > 0 {
for _, e := range m.ResourceMetrics {
l = e.SizeVT()
n += 1 + l + sov(uint64(l))
}
}
n += len(m.unknownFields)
return n
}
func (m *ExportMetricsServiceRequest) UnmarshalVT(dAtA []byte) error {
l := len(dAtA)
iNdEx := 0
for iNdEx < l {
preIndex := iNdEx
var wire uint64
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflow
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
wire |= uint64(b&0x7F) << shift
if b < 0x80 {
break
}
}
fieldNum := int32(wire >> 3)
wireType := int(wire & 0x7)
if wireType == 4 {
return fmt.Errorf("proto: ExportMetricsServiceRequest: wiretype end group for non-group")
}
if fieldNum <= 0 {
return fmt.Errorf("proto: ExportMetricsServiceRequest: illegal tag %d (wire type %d)", fieldNum, wire)
}
switch fieldNum {
case 1:
if wireType != 2 {
return fmt.Errorf("proto: wrong wireType = %d for field ResourceMetrics", wireType)
}
var msglen int
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflow
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
msglen |= int(b&0x7F) << shift
if b < 0x80 {
break
}
}
if msglen < 0 {
return ErrInvalidLength
}
postIndex := iNdEx + msglen
if postIndex < 0 {
return ErrInvalidLength
}
if postIndex > l {
return io.ErrUnexpectedEOF
}
m.ResourceMetrics = append(m.ResourceMetrics, &ResourceMetrics{})
if err := m.ResourceMetrics[len(m.ResourceMetrics)-1].UnmarshalVT(dAtA[iNdEx:postIndex]); err != nil {
return err
}
iNdEx = postIndex
default:
iNdEx = preIndex
skippy, err := skip(dAtA[iNdEx:])
if err != nil {
return err
}
if (skippy < 0) || (iNdEx+skippy) < 0 {
return ErrInvalidLength
}
if (iNdEx + skippy) > l {
return io.ErrUnexpectedEOF
}
m.unknownFields = append(m.unknownFields, dAtA[iNdEx:iNdEx+skippy]...)
iNdEx += skippy
}
}
if iNdEx > l {
return io.ErrUnexpectedEOF
}
return nil
}

