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Diffstat (limited to 'vendor/go.opentelemetry.io/otel/sdk/metric/exemplar')
9 files changed, 0 insertions, 553 deletions
diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/README.md b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/README.md deleted file mode 100644 index d1025f5eb..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/README.md +++ /dev/null @@ -1,3 +0,0 @@ -# Metric SDK Exemplars - -[](https://pkg.go.dev/go.opentelemetry.io/otel/sdk/metric/exemplar) diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/doc.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/doc.go deleted file mode 100644 index 9f2389376..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/doc.go +++ /dev/null @@ -1,6 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -// Package exemplar provides an implementation of the OpenTelemetry exemplar -// reservoir to be used in metric collection pipelines. -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/exemplar.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/exemplar.go deleted file mode 100644 index 1ab694678..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/exemplar.go +++ /dev/null @@ -1,29 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "time" - - "go.opentelemetry.io/otel/attribute" -) - -// Exemplar is a measurement sampled from a timeseries providing a typical -// example. -type Exemplar struct { - // FilteredAttributes are the attributes recorded with the measurement but - // filtered out of the timeseries' aggregated data. - FilteredAttributes []attribute.KeyValue - // Time is the time when the measurement was recorded. - Time time.Time - // Value is the measured value. - Value Value - // SpanID is the ID of the span that was active during the measurement. If - // no span was active or the span was not sampled this will be empty. - SpanID []byte `json:",omitempty"` - // TraceID is the ID of the trace the active span belonged to during the - // measurement. If no span was active or the span was not sampled this will - // be empty. - TraceID []byte `json:",omitempty"` -} diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/filter.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/filter.go deleted file mode 100644 index b595e2ace..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/filter.go +++ /dev/null @@ -1,34 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "context" - - "go.opentelemetry.io/otel/trace" -) - -// Filter determines if a measurement should be offered. -// -// The passed ctx needs to contain any baggage or span that were active -// when the measurement was made. This information may be used by the -// Reservoir in making a sampling decision. -type Filter func(context.Context) bool - -// TraceBasedFilter is a [Filter] that will only offer measurements -// if the passed context associated with the measurement contains a sampled -// [go.opentelemetry.io/otel/trace.SpanContext]. -func TraceBasedFilter(ctx context.Context) bool { - return trace.SpanContextFromContext(ctx).IsSampled() -} - -// AlwaysOnFilter is a [Filter] that always offers measurements. -func AlwaysOnFilter(ctx context.Context) bool { - return true -} - -// AlwaysOffFilter is a [Filter] that never offers measurements. -func AlwaysOffFilter(ctx context.Context) bool { - return false -} diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/fixed_size_reservoir.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/fixed_size_reservoir.go deleted file mode 100644 index d4aab0aad..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/fixed_size_reservoir.go +++ /dev/null @@ -1,217 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "context" - "math" - "math/rand" - "time" - - "go.opentelemetry.io/otel/attribute" -) - -// FixedSizeReservoirProvider returns a provider of [FixedSizeReservoir]. -func FixedSizeReservoirProvider(k int) ReservoirProvider { - return func(_ attribute.Set) Reservoir { - return NewFixedSizeReservoir(k) - } -} - -// NewFixedSizeReservoir returns a [FixedSizeReservoir] that samples at most -// k exemplars. If there are k or less measurements made, the Reservoir will -// sample each one. If there are more than k, the Reservoir will then randomly -// sample all additional measurement with a decreasing probability. -func NewFixedSizeReservoir(k int) *FixedSizeReservoir { - return newFixedSizeReservoir(newStorage(k)) -} - -var _ Reservoir = &FixedSizeReservoir{} - -// FixedSizeReservoir is a [Reservoir] that samples at most k exemplars. If -// there are k or less measurements made, the Reservoir will sample each one. -// If there are more than k, the Reservoir will then randomly sample all -// additional measurement with a decreasing probability. -type FixedSizeReservoir struct { - *storage - - // count is the number of measurement seen. - count int64 - // next is the next count that will store a measurement at a random index - // once the reservoir has been filled. - next int64 - // w is the largest random number in a distribution that is used to compute - // the next next. - w float64 - - // rng is used to make sampling decisions. - // - // Do not use crypto/rand. There is no reason for the decrease in performance - // given this is not a security sensitive decision. - rng *rand.Rand -} - -func