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prw2.0: Added support for "custom" layouts for native histogram proto (#13558)

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* prw2.0: Added support for "custom" layouts for native histogram.

Result of the discussions:
* https://github.com/prometheus/prometheus/issues/13475#issuecomment-1931496924
* https://cloud-native.slack.com/archives/C02KR205UMU/p1707301006347199

Signed-off-by: bwplotka <bwplotka@gmail.com>

* prw2.0: Added support for "custom" layouts for native histogram.

Result of the discussions:
* https://github.com/prometheus/prometheus/issues/13475#issuecomment-1931496924
* https://cloud-native.slack.com/archives/C02KR205UMU/p1707301006347199

Signed-off-by: bwplotka <bwplotka@gmail.com>

# Conflicts:
#	prompb/write/v2/types.pb.go

* Update prompb/write/v2/types.proto

Co-authored-by: George Krajcsovits <krajorama@users.noreply.github.com>
Signed-off-by: Bartlomiej Plotka <bwplotka@gmail.com>

* Addressed comments, fixed test.

Signed-off-by: bwplotka <bwplotka@gmail.com>

---------

Signed-off-by: bwplotka <bwplotka@gmail.com>
Signed-off-by: Bartlomiej Plotka <bwplotka@gmail.com>
Co-authored-by: George Krajcsovits <krajorama@users.noreply.github.com>
This commit is contained in:
Bartlomiej Plotka 2024-03-14 14:47:25 +01:00 committed by GitHub
parent ae414a3e6b
commit 0eae349b78
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GPG key ID: B5690EEEBB952194
3 changed files with 264 additions and 110 deletions
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4
prompb/write/v2/custom.go
View file

@ -113,7 +113,7 @@ func (m *TimeSeries) OptimizedMarshalToSizedBuffer(dAtA []byte) (int, error) {
i = encodeVarintTypes(dAtA, i, uint64(size)) i = encodeVarintTypes(dAtA, i, uint64(size))
} }
i-- i--
dAtA[i] = 0x22 dAtA[i] = 0x1a
} }
} }
if len(m.Exemplars) > 0 { if len(m.Exemplars) > 0 {
@ -127,7 +127,7 @@ func (m *TimeSeries) OptimizedMarshalToSizedBuffer(dAtA []byte) (int, error) {
i = encodeVarintTypes(dAtA, i, uint64(size)) i = encodeVarintTypes(dAtA, i, uint64(size))
} }
i-- i--
dAtA[i] = 0x1a dAtA[i] = 0x22
} }
} }
if len(m.Samples) > 0 { if len(m.Samples) > 0 {