4331
lib/protoparser/opentelemetry/pb/metrics_vtproto.pb.go
View file

File diff suppressed because it is too large Load diff

976
lib/protoparser/opentelemetry/pb/pb.go Normal file
View file

@ -0,0 +1,976 @@
package pb
import (
"bytes"
"fmt"
"strings"
"github.com/VictoriaMetrics/easyproto"
)
// ExportMetricsServiceRequest represents the corresponding OTEL protobuf message
type ExportMetricsServiceRequest struct {
ResourceMetrics []*ResourceMetrics
}
// UnmarshalProtobuf unmarshals r from protobuf message at src.
func (r *ExportMetricsServiceRequest) UnmarshalProtobuf(src []byte) error {
r.ResourceMetrics = nil
return r.unmarshalProtobuf(src)
}
// MarshalProtobuf marshals r to protobuf message, appends it to dst and returns the result.
func (r *ExportMetricsServiceRequest) MarshalProtobuf(dst []byte) []byte {
m := mp.Get()
r.marshalProtobuf(m.MessageMarshaler())
dst = m.Marshal(dst)
mp.Put(m)
return dst
}
var mp easyproto.MarshalerPool
func (r *ExportMetricsServiceRequest) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, rm := range r.ResourceMetrics {
rm.marshalProtobuf(mm.AppendMessage(1))
}
}
func (r *ExportMetricsServiceRequest) unmarshalProtobuf(src []byte) (err error) {
// message ExportMetricsServiceRequest {
// repeated ResourceMetrics resource_metrics = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in ExportMetricsServiceRequest: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read ResourceMetrics data")
}
r.ResourceMetrics = append(r.ResourceMetrics, &ResourceMetrics{})
rm := r.ResourceMetrics[len(r.ResourceMetrics)-1]
if err := rm.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal ResourceMetrics: %w", err)
}
}
}
return nil
}
// ResourceMetrics represents the corresponding OTEL protobuf message
type ResourceMetrics struct {
Resource *Resource
ScopeMetrics []*ScopeMetrics
}
func (rm *ResourceMetrics) marshalProtobuf(mm *easyproto.MessageMarshaler) {
if rm.Resource != nil {
rm.Resource.marshalProtobuf(mm.AppendMessage(1))
}
for _, sm := range rm.ScopeMetrics {
sm.marshalProtobuf(mm.AppendMessage(2))
}
}
func (rm *ResourceMetrics) unmarshalProtobuf(src []byte) (err error) {
// message ResourceMetrics {
// Resource resource = 1;
// repeated ScopeMetrics scope_metrics = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in ResourceMetrics: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Resource data")
}
rm.Resource = &Resource{}
if err := rm.Resource.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot umarshal Resource: %w", err)
}
case 2:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read ScopeMetrics data")
}
rm.ScopeMetrics = append(rm.ScopeMetrics, &ScopeMetrics{})
sm := rm.ScopeMetrics[len(rm.ScopeMetrics)-1]
if err := sm.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal ScopeMetrics: %w", err)
}
}
}
return nil
}
// Resource represents the corresponding OTEL protobuf message
type Resource struct {
Attributes []*KeyValue
}
func (r *Resource) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, a := range r.Attributes {
a.marshalProtobuf(mm.AppendMessage(1))
}
}
func (r *Resource) unmarshalProtobuf(src []byte) (err error) {
// message Resource {
// repeated KeyValue attributes = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Resource: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Attribute data")
}
r.Attributes = append(r.Attributes, &KeyValue{})
a := r.Attributes[len(r.Attributes)-1]
if err := a.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Attribute: %w", err)
}
}
}
return nil
}
// ScopeMetrics represents the corresponding OTEL protobuf message
type ScopeMetrics struct {
Metrics []*Metric
}
func (sm *ScopeMetrics) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, m := range sm.Metrics {
m.marshalProtobuf(mm.AppendMessage(2))
}
}
func (sm *ScopeMetrics) unmarshalProtobuf(src []byte) (err error) {
// message ScopeMetrics {
// repeated Metric metrics = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in ScopeMetrics: %w", err)
}
switch fc.FieldNum {
case 2:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Metric data")
}
sm.Metrics = append(sm.Metrics, &Metric{})
m := sm.Metrics[len(sm.Metrics)-1]
if err := m.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Metric: %w", err)
}
}
}
return nil
}
// Metric represents the corresponding OTEL protobuf message
type Metric struct {
Name string
Gauge *Gauge
Sum *Sum
Histogram *Histogram
Summary *Summary
}
func (m *Metric) marshalProtobuf(mm *easyproto.MessageMarshaler) {
mm.AppendString(1, m.Name)
switch {
case m.Gauge != nil:
m.Gauge.marshalProtobuf(mm.AppendMessage(5))
case m.Sum != nil:
m.Sum.marshalProtobuf(mm.AppendMessage(7))
case m.Histogram != nil:
m.Histogram.marshalProtobuf(mm.AppendMessage(9))
case m.Summary != nil:
m.Summary.marshalProtobuf(mm.AppendMessage(11))
}
}
func (m *Metric) unmarshalProtobuf(src []byte) (err error) {
// message Metric {
// string name = 1;
// oneof data {
// Gauge gauge = 5;
// Sum sum = 7;
// Histogram histogram = 9;
// Summary summary = 11;
// }
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Metric: %w", err)
}
switch fc.FieldNum {
case 1:
name, ok := fc.String()
if !ok {
return fmt.Errorf("cannot read metric name")
}
m.Name = strings.Clone(name)
case 5:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Gauge data")
}
m.Gauge = &Gauge{}
if err := m.Gauge.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Gauge: %w", err)
}
case 7:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Sum data")
}
m.Sum = &Sum{}
if err := m.Sum.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Sum: %w", err)
}
case 9:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Histogram data")
}
m.Histogram = &Histogram{}
if err := m.Histogram.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Histogram: %w", err)
}
case 11:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Summary data")
}
m.Summary = &Summary{}
if err := m.Summary.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Summary: %w", err)
}
}
}
return nil
}
// KeyValue represents the corresponding OTEL protobuf message
type KeyValue struct {
Key string
Value *AnyValue
}
func (kv *KeyValue) marshalProtobuf(mm *easyproto.MessageMarshaler) {
mm.AppendString(1, kv.Key)
if kv.Value != nil {
kv.Value.marshalProtobuf(mm.AppendMessage(2))
}
}
func (kv *KeyValue) unmarshalProtobuf(src []byte) (err error) {
// message KeyValue {
// string key = 1;
// AnyValue value = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in KeyValue: %w", err)
}
switch fc.FieldNum {
case 1:
key, ok := fc.String()
if !ok {
return fmt.Errorf("cannot read Key")
}
kv.Key = strings.Clone(key)
case 2:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Value")
}
kv.Value = &AnyValue{}
if err := kv.Value.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Value: %w", err)
}
}
}
return nil
}
// AnyValue represents the corresponding OTEL protobuf message
type AnyValue struct {
StringValue *string
BoolValue *bool
IntValue *int64
DoubleValue *float64
ArrayValue *ArrayValue
KeyValueList *KeyValueList
BytesValue *[]byte
}
func (av *AnyValue) marshalProtobuf(mm *easyproto.MessageMarshaler) {
switch {
case av.StringValue != nil:
mm.AppendString(1, *av.StringValue)
case av.BoolValue != nil:
mm.AppendBool(2, *av.BoolValue)
case av.IntValue != nil:
mm.AppendInt64(3, *av.IntValue)
case av.DoubleValue != nil:
mm.AppendDouble(4, *av.DoubleValue)
case av.ArrayValue != nil:
av.ArrayValue.marshalProtobuf(mm.AppendMessage(5))
case av.KeyValueList != nil:
av.KeyValueList.marshalProtobuf(mm.AppendMessage(6))
case av.BytesValue != nil:
mm.AppendBytes(7, *av.BytesValue)
}
}
func (av *AnyValue) unmarshalProtobuf(src []byte) (err error) {
// message AnyValue {
// oneof value {
// string string_value = 1;
// bool bool_value = 2;
// int64 int_value = 3;
// double double_value = 4;
// ArrayValue array_value = 5;
// KeyValueList kvlist_value = 6;
// bytes bytes_value = 7;
// }
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in AnyValue")
}
switch fc.FieldNum {
case 1:
stringValue, ok := fc.String()
if !ok {
return fmt.Errorf("cannot read StringValue")
}
stringValue = strings.Clone(stringValue)
av.StringValue = &stringValue
case 2:
boolValue, ok := fc.Bool()
if !ok {
return fmt.Errorf("cannot read BoolValue")
}
av.BoolValue = &boolValue
case 3:
intValue, ok := fc.Int64()
if !ok {
return fmt.Errorf("cannot read IntValue")
}
av.IntValue = &intValue
case 4:
doubleValue, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read DoubleValue")
}
av.DoubleValue = &doubleValue
case 5:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read ArrayValue")
}
av.ArrayValue = &ArrayValue{}
if err := av.ArrayValue.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal ArrayValue: %w", err)
}
case 6:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read KeyValueList")
}
av.KeyValueList = &KeyValueList{}
if err := av.KeyValueList.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal KeyValueList: %w", err)
}
case 7:
bytesValue, ok := fc.Bytes()
if !ok {
return fmt.Errorf("cannot read BytesValue")
}
bytesValue = bytes.Clone(bytesValue)
av.BytesValue = &bytesValue
}
}
return nil
}
// ArrayValue represents the corresponding OTEL protobuf message
type ArrayValue struct {
Values []*AnyValue
}
func (av *ArrayValue) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, v := range av.Values {
v.marshalProtobuf(mm.AppendMessage(1))
}
}
func (av *ArrayValue) unmarshalProtobuf(src []byte) (err error) {
// message ArrayValue {
// repeated AnyValue values = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in ArrayValue")
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Value data")
}
av.Values = append(av.Values, &AnyValue{})
v := av.Values[len(av.Values)-1]
if err := v.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Value: %w", err)
}
}
}
return nil
}
// KeyValueList represents the corresponding OTEL protobuf message
type KeyValueList struct {
Values []*KeyValue
}
func (kvl *KeyValueList) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, v := range kvl.Values {
v.marshalProtobuf(mm.AppendMessage(1))
}
}
func (kvl *KeyValueList) unmarshalProtobuf(src []byte) (err error) {
// message KeyValueList {
// repeated KeyValue values = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in KeyValueList")
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Value data")
}
kvl.Values = append(kvl.Values, &KeyValue{})
v := kvl.Values[len(kvl.Values)-1]
if err := v.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Value: %w", err)
}
}
}
return nil
}
// Gauge represents the corresponding OTEL protobuf message
