Skip to content

Commit

Permalink
Unsplit all data points and exemplar by measurement type (#209)
Browse files Browse the repository at this point in the history 
Signed-off-by: Bogdan Drutu <bogdandrutu@gmail.com>
  • Loading branch information
@bogdandrutu
bogdandrutu committed Aug 26, 2020
1 parent ee000ac commit f374b78
Showing 1 changed file with 182 additions and 69 deletions.
251 changes: 182 additions & 69 deletions opentelemetry/proto/metrics/v1/metrics.proto
View file
Original file line number Diff line number Diff line change
Expand Up @@ -136,13 +136,16 @@ message Metric {
// UpDownSumObserver Sum(aggregation_temporality=cumulative;is_monotonic=false)
// ValueObserver Gauge()
oneof data {
Gauge gauge = 4;
Sum sum = 5;
Histogram histogram = 6;
IntGauge int_gauge = 4;
DoubleGauge double_gauge = 5;
IntSum int_sum = 6;
DoubleSum double_sum = 7;
IntHistogram int_histogram = 8;
DoubleHistogram double_histogram = 9;
}
}

// Gauge represents the type of a scalar metric that always exports the
// Gauge represents the type of a int scalar metric that always exports the
// "current value" for every data point. It should be used for an "unknown"
// aggregation.
//
Expand All @@ -151,64 +154,67 @@ message Metric {
// aggregation, regardless of aggregation temporalities. Therefore,
// AggregationTemporality is not included. Consequently, this also means
// "StartTimeUnixNano" is ignored for all data points.
message Gauge {
repeated Int64DataPoint int64_data_points = 1;
repeated DoubleDataPoint double_data_points = 2;
message IntGauge {
repeated Int64DataPoint data_points = 1;
}

// It describes the value type of the measurement used to build this
// aggregation.
//
// Determines if the points are Int64DataPoint or DoubleDataPoint, as well
// as the value type of the exemplars.
MeasurementValueType measurement_value_type = 3;
// Gauge represents the type of a double 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 DoubleGauge {
repeated DoubleDataPoint data_points = 1;
}

// Sum represents the type of a numeric scalar metric that is calculated as a
// sum of all reported measurements over a time interval.
message Sum {
repeated Int64DataPoint int64_data_points = 1;
repeated DoubleDataPoint double_data_points = 2;
// Sum represents the type of a numeric int scalar metric that is calculated as
// a sum of all reported measurements over a time interval.
message IntSum {
repeated Int64DataPoint data_points = 1;

// It describes the value type of the measurement used to build this
// aggregation.
//
// Determines if the points are Int64DataPoint or DoubleDataPoint, as well
// as the value type of the exemplars.
MeasurementValueType measurement_value_type = 3;
// 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;
}

// Sum represents the type of a numeric double scalar metric that is calculated
// as a sum of all reported measurements over a time interval.
message DoubleSum {
repeated DoubleDataPoint 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 = 4;
AggregationTemporality aggregation_temporality = 2;

// If "true" means that the sum is monotonic.
bool is_monotonic = 5;
bool is_monotonic = 3;
}

// 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;

// It describes the value type of the measurement used to build this
// aggregation.
//
// Determines the value type of the exemplars.
MeasurementValueType measurement_value_type = 2;
// Histogram of all reported int measurements over a time interval.
message IntHistogram {
repeated IntHistogramDataPoint 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 = 3;
AggregationTemporality aggregation_temporality = 2;
}

// MeasurementValueType determines the value type for a measurement.
enum MeasurementValueType {
// UNSPECIFIED is the default MeasurementValueType, it MUST not be used.
MEASUREMENT_VALUE_TYPE_UNSPECIFIED = 0;
// INT64 is the MeasurementValueType used when the measurements are int64.
MEASUREMENT_VALUE_TYPE_INT64 = 1;
// DOUBLE is the MeasurementValueType used when the measurements are
// floating point numbers.
MEASUREMENT_VALUE_TYPE_DOUBLE = 2;
// Represents the type of a metric that is calculated by aggregating as a
// Histogram of all reported double measurements over a time interval.
message DoubleHistogram {
repeated DoubleHistogramDataPoint 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;
}

// AggregationTemporality defines how a metric aggregator reports aggregated
Expand Down Expand Up @@ -282,8 +288,8 @@ enum AggregationTemporality {
AGGREGATION_TEMPORALITY_CUMULATIVE = 2;
}

// Int64DataPoint is a single data point in a timeseries that describes the time-varying
// values of a int64 metric.
// Int64DataPoint is a single data point in a timeseries that describes the
// time-varying values of a int64 metric.
message Int64DataPoint {
// The set of labels that uniquely identify this timeseries.
repeated opentelemetry.proto.common.v1.StringKeyValue labels = 1;
Expand Down Expand Up @@ -313,11 +319,11 @@ message Int64DataPoint {

// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 5;
repeated IntExemplar exemplars = 5;
}

