/usr/share/gocode/src/google.golang.org/genproto/googleapis/monitoring/v3/common.pb.go is in golang-google-genproto-dev 0.0~git20171123.7f0da29-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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// source: google/monitoring/v3/common.proto
/*
Package monitoring is a generated protocol buffer package.
It is generated from these files:
google/monitoring/v3/common.proto
google/monitoring/v3/group.proto
google/monitoring/v3/group_service.proto
google/monitoring/v3/metric.proto
google/monitoring/v3/metric_service.proto
It has these top-level messages:
TypedValue
TimeInterval
Aggregation
Group
ListGroupsRequest
ListGroupsResponse
GetGroupRequest
CreateGroupRequest
UpdateGroupRequest
DeleteGroupRequest
ListGroupMembersRequest
ListGroupMembersResponse
Point
TimeSeries
ListMonitoredResourceDescriptorsRequest
ListMonitoredResourceDescriptorsResponse
GetMonitoredResourceDescriptorRequest
ListMetricDescriptorsRequest
ListMetricDescriptorsResponse
GetMetricDescriptorRequest
CreateMetricDescriptorRequest
DeleteMetricDescriptorRequest
ListTimeSeriesRequest
ListTimeSeriesResponse
CreateTimeSeriesRequest
CreateTimeSeriesError
*/
package monitoring
import proto "github.com/golang/protobuf/proto"
import fmt "fmt"
import math "math"
import google_api2 "google.golang.org/genproto/googleapis/api/distribution"
import google_protobuf3 "github.com/golang/protobuf/ptypes/duration"
import google_protobuf2 "github.com/golang/protobuf/ptypes/timestamp"
// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fmt.Errorf
var _ = math.Inf
// This is a compile-time assertion to ensure that this generated file
// is compatible with the proto package it is being compiled against.
// A compilation error at this line likely means your copy of the
// proto package needs to be updated.
const _ = proto.ProtoPackageIsVersion2 // please upgrade the proto package
// The Aligner describes how to bring the data points in a single
// time series into temporal alignment.
type Aggregation_Aligner int32
const (
// No alignment. Raw data is returned. Not valid if cross-time
// series reduction is requested. The value type of the result is
// the same as the value type of the input.
Aggregation_ALIGN_NONE Aggregation_Aligner = 0
// Align and convert to delta metric type. This alignment is valid
// for cumulative metrics and delta metrics. Aligning an existing
// delta metric to a delta metric requires that the alignment
// period be increased. The value type of the result is the same
// as the value type of the input.
Aggregation_ALIGN_DELTA Aggregation_Aligner = 1
// Align and convert to a rate. This alignment is valid for
// cumulative metrics and delta metrics with numeric values. The output is a
// gauge metric with value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_RATE Aggregation_Aligner = 2
// Align by interpolating between adjacent points around the
// period boundary. This alignment is valid for gauge
// metrics with numeric values. The value type of the result is the same
// as the value type of the input.
Aggregation_ALIGN_INTERPOLATE Aggregation_Aligner = 3
// Align by shifting the oldest data point before the period
// boundary to the boundary. This alignment is valid for gauge
// metrics. The value type of the result is the same as the
// value type of the input.
Aggregation_ALIGN_NEXT_OLDER Aggregation_Aligner = 4
// Align time series via aggregation. The resulting data point in
// the alignment period is the minimum of all data points in the
// period. This alignment is valid for gauge and delta metrics with numeric
// values. The value type of the result is the same as the value
// type of the input.
Aggregation_ALIGN_MIN Aggregation_Aligner = 10
// Align time series via aggregation. The resulting data point in
// the alignment period is the maximum of all data points in the
// period. This alignment is valid for gauge and delta metrics with numeric
// values. The value type of the result is the same as the value
// type of the input.
Aggregation_ALIGN_MAX Aggregation_Aligner = 11
// Align time series via aggregation. The resulting data point in
// the alignment period is the average or arithmetic mean of all
// data points in the period. This alignment is valid for gauge and delta
// metrics with numeric values. The value type of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_MEAN Aggregation_Aligner = 12
// Align time series via aggregation. The resulting data point in
// the alignment period is the count of all data points in the
// period. This alignment is valid for gauge and delta metrics with numeric
// or Boolean values. The value type of the output is
// [INT64][google.api.MetricDescriptor.ValueType.INT64].