newFixedSizeReservoir(s *storage) *FixedSizeReservoir { - r := &FixedSizeReservoir{ - storage: s, - rng: rand.New(rand.NewSource(time.Now().UnixNano())), - } - r.reset() - return r -} - -// randomFloat64 returns, as a float64, a uniform pseudo-random number in the -// open interval (0.0,1.0). -func (r *FixedSizeReservoir) randomFloat64() float64 { - // TODO: This does not return a uniform number. rng.Float64 returns a - // uniformly random int in [0,2^53) that is divided by 2^53. Meaning it - // returns multiples of 2^-53, and not all floating point numbers between 0 - // and 1 (i.e. for values less than 2^-4 the 4 last bits of the significand - // are always going to be 0). - // - // An alternative algorithm should be considered that will actually return - // a uniform number in the interval (0,1). For example, since the default - // rand source provides a uniform distribution for Int63, this can be - // converted following the prototypical code of Mersenne Twister 64 (Takuji - // Nishimura and Makoto Matsumoto: - // http://www.math.sci.hiroshima-u.ac.jp/m-mat/MT/VERSIONS/C-LANG/mt19937-64.c) - // - // (float64(rng.Int63()>>11) + 0.5) * (1.0 / 4503599627370496.0) - // - // There are likely many other methods to explore here as well. - - f := r.rng.Float64() - for f == 0 { - f = r.rng.Float64() - } - return f -} - -// Offer accepts the parameters associated with a measurement. The -// parameters will be stored as an exemplar if the Reservoir decides to -// sample the measurement. -// -// The passed ctx needs to contain any baggage or span that were active -// when the measurement was made. This information may be used by the -// Reservoir in making a sampling decision. -// -// The time t is the time when the measurement was made. The v and a -// parameters are the value and dropped (filtered) attributes of the -// measurement respectively. -func (r *FixedSizeReservoir) Offer(ctx context.Context, t time.Time, n Value, a []attribute.KeyValue) { - // The following algorithm is "Algorithm L" from Li, Kim-Hung (4 December - // 1994). "Reservoir-Sampling Algorithms of Time Complexity - // O(n(1+log(N/n)))". ACM Transactions on Mathematical Software. 20 (4): - // 481–493 (https://dl.acm.org/doi/10.1145/198429.198435). - // - // A high-level overview of "Algorithm L": - // 0) Pre-calculate the random count greater than the storage size when - // an exemplar will be replaced. - // 1) Accept all measurements offered until the configured storage size is - // reached. - // 2) Loop: - // a) When the pre-calculate count is reached, replace a random - // existing exemplar with the offered measurement. - // b) Calculate the next random count greater than the existing one - // which will replace another exemplars - // - // The way a "replacement" count is computed is by looking at `n` number of - // independent random numbers each corresponding to an offered measurement. - // Of these numbers the smallest `k` (the same size as the storage - // capacity) of them are kept as a subset. The maximum value in this - // subset, called `w` is used to weight another random number generation - // for the next count that will be considered. - // - // By weighting the next count computation like described, it is able to - // perform a uniformly-weighted sampling algorithm based on the number of - // samples the reservoir has seen so far. The sampling will "slow down" as - // more and more samples are offered so as to reduce a bias towards those - // offered just prior to the end of the collection. - // - // This algorithm is preferred because of its balance of simplicity and - // performance. It will compute three random numbers (the bulk of - // computation time) for each item that becomes part of the reservoir, but - // it does not spend any time on items that do not. In particular it has an - // asymptotic runtime of O(k(1 + log(n/k)) where n is the number of - // measurements offered and k is the reservoir size. - // - // See https://en.wikipedia.org/wiki/Reservoir_sampling for an overview of - // this and other reservoir sampling algorithms. See - // https://github.com/MrAlias/reservoir-sampling for a performance - // comparison of reservoir sampling algorithms. - - if int(r.count) < cap(r.store) { - r.store[r.count] = newMeasurement(ctx, t, n, a) - } else { - if r.count == r.next { - // Overwrite a random existing measurement with the one offered. - idx := int(r.rng.Int63n(int64(cap(r.store)))) - r.store[idx] = newMeasurement(ctx, t, n, a) - r.advance() - } - } - r.count++ -} - -// reset resets r to the initial state. -func (r *FixedSizeReservoir) reset() { - // This resets the number of exemplars known. - r.count = 0 - // Random index inserts should only happen after the storage is full. - r.next = int64(cap(r.store)) - - // Initial random number in the series used to generate r.next. - // - // This is set before r.advance to reset or initialize the random number - // series. Without doing so it would always be 0 or never restart a new - // random number series. - // - // This maps the uniform random number in (0,1) to a geometric distribution - // over the same interval. The mean of the distribution is inversely - // proportional to the storage capacity. - r.w = math.Exp(math.Log(r.randomFloat64()) / float64(cap(r.store))) - - r.advance() -} - -// advance