313
prompb/write/v2/types.pb.go
View file

@ -174,7 +174,7 @@ type TimeSeries struct {
// WriteRequests with the same labels e.g. for different exemplars, metadata // WriteRequests with the same labels e.g. for different exemplars, metadata
// or created timestamp. // or created timestamp.
LabelsRefs []uint32 `protobuf:"varint,1,rep,packed,name=labels_refs,json=labelsRefs,proto3" json:"labels_refs,omitempty"` LabelsRefs []uint32 `protobuf:"varint,1,rep,packed,name=labels_refs,json=labelsRefs,proto3" json:"labels_refs,omitempty"`
// samples contain zero or more samples for a given timeseries. For a typical // samples contain zero or more samples for a given timeseries. For typical
// clients, in healthy cases, there will be only one sample, for ~real // clients, in healthy cases, there will be only one sample, for ~real
// time metric streaming. Samples can, in theory, co-exist with histogram samples // time metric streaming. Samples can, in theory, co-exist with histogram samples
// (histograms field), although it should be extremely rare in practice (e.g. // (histograms field), although it should be extremely rare in practice (e.g.
@ -184,7 +184,7 @@ type TimeSeries struct {
// Samples are sorted by timestamp (older first). // Samples are sorted by timestamp (older first).
Samples []Sample `protobuf:"bytes,2,rep,name=samples,proto3" json:"samples"` Samples []Sample `protobuf:"bytes,2,rep,name=samples,proto3" json:"samples"`
// histograms contain zero or more histogram samples for a given timeseries. // histograms contain zero or more histogram samples for a given timeseries.
// For a typical clients, in healthy cases, there will be only one sample, for ~real // For typical clients, in healthy cases, there will be only one sample, for ~real
// time metric streaming. histograms can co-exist with samples (see samples // time metric streaming. histograms can co-exist with samples (see samples
// for details). // for details).
// //
@ -508,12 +508,16 @@ type Histogram struct {
Count isHistogram_Count `protobuf_oneof:"count"` Count isHistogram_Count `protobuf_oneof:"count"`
Sum float64 `protobuf:"fixed64,3,opt,name=sum,proto3" json:"sum,omitempty"` Sum float64 `protobuf:"fixed64,3,opt,name=sum,proto3" json:"sum,omitempty"`
// The schema defines the bucket schema. Currently, valid numbers // The schema defines the bucket schema. Currently, valid numbers
// are -4 <= n <= 8. They are all for base-2 bucket schemas, where 1 // are -53 and numbers in range of -4 <= n <= 8. More valid numbers might be
// added in future for new bucketing layouts.
//
// The schema equal to -53 means custom buckets. See
// custom_values field description for more details.
//
// Values between -4 and 8 represent base-2 bucket schema, where 1
// is a bucket boundary in each case, and then each power of two is // is a bucket boundary in each case, and then each power of two is
// divided into 2^n logarithmic buckets. Or in other words, each // divided into 2^n (n is schema value) logarithmic buckets. Or in other words,
// bucket boundary is the previous boundary times 2^(2^-n). In the // each bucket boundary is the previous boundary times 2^(2^-n).