type Gauge struct {
DataPoints []*NumberDataPoint
}
func (g *Gauge) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, dp := range g.DataPoints {
dp.marshalProtobuf(mm.AppendMessage(1))
}
}
func (g *Gauge) unmarshalProtobuf(src []byte) (err error) {
// message Gauge {
// repeated NumberDataPoint data_points = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Gauge")
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read DataPoint data")
}
g.DataPoints = append(g.DataPoints, &NumberDataPoint{})
dp := g.DataPoints[len(g.DataPoints)-1]
if err := dp.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal DataPoint: %w", err)
}
}
}
return nil
}
// NumberDataPoint represents the corresponding OTEL protobuf message
type NumberDataPoint struct {
Attributes []*KeyValue
TimeUnixNano uint64
DoubleValue *float64
IntValue *int64
Flags uint32
}
func (ndp *NumberDataPoint) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, a := range ndp.Attributes {
a.marshalProtobuf(mm.AppendMessage(7))
}
mm.AppendFixed64(3, ndp.TimeUnixNano)
switch {
case ndp.DoubleValue != nil:
mm.AppendDouble(4, *ndp.DoubleValue)
case ndp.IntValue != nil:
mm.AppendSfixed64(6, *ndp.IntValue)
}
mm.AppendUint32(8, ndp.Flags)
}
func (ndp *NumberDataPoint) unmarshalProtobuf(src []byte) (err error) {
// message NumberDataPoint {
// repeated KeyValue attributes = 7;
// fixed64 time_unix_nano = 3;
// oneof value {
// double as_double = 4;
// sfixed64 as_int = 6;
// }
// uint32 flags = 8;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in NumberDataPoint: %w", err)
}
switch fc.FieldNum {
case 7:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Attribute")
}
ndp.Attributes = append(ndp.Attributes, &KeyValue{})
a := ndp.Attributes[len(ndp.Attributes)-1]
if err := a.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Attribute: %w", err)
}
case 3:
timeUnixNano, ok := fc.Fixed64()
if !ok {
return fmt.Errorf("cannot read TimeUnixNano")
}
ndp.TimeUnixNano = timeUnixNano
case 4:
doubleValue, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read DoubleValue")
}
ndp.DoubleValue = &doubleValue
case 6:
intValue, ok := fc.Sfixed64()
if !ok {
return fmt.Errorf("cannot read IntValue")
}
ndp.IntValue = &intValue
case 8:
flags, ok := fc.Uint32()
if !ok {
return fmt.Errorf("cannot read Flags")
}
ndp.Flags = flags
}
}
return nil
}
// Sum represents the corresponding OTEL protobuf message
type Sum struct {
DataPoints []*NumberDataPoint
AggregationTemporality AggregationTemporality
}
// AggregationTemporality represents the corresponding OTEL protobuf enum
type AggregationTemporality int
const (
// AggregationTemporalityUnspecified is enum value for AggregationTemporality
AggregationTemporalityUnspecified = AggregationTemporality(0)
// AggregationTemporalityDelta is enum value for AggregationTemporality
AggregationTemporalityDelta = AggregationTemporality(1)
// AggregationTemporalityCumulative is enum value for AggregationTemporality
AggregationTemporalityCumulative = AggregationTemporality(2)
)
func (s *Sum) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, dp := range s.DataPoints {
dp.marshalProtobuf(mm.AppendMessage(1))
}
mm.AppendInt64(2, int64(s.AggregationTemporality))
}
func (s *Sum) unmarshalProtobuf(src []byte) (err error) {
// message Sum {
// repeated NumberDataPoint data_points = 1;
// AggregationTemporality aggregation_temporality = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Sum: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read DataPoint data")
}
s.DataPoints = append(s.DataPoints, &NumberDataPoint{})
dp := s.DataPoints[len(s.DataPoints)-1]
if err := dp.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal DataPoint: %w", err)
}
case 2:
at, ok := fc.Int64()
if !ok {
return fmt.Errorf("cannot read AggregationTemporality")
}
s.AggregationTemporality = AggregationTemporality(at)
}
}
return nil
}
// Histogram represents the corresponding OTEL protobuf message
type Histogram struct {
DataPoints []*HistogramDataPoint
AggregationTemporality AggregationTemporality
}
func (h *Histogram) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, dp := range h.DataPoints {
dp.marshalProtobuf(mm.AppendMessage(1))
}
mm.AppendInt64(2, int64(h.AggregationTemporality))
}
func (h *Histogram) unmarshalProtobuf(src []byte) (err error) {
// message Histogram {
// repeated HistogramDataPoint data_points = 1;
// AggregationTemporality aggregation_temporality = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Histogram: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read DataPoint")
}
h.DataPoints = append(h.DataPoints, &HistogramDataPoint{})
dp := h.DataPoints[len(h.DataPoints)-1]
if err := dp.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal DataPoint: %w", err)
}
case 2:
at, ok := fc.Int64()
if !ok {
return fmt.Errorf("cannot read AggregationTemporality")
}
h.AggregationTemporality = AggregationTemporality(at)
}
}
return nil
}
// Summary represents the corresponding OTEL protobuf message
type Summary struct {
DataPoints []*SummaryDataPoint
}
func (s *Summary) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, dp := range s.DataPoints {
dp.marshalProtobuf(mm.AppendMessage(1))
}
}
func (s *Summary) unmarshalProtobuf(src []byte) (err error) {
// message Summary {
// repeated SummaryDataPoint data_points = 1;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in Summary: %w", err)
}
switch fc.FieldNum {
case 1:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read DataPoint")
}
s.DataPoints = append(s.DataPoints, &SummaryDataPoint{})
dp := s.DataPoints[len(s.DataPoints)-1]
if err := dp.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal DataPoint: %w", err)
}
}
}
return nil
}
// HistogramDataPoint represents the corresponding OTEL protobuf message
type HistogramDataPoint struct {
Attributes []*KeyValue
TimeUnixNano uint64
Count uint64
Sum *float64
BucketCounts []uint64
ExplicitBounds []float64
Flags uint32
}
func (dp *HistogramDataPoint) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, a := range dp.Attributes {
a.marshalProtobuf(mm.AppendMessage(9))
}
mm.AppendFixed64(3, dp.TimeUnixNano)
mm.AppendFixed64(4, dp.Count)
if dp.Sum != nil {
mm.AppendDouble(5, *dp.Sum)
}
mm.AppendFixed64s(6, dp.BucketCounts)
mm.AppendDoubles(7, dp.ExplicitBounds)
mm.AppendUint32(10, dp.Flags)
}
func (dp *HistogramDataPoint) unmarshalProtobuf(src []byte) (err error) {
// message HistogramDataPoint {
// repeated KeyValue attributes = 9;
// fixed64 time_unix_nano = 3;
// fixed64 count = 4;
// optional double sum = 5;
// repeated fixed64 bucket_counts = 6;
// repeated double explicit_bounds = 7;
// uint32 flags = 10;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in HistogramDataPoint: %w", err)
}
switch fc.FieldNum {
case 9:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Attribute")
}
dp.Attributes = append(dp.Attributes, &KeyValue{})
a := dp.Attributes[len(dp.Attributes)-1]
if err := a.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Attribute: %w", err)
}
case 3:
timeUnixNano, ok := fc.Fixed64()
if !ok {
return fmt.Errorf("cannot read TimeUnixNano")
}
dp.TimeUnixNano = timeUnixNano
case 4:
count, ok := fc.Fixed64()
if !ok {
return fmt.Errorf("cannot read Count")
}
dp.Count = count
case 5:
sum, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read Sum")
}
dp.Sum = &sum
case 6:
bucketCounts, ok := fc.UnpackFixed64s(dp.BucketCounts)
if !ok {
return fmt.Errorf("cannot read BucketCounts")
}
dp.BucketCounts = bucketCounts
case 7:
explicitBounds, ok := fc.UnpackDoubles(dp.ExplicitBounds)
if !ok {
return fmt.Errorf("cannot read ExplicitBounds")
}
dp.ExplicitBounds = explicitBounds
case 10:
flags, ok := fc.Uint32()
if !ok {
return fmt.Errorf("cannot read Flags")
}
dp.Flags = flags
}
}
return nil
}
// SummaryDataPoint represents the corresponding OTEL protobuf message
type SummaryDataPoint struct {
Attributes []*KeyValue
TimeUnixNano uint64
Count uint64
Sum float64
QuantileValues []*ValueAtQuantile
Flags uint32
}
func (dp *SummaryDataPoint) marshalProtobuf(mm *easyproto.MessageMarshaler) {
for _, a := range dp.Attributes {
a.marshalProtobuf(mm.AppendMessage(7))
}
mm.AppendFixed64(3, dp.TimeUnixNano)
mm.AppendFixed64(4, dp.Count)
mm.AppendDouble(5, dp.Sum)
for _, v := range dp.QuantileValues {
v.marshalProtobuf(mm.AppendMessage(6))
}
mm.AppendUint32(8, dp.Flags)
}
func (dp *SummaryDataPoint) unmarshalProtobuf(src []byte) (err error) {
// message SummaryDataPoint {
// repeated KeyValue attributes = 7;
// fixed64 time_unix_nano = 3;
// fixed64 count = 4;
// double sum = 5;
// repeated ValueAtQuantile quantile_values = 6;
// uint32 flags = 8;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in SummaryDataPoint: %w", err)
}
switch fc.FieldNum {
case 7:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read Attribute")
}
dp.Attributes = append(dp.Attributes, &KeyValue{})
a := dp.Attributes[len(dp.Attributes)-1]
if err := a.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal Attribute: %w", err)
}
case 3:
timeUnixNano, ok := fc.Fixed64()
if !ok {
return fmt.Errorf("cannot read TimeUnixNano")
}
dp.TimeUnixNano = timeUnixNano
case 4:
count, ok := fc.Fixed64()
if !ok {
return fmt.Errorf("cannot read Count")
}
dp.Count = count
case 5:
sum, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read Sum")
}
dp.Sum = sum
case 6:
data, ok := fc.MessageData()
if !ok {
return fmt.Errorf("cannot read QuantileValue")
}
dp.QuantileValues = append(dp.QuantileValues, &ValueAtQuantile{})
v := dp.QuantileValues[len(dp.QuantileValues)-1]
if err := v.unmarshalProtobuf(data); err != nil {
return fmt.Errorf("cannot unmarshal QuantileValue: %w", err)
}
case 8:
flags, ok := fc.Uint32()
if !ok {
return fmt.Errorf("cannot read Flags")
}
dp.Flags = flags
}
}
return nil
}
// ValueAtQuantile represents the corresponding OTEL protobuf message
type ValueAtQuantile struct {
Quantile float64
Value float64
}
func (v *ValueAtQuantile) marshalProtobuf(mm *easyproto.MessageMarshaler) {
mm.AppendDouble(1, v.Quantile)
mm.AppendDouble(2, v.Value)
}
func (v *ValueAtQuantile) unmarshalProtobuf(src []byte) (err error) {
// message ValueAtQuantile {
// double quantile = 1;
// double value = 2;
// }
var fc easyproto.FieldContext
for len(src) > 0 {
src, err = fc.NextField(src)
if err != nil {
return fmt.Errorf("cannot read next field in ValueAtQuantile: %w", err)
}
switch fc.FieldNum {
case 1:
quantile, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read Quantile")
}
v.Quantile = quantile
case 2:
value, ok := fc.Double()
if !ok {
return fmt.Errorf("cannot read Value")
}
v.Value = value
}
}
return nil
}

