From f1cce2de3bcb802ff6486f7ef5d2d3782c33e466 Mon Sep 17 00:00:00 2001 From: Joshua MacDonald Date: Thu, 15 Aug 2024 07:43:37 -0700 Subject: [PATCH] Rename the experimental probability sampling specification (#4168) This reduces the number of lines of diff in PR 4166, which replaces the entire `tracestate-probability-sampling.md` file with new contents. Part of #4166. ## Changes Move a file, place a link to it and explain that a change is in progress. --- ...state-probability-sampling-experimental.md | 1061 +++++++++++++++++ .../trace/tracestate-probability-sampling.md | 1058 +--------------- 2 files changed, 1065 insertions(+), 1054 deletions(-) create mode 100644 specification/trace/tracestate-probability-sampling-experimental.md diff --git a/specification/trace/tracestate-probability-sampling-experimental.md b/specification/trace/tracestate-probability-sampling-experimental.md new file mode 100644 index 00000000000..9b6b10d92d8 --- /dev/null +++ b/specification/trace/tracestate-probability-sampling-experimental.md @@ -0,0 +1,1061 @@ + + +# TraceState: Probability Sampling + +**Status**: [Development](../document-status.md) + +
+Table of Contents + + + +- [Overview](#overview) + * [Definitions](#definitions) + + [Sampling](#sampling) + + [Adjusted count](#adjusted-count) + + [Sampler](#sampler) + + [Parent-based sampler](#parent-based-sampler) + + [Probability sampler](#probability-sampler) + + [Consistent probability sampler](#consistent-probability-sampler) + + [Trace completeness](#trace-completeness) + + [Non-probability sampler](#non-probability-sampler) + + [Always-on consistent probability sampler](#always-on-consistent-probability-sampler) + + [Always-off sampler](#always-off-sampler) +- [Consistent Probability sampling](#consistent-probability-sampling) + * [Conformance](#conformance) + * [Completeness guarantee](#completeness-guarantee) + * [Context invariants](#context-invariants) + + [Sampled flag](#sampled-flag) + - [Requirement: Inconsistent p-values are unset](#requirement-inconsistent-p-values-are-unset) + + [P-value](#p-value) + - [Requirement: Out-of-range p-values are unset](#requirement-out-of-range-p-values-are-unset) + + [R-value](#r-value) + - [Requirement: Out-of-range r-values unset both p and r](#requirement-out-of-range-r-values-unset-both-p-and-r) + - [Requirement: R-value is generated with the correct probabilities](#requirement-r-value-is-generated-with-the-correct-probabilities) + + [Examples: Context invariants](#examples-context-invariants) + - [Example: Probability sampled context](#example-probability-sampled-context) + - [Example: Probability unsampled](#example-probability-unsampled) + * [Samplers](#samplers) + + [ParentConsistentProbabilityBased sampler](#parentconsistentprobabilitybased-sampler) + - [Requirement: ParentConsistentProbabilityBased API](#requirement-parentconsistentprobabilitybased-api) + - [Requirement: ParentConsistentProbabilityBased does not modify valid tracestate](#requirement-parentconsistentprobabilitybased-does-not-modify-valid-tracestate) + - [Requirement: ParentConsistentProbabilityBased calls the configured root sampler for root spans](#requirement-parentconsistentprobabilitybased-calls-the-configured-root-sampler-for-root-spans) + - [Requirement: ParentConsistentProbabilityBased respects the sampled flag for non-root spans](#requirement-parentconsistentprobabilitybased-respects-the-sampled-flag-for-non-root-spans) + + [ConsistentProbabilityBased sampler](#consistentprobabilitybased-sampler) + - [Requirement: TraceIdRatioBased API compatibility](#requirement-traceidratiobased-api-compatibility) + - [Requirement: ConsistentProbabilityBased sampler sets r for root span](#requirement-consistentprobabilitybased-sampler-sets-r-for-root-span) + - [Requirement: ConsistentProbabilityBased sampler unsets p when not sampled](#requirement-consistentprobabilitybased-sampler-unsets-p-when-not-sampled) + - [Requirement: ConsistentProbabilityBased sampler sets p when sampled](#requirement-consistentprobabilitybased-sampler-sets-p-when-sampled) + - [Requirement: ConsistentProbabilityBased sampler records unbiased adjusted counts](#requirement-consistentprobabilitybased-sampler-records-unbiased-adjusted-counts) + - [Requirement: ConsistentProbabilityBased sampler sets r for non-root span](#requirement-consistentprobabilitybased-sampler-sets-r-for-non-root-span) + - [Requirement: ConsistentProbabilityBased