updates the count at which the offered measurement will overwrite an -// existing exemplar. -func (r *FixedSizeReservoir) advance() { - // Calculate the next value in the random number series. - // - // The current value of r.w is based on the max of a distribution of random - // numbers (i.e. `w = max(u_1,u_2,...,u_k)` for `k` equal to the capacity - // of the storage and each `u` in the interval (0,w)). To calculate the - // next r.w we use the fact that when the next exemplar is selected to be - // included in the storage an existing one will be dropped, and the - // corresponding random number in the set used to calculate r.w will also - // be replaced. The replacement random number will also be within (0,w), - // therefore the next r.w will be based on the same distribution (i.e. - // `max(u_1,u_2,...,u_k)`). Therefore, we can sample the next r.w by - // computing the next random number `u` and take r.w as `w * u^(1/k)`. - r.w *= math.Exp(math.Log(r.randomFloat64()) / float64(cap(r.store))) - // Use the new random number in the series to calculate the count of the - // next measurement that will be stored. - // - // Given 0 < r.w < 1, each iteration will result in subsequent r.w being - // smaller. This translates here into the next next being selected against - // a distribution with a higher mean (i.e. the expected value will increase - // and replacements become less likely) - // - // Important to note, the new r.next will always be at least 1 more than - // the last r.next. - r.next += int64(math.Log(r.randomFloat64())/math.Log(1-r.w)) + 1 -} - -// Collect returns all the held exemplars. -// -// The Reservoir state is preserved after this call. -func (r *FixedSizeReservoir) Collect(dest *[]Exemplar) { - r.storage.Collect(dest) - // Call reset here even though it will reset r.count and restart the random - // number series. This will persist any old exemplars as long as no new - // measurements are offered, but it will also prioritize those new - // measurements that are made over the older collection cycle ones. - r.reset() -} diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/histogram_reservoir.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/histogram_reservoir.go deleted file mode 100644 index 3b76cf305..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/histogram_reservoir.go +++ /dev/null @@ -1,70 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "context" - "slices" - "sort" - "time" - - "go.opentelemetry.io/otel/attribute" -) - -// HistogramReservoirProvider is a provider of [HistogramReservoir]. -func HistogramReservoirProvider(bounds []float64) ReservoirProvider { - cp := slices.Clone(bounds) - slices.Sort(cp) - return func(_ attribute.Set) Reservoir { - return NewHistogramReservoir(cp) - } -} - -// NewHistogramReservoir returns a [HistogramReservoir] that samples the last -// measurement that falls within a histogram bucket. The histogram bucket -// upper-boundaries are define by bounds. -// -// The passed bounds must be sorted before calling this function. -func NewHistogramReservoir(bounds []float64) *HistogramReservoir { - return &HistogramReservoir{ - bounds: bounds, - storage: newStorage(len(bounds) + 1), - } -} - -var _ Reservoir = &HistogramReservoir{} - -// HistogramReservoir is a [Reservoir] that samples the last measurement that -// falls within a histogram bucket. The histogram bucket upper-boundaries are -// define by bounds. -type HistogramReservoir struct { - *storage - - // bounds are bucket bounds in ascending order. - bounds []float64 -} - -// Offer accepts the parameters associated with a measurement. The -// parameters will be stored as an exemplar if the Reservoir decides to -// sample the measurement. -// -// The passed ctx needs to contain any baggage or span that were active -// when the measurement was made. This information may be used by the -// Reservoir in making a sampling decision. -// -// The time t is the time when the measurement was made. The v and a -// parameters are the value and dropped (filtered) attributes of the -// measurement respectively. -func (r *HistogramReservoir) Offer(ctx context.Context, t time.Time, v Value, a []attribute.KeyValue) { - var x float64 - switch v.Type() { - case Int64ValueType: - x = float64(v.Int64()) - case Float64ValueType: - x = v.Float64() - default: - panic("unknown value type") - } - r.store[sort.SearchFloat64s(r.bounds, x)] = newMeasurement(ctx, t, v, a) -} diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/reservoir.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/reservoir.go deleted file mode 100644 index ba5cd1a6b..