48
lib/protoparser/opentelemetry/pb/resource.pb.go
View file

@ -1,48 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.12
// source: lib/protoparser/opentelemetry/proto/resource.proto
package pb
// Resource information.
type Resource struct {
unknownFields []byte
// Set of attributes that describe the resource.
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
Attributes []*KeyValue `protobuf:"bytes,1,rep,name=attributes,proto3" json:"attributes,omitempty"`
// dropped_attributes_count is the number of dropped attributes. If the value is 0, then
// no attributes were dropped.
DroppedAttributesCount uint32 `protobuf:"varint,2,opt,name=dropped_attributes_count,json=droppedAttributesCount,proto3" json:"dropped_attributes_count,omitempty"`
}
func (x *Resource) GetAttributes() []*KeyValue {
if x != nil {
return x.Attributes
}
return nil
}
func (x *Resource) GetDroppedAttributesCount() uint32 {
if x != nil {
return x.DroppedAttributesCount
}
return 0
}

184
lib/protoparser/opentelemetry/pb/resource_vtproto.pb.go
View file

@ -1,184 +0,0 @@
// Code generated by protoc-gen-go-vtproto. DO NOT EDIT.
// protoc-gen-go-vtproto version: v0.4.0
// source: lib/protoparser/opentelemetry/proto/resource.proto
package pb
import (
fmt "fmt"
io "io"
)
func (m *Resource) MarshalVT() (dAtA []byte, err error) {
if m == nil {
return nil, nil
}
size := m.SizeVT()
dAtA = make([]byte, size)
n, err := m.MarshalToSizedBufferVT(dAtA[:size])
if err != nil {
return nil, err
}
return dAtA[:n], nil
}
func (m *Resource) MarshalToVT(dAtA []byte) (int, error) {
size := m.SizeVT()
return m.MarshalToSizedBufferVT(dAtA[:size])
}
func (m *Resource) MarshalToSizedBufferVT(dAtA []byte) (int, error) {
if m == nil {
return 0, nil
}
i := len(dAtA)
_ = i
var l int
_ = l
if m.unknownFields != nil {
i -= len(m.unknownFields)
copy(dAtA[i:], m.unknownFields)
}
if m.DroppedAttributesCount != 0 {
i = encodeVarint(dAtA, i, uint64(m.DroppedAttributesCount))
i--
dAtA[i] = 0x10
}
if len(m.Attributes) > 0 {
for iNdEx := len(m.Attributes) - 1; iNdEx >= 0; iNdEx-- {
size, err := m.Attributes[iNdEx].MarshalToSizedBufferVT(dAtA[:i])
if err != nil {
return 0, err
}
i -= size
i = encodeVarint(dAtA, i, uint64(size))
i--
dAtA[i] = 0xa
}
}
return len(dAtA) - i, nil
}
func (m *Resource) SizeVT() (n int) {
if m == nil {
return 0
}
var l int
_ = l
if len(m.Attributes) > 0 {
for _, e := range m.Attributes {
l = e.SizeVT()
n += 1 + l + sov(uint64(l))
}
}
if m.DroppedAttributesCount != 0 {
n += 1 + sov(uint64(m.DroppedAttributesCount))
}
n += len(m.unknownFields)
return n
}
func (m *Resource) UnmarshalVT(dAtA []byte) error {
l := len(dAtA)
iNdEx := 0
for iNdEx < l {
preIndex := iNdEx
var wire uint64
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflow
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
wire |= uint64(b&0x7F) << shift
if b < 0x80 {
break
}
}
fieldNum := int32(wire >> 3)
wireType := int(wire & 0x7)
if wireType == 4 {
return fmt.Errorf("proto: Resource: wiretype end group for non-group")
}
if fieldNum <= 0 {
return fmt.Errorf("proto: Resource: illegal tag %d (wire type %d)", fieldNum, wire)
}
switch fieldNum {
case 1:
if wireType != 2 {
return fmt.Errorf("proto: wrong wireType = %d for field Attributes", wireType)
}
var msglen int
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflow
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
msglen |= int(b&0x7F) << shift
if b < 0x80 {
break
}
}
if msglen < 0 {
return ErrInvalidLength
}
postIndex := iNdEx + msglen
if postIndex < 0 {
return ErrInvalidLength
}
if postIndex > l {
return io.ErrUnexpectedEOF
}
m.Attributes = append(m.Attributes, &KeyValue{})
if err := m.Attributes[len(m.Attributes)-1].UnmarshalVT(dAtA[iNdEx:postIndex]); err != nil {
return err
}
iNdEx = postIndex
case 2:
if wireType != 0 {
return fmt.Errorf("proto: wrong wireType = %d for field DroppedAttributesCount", wireType)
}
m.DroppedAttributesCount = 0
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflow
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
m.DroppedAttributesCount |= uint32(b&0x7F) << shift
if b < 0x80 {
break
}
}
default:
iNdEx = preIndex
skippy, err := skip(dAtA[iNdEx:])
if err != nil {
return err
}
if (skippy < 0) || (iNdEx+skippy) < 0 {
return ErrInvalidLength
}
if (iNdEx + skippy) > l {
return io.ErrUnexpectedEOF
}
m.unknownFields = append(m.unknownFields, dAtA[iNdEx:iNdEx+skippy]...)
iNdEx += skippy
}
}
if iNdEx > l {
return io.ErrUnexpectedEOF
}
return nil
}

32
lib/protoparser/opentelemetry/proto/README.md
View file

@ -1,32 +0,0 @@
# Opentelemetry proto files
Content copied from https://github.com/open-telemetry/opentelemetry-proto/tree/main/opentelemetry/proto
## Requirements
- protoc binary [link](http://google.github.io/proto-lens/installing-protoc.html)
- golang-proto-gen[link](https://developers.google.com/protocol-buffers/docs/reference/go-generated)
- custom marshaller [link](https://github.com/planetscale/vtprotobuf)
## Modifications
Original proto files were modified:
1) changed package name for `package opentelemetry`.
2) changed import paths - changed directory names.
3) changed go_package for `opentelemetry/pb`.
## How to generate pbs
run command:
```bash
export GOBIN=~/go/bin protoc
protoc -I=. --go_out=./lib/protoparser/opentelemetry --go-vtproto_out=./lib/protoparser/opentelemetry --plugin protoc-gen-go-vtproto="$GOBIN/protoc-gen-go-vtproto" --go-vtproto_opt=features=marshal+unmarshal+size lib/protoparser/opentelemetry/proto/*.proto
```
Generated code will be at `lib/protoparser/opentelemetry/opentelemetry/`
manually edit it:
1) remove all external imports
2) remove all unneeded methods
3) replace `unknownFields` with `unknownFields []byte`