Aggregation_ALIGN_COUNT Aggregation_Aligner = 13
// Align time series via aggregation. The resulting data point in
// the alignment period is the sum of all data points in the
// period. This alignment is valid for gauge and delta metrics with numeric
// and distribution values. The value type of the output is the
// same as the value type of the input.
Aggregation_ALIGN_SUM Aggregation_Aligner = 14
// Align time series via aggregation. The resulting data point in
// the alignment period is the standard deviation of all data
// points in the period. This alignment is valid for gauge and delta metrics
// with numeric values. The value type of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_STDDEV Aggregation_Aligner = 15
// Align time series via aggregation. The resulting data point in
// the alignment period is the count of True-valued data points in the
// period. This alignment is valid for gauge metrics with
// Boolean values. The value type of the output is
// [INT64][google.api.MetricDescriptor.ValueType.INT64].
Aggregation_ALIGN_COUNT_TRUE Aggregation_Aligner = 16
// Align time series via aggregation. The resulting data point in
// the alignment period is the fraction of True-valued data points in the
// period. This alignment is valid for gauge metrics with Boolean values.
// The output value is in the range [0, 1] and has value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_FRACTION_TRUE Aggregation_Aligner = 17
// Align time series via aggregation. The resulting data point in
// the alignment period is the 99th percentile of all data
// points in the period. This alignment is valid for gauge and delta metrics
// with distribution values. The output is a gauge metric with value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_PERCENTILE_99 Aggregation_Aligner = 18
// Align time series via aggregation. The resulting data point in
// the alignment period is the 95th percentile of all data
// points in the period. This alignment is valid for gauge and delta metrics
// with distribution values. The output is a gauge metric with value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_PERCENTILE_95 Aggregation_Aligner = 19
// Align time series via aggregation. The resulting data point in
// the alignment period is the 50th percentile of all data
// points in the period. This alignment is valid for gauge and delta metrics
// with distribution values. The output is a gauge metric with value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_PERCENTILE_50 Aggregation_Aligner = 20
// Align time series via aggregation. The resulting data point in
// the alignment period is the 5th percentile of all data
// points in the period. This alignment is valid for gauge and delta metrics
// with distribution values. The output is a gauge metric with value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_ALIGN_PERCENTILE_05 Aggregation_Aligner = 21
)
var Aggregation_Aligner_name = map[int32]string{
0: "ALIGN_NONE",
1: "ALIGN_DELTA",
2: "ALIGN_RATE",
3: "ALIGN_INTERPOLATE",
4: "ALIGN_NEXT_OLDER",
10: "ALIGN_MIN",
11: "ALIGN_MAX",
12: "ALIGN_MEAN",
13: "ALIGN_COUNT",
14: "ALIGN_SUM",
15: "ALIGN_STDDEV",
16: "ALIGN_COUNT_TRUE",
17: "ALIGN_FRACTION_TRUE",
18: "ALIGN_PERCENTILE_99",
19: "ALIGN_PERCENTILE_95",
20: "ALIGN_PERCENTILE_50",
21: "ALIGN_PERCENTILE_05",
}
var Aggregation_Aligner_value = map[string]int32{
"ALIGN_NONE": 0,
"ALIGN_DELTA": 1,
"ALIGN_RATE": 2,
"ALIGN_INTERPOLATE": 3,
"ALIGN_NEXT_OLDER": 4,
"ALIGN_MIN": 10,
"ALIGN_MAX": 11,
"ALIGN_MEAN": 12,
"ALIGN_COUNT": 13,
"ALIGN_SUM": 14,
"ALIGN_STDDEV": 15,
"ALIGN_COUNT_TRUE": 16,
"ALIGN_FRACTION_TRUE": 17,
"ALIGN_PERCENTILE_99": 18,
"ALIGN_PERCENTILE_95": 19,
"ALIGN_PERCENTILE_50": 20,
"ALIGN_PERCENTILE_05": 21,
}
func (x Aggregation_Aligner) String() string {
return proto.EnumName(Aggregation_Aligner_name, int32(x))
}
func (Aggregation_Aligner) EnumDescriptor() ([]byte, []int) { return fileDescriptor0, []int{2, 0} }
// A Reducer describes how to aggregate data points from multiple
// time series into a single time series.
type Aggregation_Reducer int32
const (
// No cross-time series reduction. The output of the aligner is
// returned.