sampler decides not to sample for probabilities less than 2**-62](#requirement-consistentprobabilitybased-sampler-decides-not-to-sample-for-probabilities-less-than-2-62) + + [Examples: Consistent probability samplers](#examples-consistent-probability-samplers) + - [Example: Setting R-value for a root span](#example-setting-r-value-for-a-root-span) + - [Example: Handling inconsistent P-value](#example-handling-inconsistent-p-value) + - [Example: Handling corrupt R-value](#example-handling-corrupt-r-value) + * [Composition rules](#composition-rules) + + [List of requirements](#list-of-requirements) + - [Requirement: Combining multiple sampling decisions using logical `or`](#requirement-combining-multiple-sampling-decisions-using-logical-or) + - [Requirement: Combine multiple consistent probability samplers using the minimum p-value](#requirement-combine-multiple-consistent-probability-samplers-using-the-minimum-p-value) + - [Requirement: Unset p when multiple consistent probability samplers decide not to sample](#requirement-unset-p-when-multiple-consistent-probability-samplers-decide-not-to-sample) + - [Requirement: Use probability sampler p-value when its decision to sample is combined with non-probability samplers](#requirement-use-probability-sampler-p-value-when-its-decision-to-sample-is-combined-with-non-probability-samplers) + - [Requirement: Use p-value 63 when a probability sampler decision not to sample is combined with a non-probability sampler decision to sample](#requirement-use-p-value-63-when-a-probability-sampler-decision-not-to-sample-is-combined-with-a-non-probability-sampler-decision-to-sample) + + [Examples: Composition](#examples-composition) + - [Example: Probability and non-probability sampler in a root context](#example-probability-and-non-probability-sampler-in-a-root-context) + - [Example: Two consistent probability samplers](#example-two-consistent-probability-samplers) + * [Producer and consumer recommendations](#producer-and-consumer-recommendations) + + [Trace producer: completeness](#trace-producer-completeness) + - [Recommendation: use non-descending power-of-two probabilities](#recommendation-use-non-descending-power-of-two-probabilities) + + [Trace producer: correctness](#trace-producer-correctness) + - [Recommendation: sampler delegation](#recommendation-sampler-delegation) + + [Trace producer: interoperability with `ParentBased` sampler](#trace-producer-interoperability-with-parentbased-sampler) + + [Trace producer: interoperability with `TraceIDRatioBased` sampler](#trace-producer-interoperability-with-traceidratiobased-sampler) + + [Trace consumer](#trace-consumer) + - [Recommendation: Recognize inconsistent r-values](#recommendation-recognize-inconsistent-r-values) + * [Appendix: Statistical test requirements](#appendix-statistical-test-requirements) + + [Test procedure: non-powers of two](#test-procedure-non-powers-of-two) + - [Requirement: Pass 12 non-power-of-two statistical tests](#requirement-pass-12-non-power-of-two-statistical-tests) + + [Test procedure: exact powers of two](#test-procedure-exact-powers-of-two) + - [Requirement: Pass 3 power-of-two statistical tests](#requirement-pass-3-power-of-two-statistical-tests) + + [Test implementation](#test-implementation) +- [Appendix](#appendix) + * [Methods for generating R-values](#methods-for-generating-r-values) + + + +
+ +## Overview + +Probability sampling allows OpenTelemetry tracing users to lower span +collection costs by the use of randomized sampling techniques. The +objectives are: + +- Compatible with the existing W3C trace context `sampled` flag +- Spans can be accurately counted using a Span-to-metrics pipeline +- Traces tend to be complete, even though spans may make independent sampling decisions. + +This document specifies an approach based on an "r-value" and a +"p-value". At a very high level, r-value is a source of randomness +and p-value encodes the sampling probability. A context is sampled +when `p <= r`. + +Significantly, by including the r-value and p-value in the +OpenTelemetry `tracestate`, these two values automatically propagate +through the context and are recorded on every Span. This allows Trace +consumers to correctly count spans simply by interpreting the p-value +on a given span. + +For efficiency, the supported sampling probabilities are limited to +powers of two. P-value is derived from sampling probability, which +equals `2**-p`, thus p-value is encoded using an unsigned integer. + +For example, a p-value of 3 indicates a sampling probability of 1/8. + +Since the W3C trace context does not specify that any of the 128 bits +in a TraceID are true uniform-distributed random bits, the r-value is +introduced as an additional source of randomness. + +The recommended method of generating an "r-value" is to count the +number of leading 0s in a string of 62 random bits, however, it is not +required to use this approach. + +### Definitions + +#### Sampling + +Sampling is a family of techniques for collecting and analyzing only a +fraction of a complete data set. Individual items that are "sampled" +are taken to represent one or more spans when collected and counted. +The representivity of each span is used in a Span-to-Metrics pipeline +to accurately count spans. + +Sampling terminology uses "population" to refer to the complete set of +data being sampled from. In OpenTelemetry tracing, "population" +refers to all spans. + +In probability sampling, the representivity of individual sample items +is generally known, whereas OpenTelemetry also recognizes +"non-probability" sampling approaches, in which representivity is not +explicitly quantified. + +#### Adjusted count + +Adjusted count is a measure of representivity, the number of spans in +the population that are represented by the individually sampled span. +Span-to-metrics pipelines can be built by adding the adjusted count of +each sample span to a counter of matching spans. + +For probability sampling, adjusted count is defined as the reciprocal +(i.e., mathematical inverse) of sampling probability. + +For non-probability sampling, adjusted count is unknown. + +Zero adjusted count is defined in a way that supports composition of +probability and non-probability sampling. Zero is assigned as the +adjusted count when a probability sampler does not select a span. + +Thus, there are three meaningfully distinct categories of adjusted count: + +| Adjusted count is | Interpretation | +| -- | -- | +| _Unknown_ | The adjusted count is not known, possibly as a result of a non-probability sampler. Items in this category should not be counted. | +| _Zero_ | The adjusted count is known; the effective count of the item is zero. | +| _Non-zero_ | The adjusted count is known; the effective count of the item is greater than zero. | + +#### Sampler + +A Sampler provides configurable logic, used by the SDK, for selecting +which Spans are "recorded" and/or "sampled" in a tracing client +library. To "record" a span means to build a representation of it in +the client's memory, which makes it eligible for being exported. To +"sample" a span implies setting the W3C `sampled` flag, recording the +span, and exporting the span when it is finished. + +OpenTelemetry supports spans that are "recorded" and not "sampled" +for in-process observability of live spans (e.g., z-pages). + +The Sampler interface and the built-in Samplers defined by +OpenTelemetry decide immediately whether to sample a span, and the +child context immediately propagates the decision. + +#### Parent-based sampler + +A Sampler that makes its decision to sample based on the W3C `sampled` +flag from the context is said to use parent-based sampling. + +#### Probability sampler + +A probability Sampler is a Sampler that knows immediately, for each +of its decisions, the probability that the span had of being selected. + +Sampling probability is defined as a number less than or equal to 1 +and greater than 0 (i.e., `0 < probability <= 1`). The case of 0 +probability is treated as a special, non-probabilistic case. + +#### Consistent probability sampler + +A consistent probability sampler is a Sampler that supports +independent sampling decisions at each span in a trace while +maintaining that traces will be complete with a certain minimum +probability across the trace. + +Consistent probability sampling requires that for any span in a given +trace, if a Sampler with lesser sampling probability selects the span +for sampling, then the span would also be selected by a Sampler +configured with greater sampling probability. + +#### Trace completeness + +A trace is said to be complete when all of the spans belonging to the +trace are collected. When at least one span is collected but not all +spans are collected, the trace is considered incomplete. + +Trace incompleteness