67
lib/protoparser/opentelemetry/proto/common.proto
View file

@ -1,67 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
syntax = "proto3";
package opentelemetry;
option csharp_namespace = "OpenTelemetry.Proto.Common.V1";
option java_multiple_files = true;
option java_package = "io.opentelemetry.proto.common.v1";
option java_outer_classname = "CommonProto";
option go_package = "opentelemetry/pb";
// AnyValue is used to represent any type of attribute value. AnyValue may contain a
// primitive value such as a string or integer or it may contain an arbitrary nested
// object containing arrays, key-value lists and primitives.
message AnyValue {
// The value is one of the listed fields. It is valid for all values to be unspecified
// in which case this AnyValue is considered to be "empty".
oneof value {
string string_value = 1;
bool bool_value = 2;
int64 int_value = 3;
double double_value = 4;
ArrayValue array_value = 5;
KeyValueList kvlist_value = 6;
bytes bytes_value = 7;
}
}
// ArrayValue is a list of AnyValue messages. We need ArrayValue as a message
// since oneof in AnyValue does not allow repeated fields.
message ArrayValue {
// Array of values. The array may be empty (contain 0 elements).
repeated AnyValue values = 1;
}
// KeyValueList is a list of KeyValue messages. We need KeyValueList as a message
// since `oneof` in AnyValue does not allow repeated fields. Everywhere else where we need
// a list of KeyValue messages (e.g. in Span) we use `repeated KeyValue` directly to
// avoid unnecessary extra wrapping (which slows down the protocol). The 2 approaches
// are semantically equivalent.
message KeyValueList {
// A collection of key/value pairs of key-value pairs. The list may be empty (may
// contain 0 elements).
// The keys MUST be unique (it is not allowed to have more than one
// value with the same key).
repeated KeyValue values = 1;
}
// KeyValue is a key-value pair that is used to store Span attributes, Link
// attributes, etc.
message KeyValue {
string key = 1;
AnyValue value = 2;
}

