package metricdata

Import Path
	go.opencensus.io/metric/metricdata (on go.dev)

Dependency Relation
	imports 3 packages, and imported by 7 packages


Involved Source Files

	
		Package metricdata contains the metrics data model.

		This is an EXPERIMENTAL package, and may change in arbitrary ways without
		notice.

	      exemplar.go
	      label.go
	      metric.go
	      point.go
	      type_string.go
	      unit.go


Package-Level Type Names (total 16, all are exported)


	/* sort exporteds by:  |  */
	
		Attachments is a map of extra values associated with a recorded data point.

		
			
		
			func go.opencensus.io/stats.WithAttachments(attachments Attachments) stats.Options
			


	
		Bucket represents a single bucket (value range) in a distribution.

		
			
				Count is the number of values in each bucket of the histogram, as described in
				bucket_bounds.

			
				Exemplar associated with this bucket (if any).

		
			


	
		BucketOptions describes the bounds of the histogram buckets in this
		distribution.

		
			
				Bounds specifies a set of bucket upper bounds.
				This defines len(bounds) + 1 (= N) buckets. The boundaries for bucket
				index i are:

				[0, Bounds[i]) for i == 0
				[Bounds[i-1], Bounds[i]) for 0 < i < N-1
				[Bounds[i-1], +infinity) for i == N-1



	
		Descriptor holds metadata about a metric.

		
			
				// human-readable description

			
				// label keys

			
				// full name of the metric

			
				// type of measure

			
				// units for the measure

		
			


	
		Distribution contains summary statistics for a population of values. It
		optionally contains a histogram representing the distribution of those
		values across a set of buckets.

		
			
				BucketOptions describes the bounds of the histogram buckets in this
				distribution.

				A Distribution may optionally contain a histogram of the values in the
				population.

				If nil, there is no associated histogram.

			
				Bucket If the distribution does not have a histogram, then omit this field.
				If there is a histogram, then the sum of the values in the Bucket counts
				must equal the value in the count field of the distribution.

			
				Count is the number of values in the population. Must be non-negative. This value
				must equal the sum of the values in bucket_counts if a histogram is
				provided.

			
				Sum is the sum of the values in the population. If count is zero then this field
				must be zero.

			
				SumOfSquaredDeviation is the sum of squared deviations from the mean of the values in the
				population. For values x_i this is:

				    Sum[i=1..n]((x_i - mean)^2)

				Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition
				describes Welford's method for accumulating this sum in one pass.

				If count is zero then this field must be zero.

		
			func NewDistributionPoint(t time.Time, val *Distribution) Point
			func ValueVisitor.VisitDistributionValue(*Distribution)


	
		Exemplar is an example data point associated with each bucket of a
		distribution type aggregation.

		Their purpose is to provide an example of the kind of thing
		(request, RPC, trace span, etc.) that resulted in that measurement.

		
			
				// attachments (if any)

			
				// the time the value was recorded

			
				// the value that was recorded

		
			
		
			


	
		LabelKey represents key of a label. It has optional
		description attribute.

		
			Description string
			Key string
		
			
		
			


	
		LabelValue represents the value of a label.
		The zero value represents a missing label value, which may be treated
		differently to an empty string value by some back ends.

		
			
				// flag that indicated whether a value is present or not

			
				// string value of the label

		
			func NewLabelValue(val string) LabelValue
			
		
			


	
		Metric represents a quantity measured against a resource with different
		label value combinations.

		
			
				// metric descriptor

			
				// resource against which this was measured

			
				// one time series for each combination of label values

		
			func go.opencensus.io/metric/metricproducer.Producer.Read() []*Metric
			
		
			func go.opencensus.io/metric/metricexport.Exporter.ExportMetrics(ctx context.Context, data []*Metric) error
			func contrib.go.opencensus.io/exporter/stackdriver.(*Exporter).ExportMetrics(ctx context.Context, metrics []*Metric) error
			


	
		Point is a single data point of a time series.