may happen on purpose (e.g., through sampling +configuration), or by accident (e.g., through collection errors). The +OpenTelemetry trace data model supports a _one-way_ test for +incompleteness: for any non-root span, the trace is definitely +incomplete if the span's parent span was not collected. + +Incomplete traces that result from sampling configuration (i.e., on +purpose) are known as partial traces. An important subset of the +partial traces are those which are also complete subtraces. A +complete subtrace is defined at a span when every descendant span is +collected. + +Since the test for an incompleteness is one-way, it is important to +know which sampling configurations may lead to incomplete traces. +Sampling configurations that lead naturally to complete traces and +complete subtraces are [discussed below](#trace-producer-completeness). + +#### Non-probability sampler + +A non-probability sampler is a Sampler that makes its decisions not +based on chance, but instead uses arbitrary logic and internal state. +The adjusted count of spans sampled by a non-probability sampler is +unknown. + +#### Always-on consistent probability sampler + +An always-on sampler is another name for a consistent probability +sampler with probability equal to one. + +#### Always-off sampler + +An always-off Sampler has the effect of disabling a span completely, +effectively excluding it from the population. This is defined as a +non-probability sampler, not a zero-percent probability sampler, +because the spans are effectively unrepresented. + +## Consistent Probability sampling + +The consistent sampling scheme adopted by OpenTelemetry propagates two +values via the context, termed "p-value" and "r-value". + +Both fields are propagated via the OpenTelemetry `tracestate` under +the `ot` vendor tag using the rules for [tracestate +handling](tracestate-handling.md). Both fields are represented as +unsigned decimal integers requiring at most 6 bits of information. + +This sampling scheme selects items from among a fixed set of 63 +distinct probability values. The set of supported probabilities +includes the integer powers of two between 1 and 2**-62. Zero +probability and probabilities smaller than 2**-62 are treated as a +special case of "ConsistentAlwaysOff" sampler, just as unit +probability (i.e., 100%) describes a special case of +"ConsistentAlwaysOn" sampler. + +R-value encodes which among the 63 possibilities will consistently +decide to sample for a given trace. Specifically, r-value specifies +the smallest probability that will decide to sample a given trace in +terms of the corresponding p-value. For example, a trace with r-value +0 will sample spans configured for 100% sampling, while r-value 1 will +sample spans configured for 50% or 100% sampling, and so on through +r-value 62, for which a consistent probability sampler will decide +"yes" at every supported probability (i.e., greater than or equal to +2**-62). + +P-value encodes the adjusted count for child contexts (i.e., consumers +of `tracestate`) and consumers of sampled spans to record for use in +Span-to-metrics pipelines. A special p-value of 63 is defined to mean +zero adjusted count, which helps define composition rules for +non-probability samplers. + +An invariant will be stated that connects the `sampled` trace flag +found in `traceparent` context to the r-value and p-value found in +`tracestate` context. + +### Conformance + +Consumers of OpenTelemetry `tracestate` data are expected to validate +the probability sampling fields before interpreting the data. This +applies to the two samplers specified here as well as consumers of +span data, who are expected to validate `tracestate` before +interpreting span adjusted counts. + +Producers of OpenTelemetry `tracestate` containing p-value and r-value +fields are required to meet the behavioral requirements stated for the +`ConsistentProbabilityBased` sampler and to ensure statistically valid +outcomes. A test suite is included in this specification so that +users and consumers of OpenTelemetry `tracestate` can be assured of +accuracy in Span-to-metrics pipelines. + +### Completeness guarantee + +This specification defines consistent sampling for power-of-two +sampling probabilities. When a sampler is configured with a +non-power-of-two sampling probability, the sampler will +probabilistically choose between the nearest powers of two. + +When