661
lib/protoparser/opentelemetry/proto/metrics.proto
View file

@ -1,661 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
syntax = "proto3";
package opentelemetry;
import "lib/protoparser/opentelemetry/proto/common.proto";
import "lib/protoparser/opentelemetry/proto/resource.proto";
option csharp_namespace = "OpenTelemetry.Proto.Metrics.V1";
option java_multiple_files = true;
option java_package = "io.opentelemetry.proto.metrics.v1";
option java_outer_classname = "MetricsProto";
option go_package = "opentelemetry/pb";
// MetricsData represents the metrics data that can be stored in a persistent
// storage, OR can be embedded by other protocols that transfer OTLP metrics
// data but do not implement the OTLP protocol.
//
// The main difference between this message and collector protocol is that
// in this message there will not be any "control" or "metadata" specific to
// OTLP protocol.
//
// When new fields are added into this message, the OTLP request MUST be updated
// as well.
message MetricsData {
// An array of ResourceMetrics.
// For data coming from a single resource this array will typically contain
// one element. Intermediary nodes that receive data from multiple origins
// typically batch the data before forwarding further and in that case this
// array will contain multiple elements.
repeated ResourceMetrics resource_metrics = 1;
}
// A collection of ScopeMetrics from a Resource.
message ResourceMetrics {
reserved 1000;
// The resource for the metrics in this message.
// If this field is not set then no resource info is known.
Resource resource = 1;
// A list of metrics that originate from a resource.
repeated ScopeMetrics scope_metrics = 2;
// This schema_url applies to the data in the "resource" field. It does not apply
// to the data in the "scope_metrics" field which have their own schema_url field.
string schema_url = 3;
}
// A collection of Metrics produced by an Scope.
message ScopeMetrics {
// A list of metrics that originate from an instrumentation library.
repeated Metric metrics = 2;
// This schema_url applies to all metrics in the "metrics" field.
string schema_url = 3;
}
// Defines a Metric which has one or more timeseries. The following is a
// brief summary of the Metric data model. For more details, see:
//
// https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md
//
//
// The data model and relation between entities is shown in the
// diagram below. Here, "DataPoint" is the term used to refer to any
// one of the specific data point value types, and "points" is the term used
// to refer to any one of the lists of points contained in the Metric.
//
// - Metric is composed of a metadata and data.
// - Metadata part contains a name, description, unit.
// - Data is one of the possible types (Sum, Gauge, Histogram, Summary).
// - DataPoint contains timestamps, attributes, and one of the possible value type
// fields.
//
// Metric
// +------------+
// |name |
// |description |
// |unit | +------------------------------------+
// |data |---> |Gauge, Sum, Histogram, Summary, ... |
// +------------+ +------------------------------------+
//
// Data [One of Gauge, Sum, Histogram, Summary, ...]
// +-----------+
// |... | // Metadata about the Data.
// |points |--+
// +-----------+ |
// | +---------------------------+
// | |DataPoint 1 |
// v |+------+------+ +------+ |
// +-----+ ||label |label |...|label | |
// | 1 |-->||value1|value2|...|valueN| |
// +-----+ |+------+------+ +------+ |
// | . | |+-----+ |
// | . | ||value| |
// | . | |+-----+ |
// | . | +---------------------------+
// | . | .
// | . | .
// | . | .
// | . | +---------------------------+
// | . | |DataPoint M |
// +-----+ |+------+------+ +------+ |
// | M |-->||label |label |...|label | |
// +-----+ ||value1|value2|...|valueN| |
// |+------+------+ +------+ |
// |+-----+ |
// ||value| |
// |+-----+ |
// +---------------------------+
//
// Each distinct type of DataPoint represents the output of a specific
// aggregation function, the result of applying the DataPoint's
// associated function of to one or more measurements.
//
// All DataPoint types have three common fields:
// - Attributes includes key-value pairs associated with the data point
// - TimeUnixNano is required, set to the end time of the aggregation
// - StartTimeUnixNano is optional, but strongly encouraged for DataPoints
// having an AggregationTemporality field, as discussed below.
//
// Both TimeUnixNano and StartTimeUnixNano values are expressed as
// UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.
//
// # TimeUnixNano
//
// This field is required, having consistent interpretation across
// DataPoint types. TimeUnixNano is the moment corresponding to when
// the data point's aggregate value was captured.
//
// Data points with the 0 value for TimeUnixNano SHOULD be rejected
// by consumers.
//
// # StartTimeUnixNano
//
// StartTimeUnixNano in general allows detecting when a sequence of
// observations is unbroken. This field indicates to consumers the
// start time for points with cumulative and delta
// AggregationTemporality, and it should be included whenever possible
// to support correct rate calculation. Although it may be omitted
// when the start time is truly unknown, setting StartTimeUnixNano is
// strongly encouraged.
message Metric {
reserved 4, 6, 8;
// name of the metric, including its DNS name prefix. It must be unique.
string name = 1;
// description of the metric, which can be used in documentation.
string description = 2;
// unit in which the metric value is reported. Follows the format
// described by http://unitsofmeasure.org/ucum.html.
string unit = 3;
// Data determines the aggregation type (if any) of the metric, what is the
// reported value type for the data points, as well as the relatationship to
// the time interval over which they are reported.
oneof data {
Gauge gauge = 5;
Sum sum = 7;
Histogram histogram = 9;
ExponentialHistogram exponential_histogram = 10;
Summary summary = 11;
}
}
// Gauge represents the type of a scalar metric that always exports the
// "current value" for every data point. It should be used for an "unknown"
// aggregation.
//
// A Gauge does not support different aggregation temporalities. Given the
// aggregation is unknown, points cannot be combined using the same
// aggregation, regardless of aggregation temporalities. Therefore,
// AggregationTemporality is not included. Consequently, this also means
// "StartTimeUnixNano" is ignored for all data points.
message Gauge {
repeated NumberDataPoint data_points = 1;
}
// Sum represents the type of a scalar metric that is calculated as a sum of all
// reported measurements over a time interval.
message Sum {
repeated NumberDataPoint data_points = 1;
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality aggregation_temporality = 2;
// If "true" means that the sum is monotonic.
bool is_monotonic = 3;
}
// Histogram represents the type of a metric that is calculated by aggregating
// as a Histogram of all reported measurements over a time interval.
message Histogram {
repeated HistogramDataPoint data_points = 1;
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality aggregation_temporality = 2;
}
// ExponentialHistogram represents the type of a metric that is calculated by aggregating
// as a ExponentialHistogram of all reported double measurements over a time interval.
message ExponentialHistogram {
repeated ExponentialHistogramDataPoint data_points = 1;
// aggregation_temporality describes if the aggregator reports delta changes
// since last report time, or cumulative changes since a fixed start time.
AggregationTemporality aggregation_temporality = 2;
}
// Summary metric data are used to convey quantile summaries,
// a Prometheus (see: https://prometheus.io/docs/concepts/metric_types/#summary)
// and OpenMetrics (see: https://github.com/OpenObservability/OpenMetrics/blob/4dbf6075567ab43296eed941037c12951faafb92/protos/prometheus.proto#L45)
// data type. These data points cannot always be merged in a meaningful way.
// While they can be useful in some applications, histogram data points are
// recommended for new applications.
message Summary {
repeated SummaryDataPoint data_points = 1;
}
// AggregationTemporality defines how a metric aggregator reports aggregated
// values. It describes how those values relate to the time interval over
// which they are aggregated.
enum AggregationTemporality {
// UNSPECIFIED is the default AggregationTemporality, it MUST not be used.
AGGREGATION_TEMPORALITY_UNSPECIFIED = 0;
// DELTA is an AggregationTemporality for a metric aggregator which reports
// changes since last report time. Successive metrics contain aggregation of
// values from continuous and non-overlapping intervals.
//
// The values for a DELTA metric are based only on the time interval
// associated with one measurement cycle. There is no dependency on
// previous measurements like is the case for CUMULATIVE metrics.
//
// For example, consider a system measuring the number of requests that
// it receives and reports the sum of these requests every second as a
// DELTA metric:
//
// 1. The system starts receiving at time=t_0.
// 2. A request is received, the system measures 1 request.
// 3. A request is received, the system measures 1 request.
// 4. A request is received, the system measures 1 request.
// 5. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+1 with a value of 3.
// 6. A request is received, the system measures 1 request.
// 7. A request is received, the system measures 1 request.
// 8. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0+1 to
// t_0+2 with a value of 2.
AGGREGATION_TEMPORALITY_DELTA = 1;
// CUMULATIVE is an AggregationTemporality for a metric aggregator which
// reports changes since a fixed start time. This means that current values
// of a CUMULATIVE metric depend on all previous measurements since the
// start time. Because of this, the sender is required to retain this state
// in some form. If this state is lost or invalidated, the CUMULATIVE metric
// values MUST be reset and a new fixed start time following the last
// reported measurement time sent MUST be used.
//
// For example, consider a system measuring the number of requests that
// it receives and reports the sum of these requests every second as a
// CUMULATIVE metric:
//
// 1. The system starts receiving at time=t_0.
// 2. A request is received, the system measures 1 request.
// 3. A request is received, the system measures 1 request.
// 4. A request is received, the system measures 1 request.
// 5. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+1 with a value of 3.
// 6. A request is received, the system measures 1 request.
// 7. A request is received, the system measures 1 request.
// 8. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_0 to
// t_0+2 with a value of 5.
// 9. The system experiences a fault and loses state.
// 10. The system recovers and resumes receiving at time=t_1.
// 11. A request is received, the system measures 1 request.
// 12. The 1 second collection cycle ends. A metric is exported for the
// number of requests received over the interval of time t_1 to
// t_0+1 with a value of 1.
//
// Note: Even though, when reporting changes since last report time, using
// CUMULATIVE is valid, it is not recommended. This may cause problems for
// systems that do not use start_time to determine when the aggregation
// value was reset (e.g. Prometheus).
AGGREGATION_TEMPORALITY_CUMULATIVE = 2;
}
// DataPointFlags is defined as a protobuf 'uint32' type and is to be used as a
// bit-field representing 32 distinct boolean flags. Each flag defined in this
// enum is a bit-mask. To test the presence of a single flag in the flags of
// a data point, for example, use an expression like:
//
// (point.flags & FLAG_NO_RECORDED_VALUE) == FLAG_NO_RECORDED_VALUE
//
enum DataPointFlags {
FLAG_NONE = 0;
// This DataPoint is valid but has no recorded value. This value
// SHOULD be used to reflect explicitly missing data in a series, as
// for an equivalent to the Prometheus "staleness marker".
FLAG_NO_RECORDED_VALUE = 1;
// Bits 2-31 are reserved for future use.
}
// NumberDataPoint is a single data point in a timeseries that describes the
// time-varying scalar value of a metric.
message NumberDataPoint {
reserved 1;
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
repeated KeyValue attributes = 7;
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 start_time_unix_nano = 2;
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 3;
// The value itself. A point is considered invalid when one of the recognized
// value fields is not present inside this oneof.
oneof value {
double as_double = 4;
sfixed64 as_int = 6;
}
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 5;
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
uint32 flags = 8;
}
// HistogramDataPoint is a single data point in a timeseries that describes the
// time-varying values of a Histogram. A Histogram contains summary statistics
// for a population of values, it may optionally contain the distribution of
// those values across a set of buckets.
//
// If the histogram contains the distribution of values, then both
// "explicit_bounds" and "bucket counts" fields must be defined.
// If the histogram does not contain the distribution of values, then both
// "explicit_bounds" and "bucket_counts" must be omitted and only "count" and
// "sum" are known.
message HistogramDataPoint {
reserved 1;
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
repeated KeyValue attributes = 9;
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 start_time_unix_nano = 2;
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 3;
// count is the number of values in the population. Must be non-negative. This
// value must be equal to the sum of the "count" fields in buckets if a
// histogram is provided.
fixed64 count = 4;
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
optional double sum = 5;
// bucket_counts is an optional field contains the count values of histogram
// for each bucket.
//
// The sum of the bucket_counts must equal the value in the count field.
//
// The number of elements in bucket_counts array must be by one greater than
// the number of elements in explicit_bounds array.
repeated fixed64 bucket_counts = 6;
// explicit_bounds specifies buckets with explicitly defined bounds for values.
//
// The boundaries for bucket at index i are:
//
// (-infinity, explicit_bounds[i]] for i == 0
// (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds)
// (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds)
//
// The values in the explicit_bounds array must be strictly increasing.
//
// Histogram buckets are inclusive of their upper boundary, except the last
// bucket where the boundary is at infinity. This format is intentionally
// compatible with the OpenMetrics histogram definition.
repeated double explicit_bounds = 7;
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 8;
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
uint32 flags = 10;
// min is the minimum value over (start_time, end_time].
optional double min = 11;
// max is the maximum value over (start_time, end_time].
optional double max = 12;
}
// ExponentialHistogramDataPoint is a single data point in a timeseries that describes the
// time-varying values of a ExponentialHistogram of double values. A ExponentialHistogram contains
// summary statistics for a population of values, it may optionally contain the
// distribution of those values across a set of buckets.
//
message ExponentialHistogramDataPoint {
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
repeated KeyValue attributes = 1;
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 start_time_unix_nano = 2;
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 3;
// count is the number of values in the population. Must be
// non-negative. This value must be equal to the sum of the "bucket_counts"
// values in the positive and negative Buckets plus the "zero_count" field.
fixed64 count = 4;
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
optional double sum = 5;
// scale describes the resolution of the histogram. Boundaries are
// located at powers of the base, where:
//
// base = (2^(2^-scale))
//
// The histogram bucket identified by `index`, a signed integer,
// contains values that are greater than (base^index) and
// less than or equal to (base^(index+1)).
//
// The positive and negative ranges of the histogram are expressed
// separately. Negative values are mapped by their absolute value
// into the negative range using the same scale as the positive range.
//
// scale is not restricted by the protocol, as the permissible
// values depend on the range of the data.
sint32 scale = 6;
// zero_count is the count of values that are either exactly zero or
// within the region considered zero by the instrumentation at the
// tolerated degree of precision. This bucket stores values that
// cannot be expressed using the standard exponential formula as
// well as values that have been rounded to zero.
//
// Implementations MAY consider the zero bucket to have probability
// mass equal to (zero_count / count).
fixed64 zero_count = 7;
// positive carries the positive range of exponential bucket counts.
Buckets positive = 8;
// negative carries the negative range of exponential bucket counts.
Buckets negative = 9;
// Buckets are a set of bucket counts, encoded in a contiguous array
// of counts.
message Buckets {
// Offset is the bucket index of the first entry in the bucket_counts array.
//
// Note: This uses a varint encoding as a simple form of compression.
sint32 offset = 1;
// Count is an array of counts, where count[i] carries the count
// of the bucket at index (offset+i). count[i] is the count of
// values greater than base^(offset+i) and less or equal to than
// base^(offset+i+1).
//
// Note: By contrast, the explicit HistogramDataPoint uses
// fixed64. This field is expected to have many buckets,
// especially zeros, so uint64 has been selected to ensure
// varint encoding.
repeated uint64 bucket_counts = 2;
}
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
uint32 flags = 10;
// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 11;
// min is the minimum value over (start_time, end_time].
optional double min = 12;
// max is the maximum value over (start_time, end_time].
optional double max = 13;
}
// SummaryDataPoint is a single data point in a timeseries that describes the
// time-varying values of a Summary metric.
message SummaryDataPoint {
reserved 1;
// The set of key/value pairs that uniquely identify the timeseries from
// where this point belongs. The list may be empty (may contain 0 elements).
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
repeated KeyValue attributes = 7;
// StartTimeUnixNano is optional but strongly encouraged, see the
// the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 start_time_unix_nano = 2;
// TimeUnixNano is required, see the detailed comments above Metric.
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 3;
// count is the number of values in the population. Must be non-negative.
fixed64 count = 4;
// sum of the values in the population. If count is zero then this field
// must be zero.
//
// Note: Sum should only be filled out when measuring non-negative discrete
// events, and is assumed to be monotonic over the values of these events.
// Negative events *can* be recorded, but sum should not be filled out when
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#summary
double sum = 5;
// Represents the value at a given quantile of a distribution.
//
// To record Min and Max values following conventions are used:
// - The 1.0 quantile is equivalent to the maximum value observed.
// - The 0.0 quantile is equivalent to the minimum value observed.
//
// See the following issue for more context:
// https://github.com/open-telemetry/opentelemetry-proto/issues/125
message ValueAtQuantile {
// The quantile of a distribution. Must be in the interval
// [0.0, 1.0].
double quantile = 1;
// The value at the given quantile of a distribution.
//
// Quantile values must NOT be negative.
double value = 2;
}
// (Optional) list of values at different quantiles of the distribution calculated
// from the current snapshot. The quantiles must be strictly increasing.
repeated ValueAtQuantile quantile_values = 6;
// Flags that apply to this specific data point. See DataPointFlags
// for the available flags and their meaning.
uint32 flags = 8;
}
// A representation of an exemplar, which is a sample input measurement.
// Exemplars also hold information about the environment when the measurement
// was recorded, for example the span and trace ID of the active span when the
// exemplar was recorded.
message Exemplar {
reserved 1;
// The set of key/value pairs that were filtered out by the aggregator, but
// recorded alongside the original measurement. Only key/value pairs that were
// filtered out by the aggregator should be included
repeated KeyValue filtered_attributes = 7;
// time_unix_nano is the exact time when this exemplar was recorded
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 2;
// The value of the measurement that was recorded. An exemplar is
// considered invalid when one of the recognized value fields is not present
// inside this oneof.
oneof value {
double as_double = 3;
sfixed64 as_int = 6;
}
// (Optional) Span ID of the exemplar trace.
// span_id may be missing if the measurement is not recorded inside a trace
// or if the trace is not sampled.
bytes span_id = 4;
// (Optional) Trace ID of the exemplar trace.
// trace_id may be missing if the measurement is not recorded inside a trace
// or if the trace is not sampled.
bytes trace_id = 5;
}