// future, more bucket schemas may be added using numbers < -4 or >
// 8.
Schema int32 `protobuf:"zigzag32,4,opt,name=schema,proto3" json:"schema,omitempty"` Schema int32 `protobuf:"zigzag32,4,opt,name=schema,proto3" json:"schema,omitempty"`
ZeroThreshold float64 `protobuf:"fixed64,5,opt,name=zero_threshold,json=zeroThreshold,proto3" json:"zero_threshold,omitempty"` ZeroThreshold float64 `protobuf:"fixed64,5,opt,name=zero_threshold,json=zeroThreshold,proto3" json:"zero_threshold,omitempty"`
// Types that are valid to be assigned to ZeroCount: // Types that are valid to be assigned to ZeroCount:
@ -524,25 +528,58 @@ type Histogram struct {
// Negative Buckets. // Negative Buckets.
NegativeSpans []BucketSpan `protobuf:"bytes,8,rep,name=negative_spans,json=negativeSpans,proto3" json:"negative_spans"` NegativeSpans []BucketSpan `protobuf:"bytes,8,rep,name=negative_spans,json=negativeSpans,proto3" json:"negative_spans"`
// Use either "negative_deltas" or "negative_counts", the former for // Use either "negative_deltas" or "negative_counts", the former for
// regular histograms with integer counts, the latter for float // regular histograms with integer counts, the latter for
// histograms. // float histograms.
NegativeDeltas []int64 `protobuf:"zigzag64,9,rep,packed,name=negative_deltas,json=negativeDeltas,proto3" json:"negative_deltas,omitempty"` NegativeDeltas []int64 `protobuf:"zigzag64,9,rep,packed,name=negative_deltas,json=negativeDeltas,proto3" json:"negative_deltas,omitempty"`
NegativeCounts []float64 `protobuf:"fixed64,10,rep,packed,name=negative_counts,json=negativeCounts,proto3" json:"negative_counts,omitempty"` NegativeCounts []float64 `protobuf:"fixed64,10,rep,packed,name=negative_counts,json=negativeCounts,proto3" json:"negative_counts,omitempty"`
// Positive Buckets. // Positive Buckets.
//
// In case of custom buckets (-53 schema value) the positive buckets are interpreted as follows:
// * The span offset+length points to an the index of the custom_values array
// or +Inf if pointing to the len of the array.
// * The counts and deltas have the same meaning as for exponential histograms.
PositiveSpans []BucketSpan `protobuf:"bytes,11,rep,name=positive_spans,json=positiveSpans,proto3" json:"positive_spans"` PositiveSpans []BucketSpan `protobuf:"bytes,11,rep,name=positive_spans,json=positiveSpans,proto3" json:"positive_spans"`
// Use either "positive_deltas" or "positive_counts", the former for // Use either "positive_deltas" or "positive_counts", the former for
// regular histograms with integer counts, the latter for float // regular histograms with integer counts, the latter for
// histograms. // float histograms.
PositiveDeltas []int64 `protobuf:"zigzag64,12,rep,packed,name=positive_deltas,json=positiveDeltas,proto3" json:"positive_deltas,omitempty"` PositiveDeltas []int64 `protobuf:"zigzag64,12,rep,packed,name=positive_deltas,json=positiveDeltas,proto3" json:"positive_deltas,omitempty"`
PositiveCounts []float64 `protobuf:"fixed64,13,rep,packed,name=positive_counts,json=positiveCounts,proto3" json:"positive_counts,omitempty"` PositiveCounts []float64 `protobuf:"fixed64,13,rep,packed,name=positive_counts,json=positiveCounts,proto3" json:"positive_counts,omitempty"`