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/reservoir.go +++ /dev/null @@ -1,40 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "context" - "time" - - "go.opentelemetry.io/otel/attribute" -) - -// Reservoir holds the sampled exemplar of measurements made. -type Reservoir interface { - // Offer accepts the parameters associated with a measurement. The - // parameters will be stored as an exemplar if the Reservoir decides to - // sample the measurement. - // - // The passed ctx needs to contain any baggage or span that were active - // when the measurement was made. This information may be used by the - // Reservoir in making a sampling decision. - // - // The time t is the time when the measurement was made. The val and attr - // parameters are the value and dropped (filtered) attributes of the - // measurement respectively. - Offer(ctx context.Context, t time.Time, val Value, attr []attribute.KeyValue) - - // Collect returns all the held exemplars. - // - // The Reservoir state is preserved after this call. - Collect(dest *[]Exemplar) -} - -// ReservoirProvider creates new [Reservoir]s. -// -// The attributes provided are attributes which are kept by the aggregation, and -// are exclusive with attributes passed to Offer. The combination of these -// attributes and the attributes passed to Offer is the complete set of -// attributes a measurement was made with. -type ReservoirProvider func(attr attribute.Set) Reservoir diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/storage.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/storage.go deleted file mode 100644 index 0e2e26dfb..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/storage.go +++ /dev/null @@ -1,95 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import ( - "context" - "time" - - "go.opentelemetry.io/otel/attribute" - "go.opentelemetry.io/otel/trace" -) - -// storage is an exemplar storage for [Reservoir] implementations. -type storage struct { - // store are the measurements sampled. - // - // This does not use []metricdata.Exemplar because it potentially would - // require an allocation for trace and span IDs in the hot path of Offer. - store []measurement -} - -func newStorage(n int) *storage { - return &storage{store: make([]measurement, n)} -} - -// Collect returns all the held exemplars. -// -// The Reservoir state is preserved after this call. -func (r *storage) Collect(dest *[]Exemplar) { - *dest = reset(*dest, len(r.store), len(r.store)) - var n int - for _, m := range r.store { - if !m.valid { - continue - } - - m.exemplar(&(*dest)[n]) - n++ - } - *dest = (*dest)[:n] -} - -// measurement is a measurement made by a telemetry system. -type measurement struct { - // FilteredAttributes are the attributes dropped during the measurement. - FilteredAttributes []attribute.KeyValue - // Time is the time when the measurement was made. - Time time.Time - // Value is the value of the measurement. - Value Value - // SpanContext is the SpanContext active when a measurement was made. - SpanContext trace.SpanContext - - valid bool -} - -// newMeasurement returns a new non-empty Measurement. -func newMeasurement(ctx context.Context, ts time.Time, v Value, droppedAttr []attribute.KeyValue) measurement { - return measurement{ - FilteredAttributes: droppedAttr, - Time: ts, - Value: v, - SpanContext: trace.SpanContextFromContext(ctx), - valid: true, - } -} - -// exemplar returns m as an [Exemplar]. -func (m measurement) exemplar(dest *Exemplar) { - dest.FilteredAttributes = m.FilteredAttributes - dest.Time = m.Time - dest.Value = m.Value - - if m.SpanContext.HasTraceID() { - traceID := m.SpanContext.TraceID() - dest.TraceID = traceID[:] - } else { - dest.TraceID = dest.TraceID[:0] - } - - if m.SpanContext.HasSpanID() { - spanID := m.SpanContext.SpanID() - dest.SpanID = spanID[:] - } else { - dest.SpanID = dest.SpanID[:0] - } -} - -func reset[T any](s []T, length, capacity int) []T { - if cap(s) < capacity { - return make([]T, length, capacity) - } - return s[:length] -} diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/value.go b/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/value.go deleted file mode 100644 index 590b089a8..000000000 --- a/vendor/go.opentelemetry.io/otel/sdk/metric/exemplar/value.go +++ /dev/null @@ -1,59 +0,0 @@ -// Copyright The OpenTelemetry Authors -// SPDX-License-Identifier: Apache-2.0 - -package exemplar // import "go.opentelemetry.io/otel/sdk/metric/exemplar" - -import "math" - -// ValueType identifies the type of value used in exemplar data. -type ValueType uint8 - -const ( - // UnknownValueType should not be used. It represents a misconfigured - // Value. - UnknownValueType ValueType = 0 - // Int64ValueType represents a Value with int64 data. - Int64ValueType ValueType = 1 - // Float64ValueType represents a Value with float64 data. - Float64ValueType ValueType = 2 -) - -// Value is the value of data held by an exemplar. -type Value struct { - t ValueType - val uint64 -} - -// NewValue returns a new [Value] for the provided value. -func NewValue[N int64 | float64](value N) Value { - switch v := any(value).(type) { - case int64: - // This can be later converted back to int64 (overflow not checked). - return Value{t: Int64ValueType, val: uint64(v)} // nolint:gosec - case float64: - return Value{t: Float64ValueType, val: math.Float64bits(v)} - } - return Value{} -} - -// Type returns the [ValueType] of data held by v. -func (v Value) Type() ValueType { return v.t } - -// Int64 returns the value of v as an int64. If the ValueType of v is not an -// Int64ValueType, 0 is returned. -func (v Value) Int64() int64 { - if v.t == Int64ValueType { - // Assumes the correct int64 was stored in v.val based on type. - return int64(v.val) // nolint: gosec - } - return 0 -} - -// Float64 returns the value of v as an float64. If the ValueType of v is not -// an Float64ValueType, 0 is returned. -func (v Value) Float64() float64 { - if v.t == Float64ValueType { - return math.Float64frombits(v.val) - } - return 0 -} |