30
lib/protoparser/opentelemetry/proto/metrics_service.proto
View file

@ -1,30 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
syntax = "proto3";
package opentelemetry;
import "lib/protoparser/opentelemetry/proto/metrics.proto";
option go_package = "opentelemetry/pb";
message ExportMetricsServiceRequest {
// An array of ResourceMetrics.
// For data coming from a single resource this array will typically contain one
// element. Intermediary nodes (such as OpenTelemetry Collector) that receive
// data from multiple origins typically batch the data before forwarding further and
// in that case this array will contain multiple elements.
repeated ResourceMetrics resource_metrics = 1;
}

37
lib/protoparser/opentelemetry/proto/resource.proto
View file

@ -1,37 +0,0 @@
// Copyright 2019, OpenTelemetry 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.
syntax = "proto3";
package opentelemetry;
import "lib/protoparser/opentelemetry/proto/common.proto";
option csharp_namespace = "OpenTelemetry.Proto.Resource.V1";
option java_multiple_files = true;
option java_package = "io.opentelemetry.proto.resource.v1";
option java_outer_classname = "ResourceProto";
option go_package = "opentelemetry/pb";
// Resource information.
message Resource {
// Set of attributes that describe the resource.
// Attribute keys MUST be unique (it is not allowed to have more than one
// attribute with the same key).
repeated KeyValue attributes = 1;
// dropped_attributes_count is the number of dropped attributes. If the value is 0, then
// no attributes were dropped.
uint32 dropped_attributes_count = 2;
}