ResetHint Histogram_ResetHint `protobuf:"varint,14,opt,name=reset_hint,json=resetHint,proto3,enum=write.v2.Histogram_ResetHint" json:"reset_hint,omitempty"` ResetHint Histogram_ResetHint `protobuf:"varint,14,opt,name=reset_hint,json=resetHint,proto3,enum=write.v2.Histogram_ResetHint" json:"reset_hint,omitempty"`
// timestamp represents timestamp of the sample in ms. // timestamp represents timestamp of the sample in ms.
// For Go, see github.com/prometheus/prometheus/model/timestamp/timestamp.go // For Go, see github.com/prometheus/prometheus/model/timestamp/timestamp.go
// for conversion from/to time.Time to Prometheus timestamp. // for conversion from/to time.Time to Prometheus timestamp.
Timestamp int64 `protobuf:"varint,15,opt,name=timestamp,proto3" json:"timestamp,omitempty"` Timestamp int64 `protobuf:"varint,15,opt,name=timestamp,proto3" json:"timestamp,omitempty"`
XXX_NoUnkeyedLiteral struct{} `json:"-"` // custom_values is an additional field used by non-exponential bucketing layouts.
XXX_unrecognized []byte `json:"-"` //
XXX_sizecache int32 `json:"-"` // For custom buckets (-53 schema value) custom_values specify monotonically
// increasing upper inclusive boundaries for the bucket counts with arbitrary
// widths for this histogram. In other words, custom_values represents custom,
// explicit bucketing that could have been converted from the classic histograms.
//
// Those bounds are then referenced by spans in positive_spans with corresponding positive
// counts of deltas (refer to positive_spans for more details). This way we can
// have encode sparse histograms with custom bucketing (many buckets are often
// not used).
//
// Note that for custom bounds, even negative observations are placed in the positive
// counts to simplify the implementation and avoid ambiguity of where to place
// an underflow bucket, e.g. (-2, 1]. Therefore negative buckets and
// the zero bucket are unused, if the schema indicates custom bucketing.
//
// For each upper boundary the previous boundary represent the lower exclusive
// boundary for that bucket. The first element is the upper inclusive boundary
// for the first bucket, which implicitly has a lower inclusive bound of -Inf.
// This is similar to "le" label semantics on classic histograms. You may add a
// bucket with an upper bound of 0 to make sure that you really have no negative
// observations, but in practice, native histogram rendering will show both with
// or without first upper boundary 0 and no negative counts as the same case.
//
// The last element is not only the upper inclusive bound of the last regular
// bucket, but implicitly the lower exclusive bound of the +Inf bucket.
CustomValues []float64 `protobuf:"fixed64,16,rep,packed,name=custom_values,json=customValues,proto3" json:"custom_values,omitempty"`
XXX_NoUnkeyedLiteral struct{} `json:"-"`
XXX_unrecognized []byte `json:"-"`
XXX_sizecache int32 `json:"-"`
} }
func (m *Histogram) Reset() { *m = Histogram{} } func (m *Histogram) Reset() { *m = Histogram{} }
@ -725,6 +762,13 @@ func (m *Histogram) GetTimestamp() int64 {
return 0 return 0
} }
func (m *Histogram) GetCustomValues() []float64 {
if m != nil {