Aggregation_REDUCE_NONE Aggregation_Reducer = 0
// Reduce by computing the mean across time series for each
// alignment period. This reducer is valid for delta and
// gauge metrics with numeric or distribution values. The value type of the
// output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_REDUCE_MEAN Aggregation_Reducer = 1
// Reduce by computing the minimum across time series for each
// alignment period. This reducer is valid for delta and
// gauge metrics with numeric values. The value type of the output
// is the same as the value type of the input.
Aggregation_REDUCE_MIN Aggregation_Reducer = 2
// Reduce by computing the maximum across time series for each
// alignment period. This reducer is valid for delta and
// gauge metrics with numeric values. The value type of the output
// is the same as the value type of the input.
Aggregation_REDUCE_MAX Aggregation_Reducer = 3
// Reduce by computing the sum across time series for each
// alignment period. This reducer is valid for delta and
// gauge metrics with numeric and distribution values. The value type of
// the output is the same as the value type of the input.
Aggregation_REDUCE_SUM Aggregation_Reducer = 4
// Reduce by computing the standard deviation across time series
// for each alignment period. This reducer is valid for delta
// and gauge metrics with numeric or distribution values. The value type of
// the output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_REDUCE_STDDEV Aggregation_Reducer = 5
// Reduce by computing the count of data points across time series
// for each alignment period. This reducer is valid for delta
// and gauge metrics of numeric, Boolean, distribution, and string value
// type. The value type of the output is
// [INT64][google.api.MetricDescriptor.ValueType.INT64].
Aggregation_REDUCE_COUNT Aggregation_Reducer = 6
// Reduce by computing the count of True-valued data points across time
// series for each alignment period. This reducer is valid for delta
// and gauge metrics of Boolean value type. The value type of
// the output is [INT64][google.api.MetricDescriptor.ValueType.INT64].
Aggregation_REDUCE_COUNT_TRUE Aggregation_Reducer = 7
// Reduce by computing the fraction of True-valued data points across time
// series for each alignment period. This reducer is valid for delta
// and gauge metrics of Boolean value type. The output value is in the
// range [0, 1] and has value type
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
Aggregation_REDUCE_FRACTION_TRUE Aggregation_Reducer = 8
// Reduce by computing 99th percentile of data points across time series
// for each alignment period. This reducer is valid for gauge and delta
// metrics of numeric and distribution type. The value of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]
Aggregation_REDUCE_PERCENTILE_99 Aggregation_Reducer = 9
// Reduce by computing 95th percentile of data points across time series
// for each alignment period. This reducer is valid for gauge and delta
// metrics of numeric and distribution type. The value of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]
Aggregation_REDUCE_PERCENTILE_95 Aggregation_Reducer = 10
// Reduce by computing 50th percentile of data points across time series
// for each alignment period. This reducer is valid for gauge and delta
// metrics of numeric and distribution type. The value of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]
Aggregation_REDUCE_PERCENTILE_50 Aggregation_Reducer = 11
// Reduce by computing 5th percentile of data points across time series
// for each alignment period. This reducer is valid for gauge and delta
// metrics of numeric and distribution type. The value of the output is
// [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]
Aggregation_REDUCE_PERCENTILE_05 Aggregation_Reducer = 12
)
var Aggregation_Reducer_name = map[int32]string{
0: "REDUCE_NONE",
1: "REDUCE_MEAN",
2: "REDUCE_MIN",
3: "REDUCE_MAX",
4: "REDUCE_SUM",
5: "REDUCE_STDDEV",
6: "REDUCE_COUNT",
7: "REDUCE_COUNT_TRUE",
8: "REDUCE_FRACTION_TRUE",
9: "REDUCE_PERCENTILE_99",
10: "REDUCE_PERCENTILE_95",
11: "REDUCE_PERCENTILE_50",
12: "REDUCE_PERCENTILE_05",
}
var Aggregation_Reducer_value = map[string]int32{
"REDUCE_NONE": 0,
"REDUCE_MEAN": 1,
"REDUCE_MIN": 2,
"REDUCE_MAX": 3,
"REDUCE_SUM": 4,
"REDUCE_STDDEV": 5,
"REDUCE_COUNT": 6,
"REDUCE_COUNT_TRUE": 7,
"REDUCE_FRACTION_TRUE": 8,
"REDUCE_PERCENTILE_99": 9,
"REDUCE_PERCENTILE_95": 10,
"REDUCE_PERCENTILE_50": 11,
"REDUCE_PERCENTILE_05": 12,
}
func (x Aggregation_Reducer) String() string {
return proto.EnumName(Aggregation_Reducer_name, int32(x))
}
func (Aggregation_Reducer) EnumDescriptor() ([]byte, []int) { return fileDescriptor0, []int{2, 1} }
// A single strongly-typed value.
type TypedValue struct {
// The typed value field.