// DoubleDataPoint is a single data point in a timeseries that describes the time-varying
// value of a double metric.
// DoubleDataPoint is a single data point in a timeseries that describes the
// time-varying value of a double metric.
message DoubleDataPoint {
// The set of labels that uniquely identify this timeseries.
repeated opentelemetry.proto.common.v1.StringKeyValue labels = 1;
Expand Down Expand Up @@ -347,13 +353,14 @@ message DoubleDataPoint {

// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 5;
repeated DoubleExemplar exemplars = 5;
}

// 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.
message HistogramDataPoint {
// IntHistogramDataPoint is a single data point in a timeseries that describes
// the time-varying values of a Histogram of int values. A Histogram contains
// summary statistics for a population of values, it may optionally contain
// the distribution of those values across a set of buckets.
message IntHistogramDataPoint {
// The set of labels that uniquely identify this timeseries.
repeated opentelemetry.proto.common.v1.StringKeyValue labels = 1;

Expand All @@ -377,13 +384,90 @@ message HistogramDataPoint {
// 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.
// 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.
uint64 count = 4;

// sum of the values in the population. If count is zero then this field
// must be zero. This value must be equal to the sum of the "sum" fields in buckets if
// a histogram is provided.
// must be zero. This value must be equal to the sum of the "sum" fields in
// buckets if a histogram is provided.
int64 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 uint64 bucket_counts = 6;

// A histogram may optionally contain the distribution of the values in the population.
// In that case one of the option fields below and "buckets" field both must be defined.
// Otherwise all option fields and "buckets" field must be omitted in which case the
// distribution of values in the histogram is unknown and only the total count and sum are known.

// explicit_bounds is the only supported bucket option currently.
// TODO: Add more bucket options.

// explicit_bounds specifies buckets with explicitly defined bounds for values.
// The bucket boundaries are described by "bounds" field.
//
// This defines size(bounds) + 1 (= N) buckets. The boundaries for bucket
// at index i are:
//
// (-infinity, bounds[i]) for i == 0
// [bounds[i-1], bounds[i]) for 0 < i < N-1
// [bounds[i], +infinity) for i == N-1
// The values in bounds array must be strictly increasing.
//
// Note: only [a, b) intervals are currently supported for each bucket except the first one.
// If we decide to also support (a, b] intervals we should add support for these by defining
// a boolean value which decides what type of intervals to use.
repeated double explicit_bounds = 7;

// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated IntExemplar exemplars = 8;
}

// HistogramDataPoint is a single data point in a timeseries that describes the
// time-varying values of a Histogram of double values. A Histogram contains
// summary statistics for a population of values, it may optionally contain the
// distribution of those values across a set of buckets.
message DoubleHistogramDataPoint {
// The set of labels that uniquely identify this timeseries.
repeated opentelemetry.proto.common.v1.StringKeyValue labels = 1;

// start_time_unix_nano is the last time when the aggregation value was reset
// to "zero". For some metric types this is ignored, see data types for more
// details.
//
// The aggregation value is over the time interval (start_time_unix_nano,
// time_unix_nano].
//
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
//
// Value of 0 indicates that the timestamp is unspecified. In that case the
// timestamp may be decided by the backend.
fixed64 start_time_unix_nano = 2;

// time_unix_nano is the moment when this aggregation value was reported.
//
// 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.
uint64 count = 4;

// sum of the values in the population. If count is zero then this field
// must be zero. This value must be equal to the sum of the "sum" fields in
// buckets if a histogram is provided.
double sum = 5;

// bucket_counts is an optional field contains the count values of histogram
Expand Down Expand Up @@ -421,36 +505,65 @@ message HistogramDataPoint {

// (Optional) List of exemplars collected from
// measurements that were used to form the data point
repeated Exemplar exemplars = 8;
repeated DoubleExemplar exemplars = 8;
}

// A representation of an exemplar, which is a sample input int 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 IntExemplar {
// The set of labels that were filtered out by the aggregator, but recorded
// alongside the original measurement. Only labels that were filtered out
// by the aggregator should be included
repeated opentelemetry.proto.common.v1.StringKeyValue filtered_labels = 1;

// 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;

// Numerical int value of the measurement that was recorded.
int64 value = 3;

// (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;
}

// A representation of an exemplar, which is a sample input measurement.
// A representation of an exemplar, which is a sample input double 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 {
message DoubleExemplar {
// The set of labels that were filtered out by the aggregator, but recorded
// alongside the original measurement. Only labels that were filtered out
// by the aggregator should be included
repeated opentelemetry.proto.common.v1.StringKeyValue filtered_labels = 1;

// 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.
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
// 1970.
fixed64 time_unix_nano = 2;

// Numerical value of the measurement that was recorded. Only one of these
// two fields is used for the data, based on MeasurementValueType.
double double_value = 3;
int64 int64_value = 4;
// Numerical double value of the measurement that was recorded.
double value = 3;

// (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 = 5;
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 = 6;
bytes trace_id = 5;
}

0 comments on commit f374b78

Please sign in to comment.