return m.CustomValues
}
return nil
}
// XXX_OneofWrappers is for the internal use of the proto package. // XXX_OneofWrappers is for the internal use of the proto package.
func (*Histogram) XXX_OneofWrappers() []interface{} { func (*Histogram) XXX_OneofWrappers() []interface{} {
return []interface{}{ return []interface{}{
@ -810,62 +854,64 @@ func init() {
func init() { proto.RegisterFile("write/v2/types.proto", fileDescriptor_4919b8b88a093366) } func init() { proto.RegisterFile("write/v2/types.proto", fileDescriptor_4919b8b88a093366) }
var fileDescriptor_4919b8b88a093366 = []byte{ var fileDescriptor_4919b8b88a093366 = []byte{
// 875 bytes of a gzipped FileDescriptorProto // 897 bytes of a gzipped FileDescriptorProto
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0x00,
} }
func (m *WriteRequest) Marshal() (dAtA []byte, err error) { func (m *WriteRequest) Marshal() (dAtA []byte, err error) {
@ -1180,6 +1226,18 @@ func (m *Histogram) MarshalToSizedBuffer(dAtA []byte) (int, error) {
i -= len(m.XXX_unrecognized) i -= len(m.XXX_unrecognized)
copy(dAtA[i:], m.XXX_unrecognized) copy(dAtA[i:], m.XXX_unrecognized)
} }
if len(m.CustomValues) > 0 {
for iNdEx := len(m.CustomValues) - 1; iNdEx >= 0; iNdEx-- {
f6 := math.Float64bits(float64(m.CustomValues[iNdEx]))
i -= 8
encoding_binary.LittleEndian.PutUint64(dAtA[i:], uint64(f6))
}
i = encodeVarintTypes(dAtA, i, uint64(len(m.CustomValues)*8))
i--
dAtA[i] = 0x1
i--
dAtA[i] = 0x82
}
if m.Timestamp != 0 { if m.Timestamp != 0 {
i = encodeVarintTypes(dAtA, i, uint64(m.Timestamp)) i = encodeVarintTypes(dAtA, i, uint64(m.Timestamp))
i-- i--
@ -1192,30 +1250,30 @@ func (m *Histogram) MarshalToSizedBuffer(dAtA []byte) (int, error) {
} }
if len(m.PositiveCounts) > 0 { if len(m.PositiveCounts) > 0 {
for iNdEx := len(m.PositiveCounts) - 1; iNdEx >= 0; iNdEx-- { for iNdEx := len(m.PositiveCounts) - 1; iNdEx >= 0; iNdEx-- {
f6 := math.Float64bits(float64(m.PositiveCounts[iNdEx])) f7 := math.Float64bits(float64(m.PositiveCounts[iNdEx]))
i -= 8 i -= 8
encoding_binary.LittleEndian.PutUint64(dAtA[i:], uint64(f6)) encoding_binary.LittleEndian.PutUint64(dAtA[i:], uint64(f7))
} }
i = encodeVarintTypes(dAtA, i, uint64(len(m.PositiveCounts)*8)) i = encodeVarintTypes(dAtA, i, uint64(len(m.PositiveCounts)*8))
i-- i--
dAtA[i] = 0x6a dAtA[i] = 0x6a
} }
if len(m.PositiveDeltas) > 0 { if len(m.PositiveDeltas) > 0 {
var j7 int var j8 int
dAtA9 := make([]byte, len(m.PositiveDeltas)*10) dAtA10 := make([]byte, len(m.PositiveDeltas)*10)
for _, num := range m.PositiveDeltas { for _, num := range m.PositiveDeltas {
x8 := (uint64(num) << 1) ^ uint64((num >> 63)) x9 := (uint64(num) << 1) ^ uint64((num >> 63))
for x8 >= 1<<7 { for x9 >= 1<<7 {
dAtA9[j7] = uint8(uint64(x8)&0x7f | 0x80) dAtA10[j8] = uint8(uint64(x9)&0x7f | 0x80)
j7++ j8++
x8 >>= 7 x9 >>= 7
} }
dAtA9[j7] = uint8(x8) dAtA10[j8] = uint8(x9)
j7++ j8++
} }
i -= j7 i -= j8
copy(dAtA[i:], dAtA9[:j7]) copy(dAtA[i:], dAtA10[:j8])
i = encodeVarintTypes(dAtA, i, uint64(j7)) i = encodeVarintTypes(dAtA, i, uint64(j8))
i-- i--
dAtA[i] = 0x62 dAtA[i] = 0x62
} }
@ -1235,30 +1293,30 @@ func (m *Histogram) MarshalToSizedBuffer(dAtA []byte) (int, error) {
} }