//
// Types that are valid to be assigned to Value:
// *TypedValue_BoolValue
// *TypedValue_Int64Value
// *TypedValue_DoubleValue
// *TypedValue_StringValue
// *TypedValue_DistributionValue
Value isTypedValue_Value `protobuf_oneof:"value"`
}
func (m *TypedValue) Reset() { *m = TypedValue{} }
func (m *TypedValue) String() string { return proto.CompactTextString(m) }
func (*TypedValue) ProtoMessage() {}
func (*TypedValue) Descriptor() ([]byte, []int) { return fileDescriptor0, []int{0} }
type isTypedValue_Value interface {
isTypedValue_Value()
}
type TypedValue_BoolValue struct {
BoolValue bool `protobuf:"varint,1,opt,name=bool_value,json=boolValue,oneof"`
}
type TypedValue_Int64Value struct {
Int64Value int64 `protobuf:"varint,2,opt,name=int64_value,json=int64Value,oneof"`
}
type TypedValue_DoubleValue struct {
DoubleValue float64 `protobuf:"fixed64,3,opt,name=double_value,json=doubleValue,oneof"`
}
type TypedValue_StringValue struct {
StringValue string `protobuf:"bytes,4,opt,name=string_value,json=stringValue,oneof"`
}
type TypedValue_DistributionValue struct {
DistributionValue *google_api2.Distribution `protobuf:"bytes,5,opt,name=distribution_value,json=distributionValue,oneof"`
}
func (*TypedValue_BoolValue) isTypedValue_Value() {}
func (*TypedValue_Int64Value) isTypedValue_Value() {}
func (*TypedValue_DoubleValue) isTypedValue_Value() {}
func (*TypedValue_StringValue) isTypedValue_Value() {}
func (*TypedValue_DistributionValue) isTypedValue_Value() {}
func (m *TypedValue) GetValue() isTypedValue_Value {
if m != nil {
return m.Value
}
return nil
}
func (m *TypedValue) GetBoolValue() bool {
if x, ok := m.GetValue().(*TypedValue_BoolValue); ok {
return x.BoolValue
}
return false
}
func (m *TypedValue) GetInt64Value() int64 {
if x, ok := m.GetValue().(*TypedValue_Int64Value); ok {
return x.Int64Value
}
return 0
}
func (m *TypedValue) GetDoubleValue() float64 {
if x, ok := m.GetValue().(*TypedValue_DoubleValue); ok {
return x.DoubleValue
}
return 0
}
func (m *TypedValue) GetStringValue() string {
if x, ok := m.GetValue().(*TypedValue_StringValue); ok {
return x.StringValue
}
return ""
}
func (m *TypedValue) GetDistributionValue() *google_api2.Distribution {
if x, ok := m.GetValue().(*TypedValue_DistributionValue); ok {
return x.DistributionValue
}
return nil
}
// XXX_OneofFuncs is for the internal use of the proto package.