36
lib/protoparser/opentelemetry/stream/streamparser.go
View file

@ -56,34 +56,34 @@ func (wr *writeContext) appendSamplesFromScopeMetrics(sc *pb.ScopeMetrics) {
// skip metrics without names // skip metrics without names
continue continue
} }
switch t := m.Data.(type) { switch {
case *pb.Metric_Gauge: case m.Gauge != nil:
for _, p := range t.Gauge.DataPoints { for _, p := range m.Gauge.DataPoints {
wr.appendSampleFromNumericPoint(m.Name, p) wr.appendSampleFromNumericPoint(m.Name, p)
} }
case *pb.Metric_Sum: case m.Sum != nil:
if t.Sum.AggregationTemporality != pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE { if m.Sum.AggregationTemporality != pb.AggregationTemporalityCumulative {
rowsDroppedUnsupportedSum.Inc() rowsDroppedUnsupportedSum.Inc()
continue continue
} }
for _, p := range t.Sum.DataPoints { for _, p := range m.Sum.DataPoints {
wr.appendSampleFromNumericPoint(m.Name, p) wr.appendSampleFromNumericPoint(m.Name, p)
} }
case *pb.Metric_Summary: case m.Summary != nil:
for _, p := range t.Summary.DataPoints { for _, p := range m.Summary.DataPoints {
wr.appendSamplesFromSummary(m.Name, p) wr.appendSamplesFromSummary(m.Name, p)
} }
case *pb.Metric_Histogram: case m.Histogram != nil:
if t.Histogram.AggregationTemporality != pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE { if m.Histogram.AggregationTemporality != pb.AggregationTemporalityCumulative {
rowsDroppedUnsupportedHistogram.Inc() rowsDroppedUnsupportedHistogram.Inc()
continue continue
} }
for _, p := range t.Histogram.DataPoints { for _, p := range m.Histogram.DataPoints {
wr.appendSamplesFromHistogram(m.Name, p) wr.appendSamplesFromHistogram(m.Name, p)
} }
default: default:
rowsDroppedUnsupportedMetricType.Inc() rowsDroppedUnsupportedMetricType.Inc()
logger.Warnf("unsupported type %T for metric %q", t, m.Name) logger.Warnf("unsupported type for metric %q", m.Name)
} }
} }
} }
@ -91,11 +91,11 @@ func (wr *writeContext) appendSamplesFromScopeMetrics(sc *pb.ScopeMetrics) {
// appendSampleFromNumericPoint appends p to wr.tss // appendSampleFromNumericPoint appends p to wr.tss
func (wr *writeContext) appendSampleFromNumericPoint(metricName string, p *pb.NumberDataPoint) { func (wr *writeContext) appendSampleFromNumericPoint(metricName string, p *pb.NumberDataPoint) {
var v float64 var v float64
switch t := p.Value.(type) { switch {
case *pb.NumberDataPoint_AsInt: case p.IntValue != nil:
v = float64(t.AsInt) v = float64(*p.IntValue)
case *pb.NumberDataPoint_AsDouble: case p.DoubleValue != nil:
v = t.AsDouble v = *p.DoubleValue
} }
t := int64(p.TimeUnixNano / 1e6) t := int64(p.TimeUnixNano / 1e6)
@ -264,7 +264,7 @@ func (wr *writeContext) readAndUnpackRequest(r io.Reader) (*pb.ExportMetricsServ
return nil, fmt.Errorf("cannot read request: %w", err) return nil, fmt.Errorf("cannot read request: %w", err)
} }
var req pb.ExportMetricsServiceRequest var req pb.ExportMetricsServiceRequest
if err := req.UnmarshalVT(wr.bb.B); err != nil { if err := req.UnmarshalProtobuf(wr.bb.B); err != nil {
return nil, fmt.Errorf("cannot unmarshal request from %d bytes: %w", len(wr.bb.B), err) return nil, fmt.Errorf("cannot unmarshal request from %d bytes: %w", len(wr.bb.B), err)
} }
return &req, nil return &req, nil

45
lib/protoparser/opentelemetry/stream/streamparser_test.go
View file

@ -60,10 +60,7 @@ func TestParseStream(t *testing.T) {
} }
// Verify protobuf parsing // Verify protobuf parsing
pbData, err := req.MarshalVT() pbData := req.MarshalProtobuf(nil)
if err != nil {
t.Fatalf("cannot marshal to protobuf: %s", err)
}
if err := checkParseStream(pbData, checkSeries); err != nil { if err := checkParseStream(pbData, checkSeries); err != nil {
t.Fatalf("cannot parse protobuf: %s", err) t.Fatalf("cannot parse protobuf: %s", err)
} }
@ -149,28 +146,25 @@ func attributesFromKV(k, v string) []*pb.KeyValue {
{ {
Key: k, Key: k,
Value: &pb.AnyValue{ Value: &pb.AnyValue{
Value: &pb.AnyValue_StringValue{ StringValue: &v,
StringValue: v,
},
}, },
}, },
} }
} }
func generateGauge(name string) *pb.Metric { func generateGauge(name string) *pb.Metric {
n := int64(15)
points := []*pb.NumberDataPoint{ points := []*pb.NumberDataPoint{
{ {
Attributes: attributesFromKV("label1", "value1"), Attributes: attributesFromKV("label1", "value1"),
Value: &pb.NumberDataPoint_AsInt{AsInt: 15}, IntValue: &n,
TimeUnixNano: uint64(15 * time.Second), TimeUnixNano: uint64(15 * time.Second),
}, },
} }
return &pb.Metric{ return &pb.Metric{
Name: name, Name: name,
Data: &pb.Metric_Gauge{ Gauge: &pb.Gauge{
Gauge: &pb.Gauge{ DataPoints: points,
DataPoints: points,
},
}, },
} }
} }
@ -189,30 +183,27 @@ func generateHistogram(name string) *pb.Metric {
} }
return &pb.Metric{ return &pb.Metric{
Name: name, Name: name,
Data: &pb.Metric_Histogram{ Histogram: &pb.Histogram{
Histogram: &pb.Histogram{ AggregationTemporality: pb.AggregationTemporalityCumulative,
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE, DataPoints: points,
DataPoints: points,
},
}, },
} }
} }
func generateSum(name string) *pb.Metric { func generateSum(name string) *pb.Metric {
d := float64(15.5)
points := []*pb.NumberDataPoint{ points := []*pb.NumberDataPoint{
{ {
Attributes: attributesFromKV("label5", "value5"), Attributes: attributesFromKV("label5", "value5"),
Value: &pb.NumberDataPoint_AsDouble{AsDouble: 15.5}, DoubleValue: &d,
TimeUnixNano: uint64(150 * time.Second), TimeUnixNano: uint64(150 * time.Second),
}, },
} }
return &pb.Metric{ return &pb.Metric{
Name: name, Name: name,
Data: &pb.Metric_Sum{ Sum: &pb.Sum{
Sum: &pb.Sum{ AggregationTemporality: pb.AggregationTemporalityCumulative,
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE, DataPoints: points,
DataPoints: points,
},
}, },
} }
} }
@ -224,7 +215,7 @@ func generateSummary(name string) *pb.Metric {
TimeUnixNano: uint64(35 * time.Second), TimeUnixNano: uint64(35 * time.Second),
Sum: 32.5, Sum: 32.5,
Count: 5, Count: 5,
QuantileValues: []*pb.SummaryDataPoint_ValueAtQuantile{ QuantileValues: []*pb.ValueAtQuantile{
{ {
Quantile: 0.1, Quantile: 0.1,
Value: 7.5, Value: 7.5,
@ -242,10 +233,8 @@ func generateSummary(name string) *pb.Metric {
} }
return &pb.Metric{ return &pb.Metric{
Name: name, Name: name,
Data: &pb.Metric_Summary{ Summary: &pb.Summary{
Summary: &pb.Summary{ DataPoints: points,
DataPoints: points,
},
}, },
} }
} }

5
lib/protoparser/opentelemetry/stream/streamparser_timing_test.go
View file

@ -21,10 +21,7 @@ func BenchmarkParseStream(b *testing.B) {
pbRequest := pb.ExportMetricsServiceRequest{ pbRequest := pb.ExportMetricsServiceRequest{
ResourceMetrics: []*pb.ResourceMetrics{generateOTLPSamples(samples)}, ResourceMetrics: []*pb.ResourceMetrics{generateOTLPSamples(samples)},
} }
data, err := pbRequest.MarshalVT() data := pbRequest.MarshalProtobuf(nil)
if err != nil {
b.Fatalf("cannot marshal data: %s", err)
}
for p.Next() { for p.Next() {
err := ParseStream(bytes.NewBuffer(data), false, func(tss []prompbmarshal.TimeSeries) error { err := ParseStream(bytes.NewBuffer(data), false, func(tss []prompbmarshal.TimeSeries) error {