if len(m.NegativeCounts) > 0 { if len(m.NegativeCounts) > 0 {
for iNdEx := len(m.NegativeCounts) - 1; iNdEx >= 0; iNdEx-- { for iNdEx := len(m.NegativeCounts) - 1; iNdEx >= 0; iNdEx-- {
f10 := math.Float64bits(float64(m.NegativeCounts[iNdEx])) f11 := math.Float64bits(float64(m.NegativeCounts[iNdEx]))
i -= 8 i -= 8
encoding_binary.LittleEndian.PutUint64(dAtA[i:], uint64(f10)) encoding_binary.LittleEndian.PutUint64(dAtA[i:], uint64(f11))
} }
i = encodeVarintTypes(dAtA, i, uint64(len(m.NegativeCounts)*8)) i = encodeVarintTypes(dAtA, i, uint64(len(m.NegativeCounts)*8))
i-- i--
dAtA[i] = 0x52 dAtA[i] = 0x52
} }
if len(m.NegativeDeltas) > 0 { if len(m.NegativeDeltas) > 0 {
var j11 int var j12 int
dAtA13 := make([]byte, len(m.NegativeDeltas)*10) dAtA14 := make([]byte, len(m.NegativeDeltas)*10)
for _, num := range m.NegativeDeltas { for _, num := range m.NegativeDeltas {
x12 := (uint64(num) << 1) ^ uint64((num >> 63)) x13 := (uint64(num) << 1) ^ uint64((num >> 63))
for x12 >= 1<<7 { for x13 >= 1<<7 {
dAtA13[j11] = uint8(uint64(x12)&0x7f | 0x80) dAtA14[j12] = uint8(uint64(x13)&0x7f | 0x80)
j11++ j12++
x12 >>= 7 x13 >>= 7
} }
dAtA13[j11] = uint8(x12) dAtA14[j12] = uint8(x13)
j11++ j12++
} }
i -= j11 i -= j12
copy(dAtA[i:], dAtA13[:j11]) copy(dAtA[i:], dAtA14[:j12])
i = encodeVarintTypes(dAtA, i, uint64(j11)) i = encodeVarintTypes(dAtA, i, uint64(j12))
i-- i--
dAtA[i] = 0x4a dAtA[i] = 0x4a
} }
@ -1601,6 +1659,9 @@ func (m *Histogram) Size() (n int) {
if m.Timestamp != 0 { if m.Timestamp != 0 {
n += 1 + sovTypes(uint64(m.Timestamp)) n += 1 + sovTypes(uint64(m.Timestamp))
} }
if len(m.CustomValues) > 0 {
n += 2 + sovTypes(uint64(len(m.CustomValues)*8)) + len(m.CustomValues)*8
}
if m.XXX_unrecognized != nil { if m.XXX_unrecognized != nil {
n += len(m.XXX_unrecognized) n += len(m.XXX_unrecognized)
} }
@ -2915,6 +2976,60 @@ func (m *Histogram) Unmarshal(dAtA []byte) error {
break break
} }
} }
case 16:
if wireType == 1 {
var v uint64
if (iNdEx + 8) > l {
return io.ErrUnexpectedEOF
}
v = uint64(encoding_binary.LittleEndian.Uint64(dAtA[iNdEx:]))
iNdEx += 8
v2 := float64(math.Float64frombits(v))
m.CustomValues = append(m.CustomValues, v2)
} else if wireType == 2 {
var packedLen int
for shift := uint(0); ; shift += 7 {
if shift >= 64 {
return ErrIntOverflowTypes
}
if iNdEx >= l {
return io.ErrUnexpectedEOF
}
b := dAtA[iNdEx]
iNdEx++
packedLen |= int(b&0x7F) << shift
if b < 0x80 {
break
}
}
if packedLen < 0 {
return ErrInvalidLengthTypes
}
postIndex := iNdEx + packedLen
if postIndex < 0 {
return ErrInvalidLengthTypes
}
if postIndex > l {
return io.ErrUnexpectedEOF
}
var elementCount int
elementCount = packedLen / 8
if elementCount != 0 && len(m.CustomValues) == 0 {
m.CustomValues = make([]float64, 0, elementCount)
}
for iNdEx < postIndex {
var v uint64
if (iNdEx + 8) > l {
return io.ErrUnexpectedEOF
}
v = uint64(encoding_binary.LittleEndian.Uint64(dAtA[iNdEx:]))
iNdEx += 8
v2 := float64(math.Float64frombits(v))
m.CustomValues = append(m.CustomValues, v2)
}
} else {
return fmt.Errorf("proto: wrong wireType = %d for field CustomValues", wireType)
}
default: default:
iNdEx = preIndex iNdEx = preIndex
skippy, err := skipTypes(dAtA[iNdEx:]) skippy, err := skipTypes(dAtA[iNdEx:])