func (*TypedValue) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{}) {
return _TypedValue_OneofMarshaler, _TypedValue_OneofUnmarshaler, _TypedValue_OneofSizer, []interface{}{
(*TypedValue_BoolValue)(nil),
(*TypedValue_Int64Value)(nil),
(*TypedValue_DoubleValue)(nil),
(*TypedValue_StringValue)(nil),
(*TypedValue_DistributionValue)(nil),
}
}
func _TypedValue_OneofMarshaler(msg proto.Message, b *proto.Buffer) error {
m := msg.(*TypedValue)
// value
switch x := m.Value.(type) {
case *TypedValue_BoolValue:
t := uint64(0)
if x.BoolValue {
t = 1
}
b.EncodeVarint(1<<3 | proto.WireVarint)
b.EncodeVarint(t)
case *TypedValue_Int64Value:
b.EncodeVarint(2<<3 | proto.WireVarint)
b.EncodeVarint(uint64(x.Int64Value))
case *TypedValue_DoubleValue:
b.EncodeVarint(3<<3 | proto.WireFixed64)
b.EncodeFixed64(math.Float64bits(x.DoubleValue))
case *TypedValue_StringValue:
b.EncodeVarint(4<<3 | proto.WireBytes)
b.EncodeStringBytes(x.StringValue)
case *TypedValue_DistributionValue:
b.EncodeVarint(5<<3 | proto.WireBytes)
if err := b.EncodeMessage(x.DistributionValue); err != nil {
return err
}
case nil:
default:
return fmt.Errorf("TypedValue.Value has unexpected type %T", x)
}
return nil
}
func _TypedValue_OneofUnmarshaler(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error) {
m := msg.(*TypedValue)
switch tag {
case 1: // value.bool_value
if wire != proto.WireVarint {
return true, proto.ErrInternalBadWireType
}
x, err := b.DecodeVarint()
m.Value = &TypedValue_BoolValue{x != 0}
return true, err
case 2: // value.int64_value
if wire != proto.WireVarint {
return true, proto.ErrInternalBadWireType
}
x, err := b.DecodeVarint()
m.Value = &TypedValue_Int64Value{int64(x)}
return true, err
case 3: // value.double_value
if wire != proto.WireFixed64 {
return true, proto.ErrInternalBadWireType
}
x, err := b.DecodeFixed64()
m.Value = &TypedValue_DoubleValue{math.Float64frombits(x)}
return true, err
case 4: // value.string_value
if wire != proto.WireBytes {
return true, proto.ErrInternalBadWireType
}
x, err := b.DecodeStringBytes()
m.Value = &TypedValue_StringValue{x}
return true, err
case 5: // value.distribution_value
if wire != proto.WireBytes {
return true, proto.ErrInternalBadWireType
}
msg := new(google_api2.Distribution)
err := b.DecodeMessage(msg)
m.Value = &TypedValue_DistributionValue{msg}
return true, err
default:
return false, nil
}
}
func _TypedValue_OneofSizer(msg proto.Message) (n int) {
m := msg.(*TypedValue)
// value
switch x := m.Value.(type) {
case *TypedValue_BoolValue:
n += proto.SizeVarint(1<<3 | proto.WireVarint)
n += 1
case *TypedValue_Int64Value:
n += proto.SizeVarint(2<<3 | proto.WireVarint)
n += proto.SizeVarint(uint64(x.Int64Value))
case *TypedValue_DoubleValue:
n += proto.SizeVarint(3<<3 | proto.WireFixed64)
n += 8
case *TypedValue_StringValue:
n += proto.SizeVarint(4<<3 | proto.WireBytes)
n += proto.SizeVarint(uint64(len(x.StringValue)))
n += len(x.StringValue)
case *TypedValue_DistributionValue:
s := proto.Size(x.DistributionValue)
n += proto.SizeVarint(5<<3 | proto.WireBytes)
n += proto.SizeVarint(uint64(s))
n += s
case nil:
default:
panic(fmt.Sprintf("proto: unexpected type %T in oneof", x))
}
return n
}
// A time interval extending just after a start time through an end time.
// If the start time is the same as the end time, then the interval
// represents a single point in time.
type TimeInterval struct {
// Required. The end of the time interval.
EndTime *google_protobuf2.Timestamp `protobuf:"bytes,2,opt,name=end_time,json=endTime" json:"end_time,omitempty"`
// Optional. The beginning of the time interval. The default value
// for the start time is the end time. The start time must not be
// later than the end time.
StartTime *google_protobuf2.Timestamp `protobuf:"bytes,1,opt,name=start_time,json=startTime" json:"start_time,omitempty"`
}
func (m *TimeInterval) Reset() { *m = TimeInterval{} }
func (m *TimeInterval) String() string { return proto.CompactTextString(m) }
func (*TimeInterval) ProtoMessage() {}
func (*TimeInterval) Descriptor() ([]byte, []int) { return fileDescriptor0, []int{1} }
func (m *TimeInterval) GetEndTime() *google_protobuf2.Timestamp {
if m != nil {
return m.EndTime
}
return nil
}
func (m *TimeInterval) GetStartTime() *google_protobuf2.Timestamp {
if m != nil {
return m.StartTime
}
return nil
}
// Describes how to combine multiple time series to provide different views of
// the data. Aggregation consists of an alignment step on individual time
// series (`per_series_aligner`) followed by an optional reduction of the data
// across different time series (`cross_series_reducer`). For more details, see
// [Aggregation](/monitoring/api/learn_more#aggregation).
type Aggregation struct {
// The alignment period for per-[time series][google.monitoring.v3.TimeSeries]
// alignment. If present, `alignmentPeriod` must be at least 60
// seconds. After per-time series alignment, each time series will
// contain data points only on the period boundaries. If
// `perSeriesAligner` is not specified or equals `ALIGN_NONE`, then
// this field is ignored. If `perSeriesAligner` is specified and
// does not equal `ALIGN_NONE`, then this field must be defined;
// otherwise an error is returned.