		
			
				Time is the point in time that this point represents in a time series.

			
				Value is the value of this point. Prefer using ReadValue to switching on
				the value type, since new value types might be added.

		
			
				ReadValue accepts a ValueVisitor and calls the appropriate method with the
				value of this point.
				Consumers of Point should use this in preference to switching on the type
				of the value directly, since new value types may be added.

		
			func NewDistributionPoint(t time.Time, val *Distribution) Point
			func NewFloat64Point(t time.Time, val float64) Point
			func NewInt64Point(t time.Time, val int64) Point
			func NewSummaryPoint(t time.Time, val *Summary) Point
			
		
			


	
		Snapshot represents percentiles over an arbitrary time.
		The values in this struct can be reset at arbitrary unknown times, with
		the requirement that all of them are reset at the same time.

		
			
				Count is the number of values in the snapshot. Optional since some systems don't
				expose this. Set to 0 if not available.

			
				Percentiles is a map from percentile (range (0-100.0]) to the value of
				the percentile.

			
				Sum is the sum of values in the snapshot. Optional since some systems don't
				expose this. If count is 0 then this field must be zero.



	
		Summary is a representation of percentiles.

		
			
				Count is the cumulative count (if available).

			
				HasCountAndSum is true if Count and Sum are available.

			
				Snapshot represents percentiles calculated over an arbitrary time window.
				The values in this struct can be reset at arbitrary unknown times, with
				the requirement that all of them are reset at the same time.

			
				Sum is the cumulative sum of values  (if available).

		
			func NewSummaryPoint(t time.Time, val *Summary) Point
			func ValueVisitor.VisitSummaryValue(*Summary)


	
		TimeSeries is a sequence of points associated with a combination of label
		values.

		
			
				// label values, same order as keys in the metric descriptor

			
				// points sequence

			
				// time we started recording this time series

		
			


	
		Type is the overall type of metric, including its value type and whether it
		represents a cumulative total (since the start time) or if it represents a
		gauge value.

		
			( T) String() string
		
			 T : expvar.Var
			 T : fmt.Stringer
			
		
			
		
			
		
			const TypeCumulativeDistribution
			const TypeCumulativeFloat64
			const TypeCumulativeInt64
			const TypeGaugeDistribution
			const TypeGaugeFloat64
			const TypeGaugeInt64
			const TypeSummary


	
		Unit is a string encoded according to the case-sensitive abbreviations from the
		Unified Code for Units of Measure: http://unitsofmeasure.org/ucum.html

		
			
		
			const UnitBytes
			const UnitDimensionless
			const UnitMilliseconds


	
		ValueVisitor allows reading the value of a point.

		
			( T) VisitDistributionValue(*Distribution)
			( T) VisitFloat64Value(float64)
			( T) VisitInt64Value(int64)
			( T) VisitSummaryValue(*Summary)
		
			func Point.ReadValue(vv ValueVisitor)




Package-Level Functions (total 5, all are exported)


	
		NewDistributionPoint creates a new Point holding a Distribution value.


	
		NewFloat64Point creates a new Point holding a float64 value.


	
		NewInt64Point creates a new Point holding an int64 value.


	
		NewLabelValue creates a new non-nil LabelValue that represents the given string.


	
		NewSummaryPoint creates a new Point holding a Summary value.




Package-Level Variables (only one, which is unexported)

	


Package-Level Constants (total 12, in which 11 are exported)


	
		Exemplars keys.


	
		Metric types.


	
		Metric types.


	
		Metric types.


	
		Metric types.


	
		Metric types.


	
		Metric types.


	
		Predefined units. To record against a unit not represented here, create your
		own Unit type constant from a string.


	
		Predefined units. To record against a unit not represented here, create your
		own Unit type constant from a string.


	
		Predefined units. To record against a unit not represented here, create your
		own Unit type constant from a string.