57
prompb/write/v2/types.proto
View file

@ -155,13 +155,18 @@ message Histogram {
double count_float = 2; double count_float = 2;
} }
double sum = 3; // Sum of observations in the histogram. double sum = 3; // Sum of observations in the histogram.
// The schema defines the bucket schema. Currently, valid numbers // The schema defines the bucket schema. Currently, valid numbers
// are -4 <= n <= 8. They are all for base-2 bucket schemas, where 1 // are -53 and numbers in range of -4 <= n <= 8. More valid numbers might be
// added in future for new bucketing layouts.
//
// The schema equal to -53 means custom buckets. See
// custom_values field description for more details.
//
// Values between -4 and 8 represent base-2 bucket schema, where 1
// is a bucket boundary in each case, and then each power of two is // is a bucket boundary in each case, and then each power of two is
// divided into 2^n logarithmic buckets. Or in other words, each // divided into 2^n (n is schema value) logarithmic buckets. Or in other words,
// bucket boundary is the previous boundary times 2^(2^-n). In the // each bucket boundary is the previous boundary times 2^(2^-n).
// future, more bucket schemas may be added using numbers < -4 or >
// 8.
sint32 schema = 4; sint32 schema = 4;
double zero_threshold = 5; // Breadth of the zero bucket. double zero_threshold = 5; // Breadth of the zero bucket.
oneof zero_count { // Count in zero bucket. oneof zero_count { // Count in zero bucket.
@ -172,16 +177,21 @@ message Histogram {
// Negative Buckets. // Negative Buckets.
repeated BucketSpan negative_spans = 8 [(gogoproto.nullable) = false]; repeated BucketSpan negative_spans = 8 [(gogoproto.nullable) = false];
// Use either "negative_deltas" or "negative_counts", the former for // Use either "negative_deltas" or "negative_counts", the former for
// regular histograms with integer counts, the latter for float // regular histograms with integer counts, the latter for
// histograms. // float histograms.
repeated sint64 negative_deltas = 9; // Count delta of each bucket compared to previous one (or to zero for 1st bucket). repeated sint64 negative_deltas = 9; // Count delta of each bucket compared to previous one (or to zero for 1st bucket).
repeated double negative_counts = 10; // Absolute count of each bucket. repeated double negative_counts = 10; // Absolute count of each bucket.
// Positive Buckets. // Positive Buckets.
//
// In case of custom buckets (-53 schema value) the positive buckets are interpreted as follows:
// * The span offset+length points to an the index of the custom_values array
// or +Inf if pointing to the len of the array.
// * The counts and deltas have the same meaning as for exponential histograms.
repeated BucketSpan positive_spans = 11 [(gogoproto.nullable) = false]; repeated BucketSpan positive_spans = 11 [(gogoproto.nullable) = false];
// Use either "positive_deltas" or "positive_counts", the former for // Use either "positive_deltas" or "positive_counts", the former for
// regular histograms with integer counts, the latter for float // regular histograms with integer counts, the latter for
// histograms. // float histograms.
repeated sint64 positive_deltas = 12; // Count delta of each bucket compared to previous one (or to zero for 1st bucket). repeated sint64 positive_deltas = 12; // Count delta of each bucket compared to previous one (or to zero for 1st bucket).
repeated double positive_counts = 13; // Absolute count of each bucket. repeated double positive_counts = 13; // Absolute count of each bucket.
@ -190,6 +200,35 @@ message Histogram {
// For Go, see github.com/prometheus/prometheus/model/timestamp/timestamp.go // For Go, see github.com/prometheus/prometheus/model/timestamp/timestamp.go
// for conversion from/to time.Time to Prometheus timestamp. // for conversion from/to time.Time to Prometheus timestamp.
int64 timestamp = 15; int64 timestamp = 15;
// custom_values is an additional field used by non-exponential bucketing layouts.
//
// For custom buckets (-53 schema value) custom_values specify monotonically
// increasing upper inclusive boundaries for the bucket counts with arbitrary
// widths for this histogram. In other words, custom_values represents custom,
// explicit bucketing that could have been converted from the classic histograms.
//
// Those bounds are then referenced by spans in positive_spans with corresponding positive
// counts of deltas (refer to positive_spans for more details). This way we can
// have encode sparse histograms with custom bucketing (many buckets are often
// not used).
//
// Note that for custom bounds, even negative observations are placed in the positive
// counts to simplify the implementation and avoid ambiguity of where to place
// an underflow bucket, e.g. (-2, 1]. Therefore negative buckets and
// the zero bucket are unused, if the schema indicates custom bucketing.
//
// For each upper boundary the previous boundary represent the lower exclusive
// boundary for that bucket. The first element is the upper inclusive boundary
// for the first bucket, which implicitly has a lower inclusive bound of -Inf.
// This is similar to "le" label semantics on classic histograms. You may add a
// bucket with an upper bound of 0 to make sure that you really have no negative
// observations, but in practice, native histogram rendering will show both with
// or without first upper boundary 0 and no negative counts as the same case.
//
// The last element is not only the upper inclusive bound of the last regular
// bucket, but implicitly the lower exclusive bound of the +Inf bucket.
repeated double custom_values = 16;
} }
// A BucketSpan defines a number of consecutive buckets with their // A BucketSpan defines a number of consecutive buckets with their