AlignmentPeriod *google_protobuf3.Duration `protobuf:"bytes,1,opt,name=alignment_period,json=alignmentPeriod" json:"alignment_period,omitempty"`
// The approach to be used to align individual time series. Not all
// alignment functions may be applied to all time series, depending
// on the metric type and value type of the original time
// series. Alignment may change the metric type or the value type of
// the time series.
//
// Time series data must be aligned in order to perform cross-time
// series reduction. If `crossSeriesReducer` is specified, then
// `perSeriesAligner` must be specified and not equal `ALIGN_NONE`
// and `alignmentPeriod` must be specified; otherwise, an error is
// returned.
PerSeriesAligner Aggregation_Aligner `protobuf:"varint,2,opt,name=per_series_aligner,json=perSeriesAligner,enum=google.monitoring.v3.Aggregation_Aligner" json:"per_series_aligner,omitempty"`
// The approach to be used to combine time series. Not all reducer
// functions may be applied to all time series, depending on the
// metric type and the value type of the original time
// series. Reduction may change the metric type of value type of the
// time series.
//
// Time series data must be aligned in order to perform cross-time
// series reduction. If `crossSeriesReducer` is specified, then
// `perSeriesAligner` must be specified and not equal `ALIGN_NONE`
// and `alignmentPeriod` must be specified; otherwise, an error is
// returned.
CrossSeriesReducer Aggregation_Reducer `protobuf:"varint,4,opt,name=cross_series_reducer,json=crossSeriesReducer,enum=google.monitoring.v3.Aggregation_Reducer" json:"cross_series_reducer,omitempty"`
// The set of fields to preserve when `crossSeriesReducer` is
// specified. The `groupByFields` determine how the time series are
// partitioned into subsets prior to applying the aggregation
// function. Each subset contains time series that have the same
// value for each of the grouping fields. Each individual time
// series is a member of exactly one subset. The
// `crossSeriesReducer` is applied to each subset of time series.
// It is not possible to reduce across different resource types, so
// this field implicitly contains `resource.type`. Fields not
// specified in `groupByFields` are aggregated away. If
// `groupByFields` is not specified and all the time series have
// the same resource type, then the time series are aggregated into
// a single output time series. If `crossSeriesReducer` is not
// defined, this field is ignored.
GroupByFields []string `protobuf:"bytes,5,rep,name=group_by_fields,json=groupByFields" json:"group_by_fields,omitempty"`
}
func (m *Aggregation) Reset() { *m = Aggregation{} }
func (m *Aggregation) String() string { return proto.CompactTextString(m) }
func (*Aggregation) ProtoMessage() {}
func (*Aggregation) Descriptor() ([]byte, []int) { return fileDescriptor0, []int{2} }
func (m *Aggregation) GetAlignmentPeriod() *google_protobuf3.Duration {
if m != nil {
return m.AlignmentPeriod
}
return nil
}
func (m *Aggregation) GetPerSeriesAligner() Aggregation_Aligner {
if m != nil {
return m.PerSeriesAligner
}
return Aggregation_ALIGN_NONE
}
func (m *Aggregation) GetCrossSeriesReducer() Aggregation_Reducer {
if m != nil {
return m.CrossSeriesReducer
}
return Aggregation_REDUCE_NONE
}
func (m *Aggregation) GetGroupByFields() []string {
if m != nil {
return m.GroupByFields
}
return nil
}
func init() {
proto.RegisterType((*TypedValue)(nil), "google.monitoring.v3.TypedValue")
proto.RegisterType((*TimeInterval)(nil), "google.monitoring.v3.TimeInterval")
proto.RegisterType((*Aggregation)(nil), "google.monitoring.v3.Aggregation")
proto.RegisterEnum("google.monitoring.v3.Aggregation_Aligner", Aggregation_Aligner_name, Aggregation_Aligner_value)
proto.RegisterEnum("google.monitoring.v3.Aggregation_Reducer", Aggregation_Reducer_name, Aggregation_Reducer_value)
}
func init() { proto.RegisterFile("google/monitoring/v3/common.proto", fileDescriptor0) }
var fileDescriptor0 = []byte{
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