a single consistent probability sampler is used at the root of a +trace and all other spans use a parent-based sampler, the resulting +traces are always complete (ignoring collection errors). This +property holds even for non-power-of-two sampling probabilities. + +When multiple consistent probability samplers are used in the same +trace, in general, trace completeness is ensured at the smallest power +of two greater than or equal to the minimum sampling probability +across the trace. + +### Context invariants + +The W3C `traceparent` (version 0) contains three fields of +information: the TraceId, the SpanId, and the trace flags. The +`sampled` trace flag has been defined by W3C to signal an intent to +sample the context. + +The [Sampler API](sdk.md#sampler) is responsible for setting the +`sampled` flag and the `tracestate`. + +P-value and r-value are set in the OpenTelemetry `tracestate`, under +the vendor tag `ot`, using the identifiers `p` and `r`. P-value is an +unsigned integer valid in the inclusive range `[0, 63]` (i.e., there +are 64 valid values). R-value is an unsigned integer valid in the +inclusive range `[0, 62]` (i.e., there are 63 valid values). P-value +and r-value are independent settings, each can be meaningfully set +without the other present. + +#### Sampled flag + +Probability sampling uses additional information to enable consistent +decision making and to record the adjusted count of sampled spans. +When both values are defined and in the specified range, the invariant +between r-value and p-value and the `sampled` trace flag states that +`((p <= r) == sampled) OR (sampled AND (p == 63)) == TRUE`. + +The invariant between `sampled`, `p`, and `r` only applies when both +`p` and `r` are present. When the invariant is violated, the +`sampled` flag takes precedence and `p` is unset from `tracestate` in +order to signal unknown adjusted count. + +##### Requirement: Inconsistent p-values are unset + +Samplers SHOULD unset `p` when the invariant between the `sampled`, +`p`, and `r` values is violated before using the `tracestate` to make +a sampling decision or interpret adjusted count. + +#### P-value + +Zero adjusted count is represented by the special p-value 63, +otherwise the p-value is set to the negative base-2 logarithm of +sampling probability: + +| p-value | Parent Probability | Adjusted count | +| ----- | ----------- | -- | +| 0 | 1 | 1 | +| 1 | 1/2 | 2 | +| 2 | 1/4 | 4 | +| ... | ... | ... | +| N | 2**-N | 2**N | +| ... | ... | ... | +| 61 | 2**-61 | 2**61 | +| 62 | 2**-62 | 2**62 | +| 63 | 0 | 0 | + +##### Requirement: Out-of-range p-values are unset + +Consumers SHOULD unset `p` from the `tracestate` if the unsigned +decimal value is greater than 63 before using the `tracestate` to make +a sampling decision or interpret adjusted count. + +#### R-value + +R-value is set in the `tracestate` by the Sampler at the root of the +trace, in order to support consistent probability sampling. When the +value is omitted or not present, child spans in the trace are not able +to participate in consistent probability sampling. + +R-value determines which sampling probabilities will decide to sample +or not decide to sample for spans of a given trace, as follows: + +| r-value | Implied sampling probabilities | +| ---------------- | ---------------------- | +| 0 | 1 | +| 1 | 1/2 and above | +| 2 | 1/4 and above | +| 3 | 1/8 and above | +| ... | ... | +| 0 <= r <= 61 | 2**-r and above | +| ... | ... | +| 59 | 2**-59 and above | +| 60 | 2**-60 and above | +| 61 | 2**-61 and above | +| 62 | 2**-62 and above | + +These probabilities are specified to ensure that conforming Sampler +implementations record spans with correct adjusted counts. The +recommended method of generating r-values is to count the number of +leading 0s in a string of 62 random bits, however it is not required +to use this approach. + +##### Requirement: Out-of-range r-values unset both p and r + +Samplers SHOULD unset both `r` and `p` from the `tracestate` if the +unsigned decimal value of `r` is greater than 62 before using the +`tracestate` to make a sampling decision. + +##### Requirement: R-value is generated with the correct probabilities + +Samplers MUST generate r-values using a randomized scheme that +produces each value with the probabilities equivalent to those +produced by counting the number of leading 0s in a string of 62 random +bits. + +#### Examples: Context invariants + +##### Example: Probability sampled context + +Consider a trace context with the following headers: + +``` +traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 +tracestate: ot=r:3;p:2 +``` + +The `traceparent` contents in this example example are repeated from +the [W3C specification](https://www.w3.org/TR/trace-context/#examples-of-http-traceparent-headers)) +and have the following base64-encoded field values: + +``` +base16(version) = 00 +base16(trace-id) = 4bf92f3577b34da6a3ce929d0e0e4736 +base16(parent-id) = 00f067aa0ba902b7 +base16(trace-flags) = 01 // (i.e., sampled) +``` + +The `tracestate` header contains OpenTelemetry string `r:3;p:2`, +containing decimal-encoded p-value and r-value: + +``` +base10(r) = 3 +base10(p) = 2 +``` + +Here, r-value 3 indicates that a consistent probability sampler +configured with probability 12.5% (i.e., 1-in-8) or greater will +sample the trace. The p-value 2 indicates that the parent that set +the `sampled` flag was configured to sample at 25% (i.e., 1-in-4). +This trace context is consistent because `p <= r` is true and the +`sampled` flag is set. + +##### Example: Probability unsampled + +This example has an unsampled context where only the r-value is set. + +``` +traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-00 +tracestate: ot=r:3 +``` + +This supports consistent probability sampling in child contexts by +virtue of having an r-value. P-value is not set, consistent with an +unsampled context. + +### Samplers + +#### ParentConsistentProbabilityBased sampler + +The `ParentConsistentProbabilityBased` sampler is meant as an optional +replacement for the [`ParentBased` Sampler](sdk.md#parentbased). It is +required to first validate the `tracestate` and then respect the +`sampled` flag in the W3C traceparent. + +##### Requirement: ParentConsistentProbabilityBased API + +The `ParentConsistentProbabilityBased` Sampler constructor SHOULD take +a single Sampler argument, which is the Sampler to use in case the +`ParentConsistentProbabilityBased` Sampler is called for a root span. + +##### Requirement: ParentConsistentProbabilityBased does not modify valid tracestate + +The `ParentConsistentProbabilityBased` Sampler MUST NOT modify a +valid `tracestate`. + +##### Requirement: ParentConsistentProbabilityBased calls the configured root sampler for root spans + +The `ParentConsistentProbabilityBased` Sampler MUST delegate to the +configured root Sampler when there is not a valid parent trace context. + +##### Requirement: ParentConsistentProbabilityBased respects the sampled flag for non-root spans + +The `ParentConsistentProbabilityBased` Sampler MUST decide to sample +the span according to the value of the `sampled` flag in the W3C +traceparent header. + +#### ConsistentProbabilityBased sampler + +The `ConsistentProbabilityBased` sampler is meant as an optional +replacement for the [`TraceIdRatioBased` +Sampler](sdk.md#traceidratiobased). In the case where it is used as a +root sampler, the `ConsistentProbabilityBased` sampler is required to +produce a valid `tracestate`. In the case where it is used in a +non-root context, it is required to validate the incoming `tracestate` +and to produce a valid `tracestate` for the outgoing context. + +The `ConsistentProbabilityBased` sampler is required to support +probabilities that are not exact powers of two. To do so, +implementations are required to select between the nearest powers of +two probabilistically. For example, 5% sampling can be achieved by +selecting 1/16 sampling 60% of the time and 1/32 sampling 40% of the +time. + +##### Requirement: TraceIdRatioBased API compatibility + +The `ConsistentProbabilityBased` Sampler MUST have the same +constructor signature as the built-in `TraceIdRatioBased` sampler in +each OpenTelemetry SDK. + +##### Requirement: ConsistentProbabilityBased sampler sets r for root span + +The `ConsistentProbabilityBased` Sampler MUST set `r` when it makes a +root sampling decision. + +##### Requirement: ConsistentProbabilityBased sampler unsets p when not sampled + +The `ConsistentProbabilityBased` Sampler MUST unset `p` from the +`tracestate` when it decides not to sample. + +##### Requirement: ConsistentProbabilityBased sampler sets p when sampled + +The `ConsistentProbabilityBased` Sampler MUST set `p` when it decides +to sample according to its configured sampling probability. + +##### Requirement: ConsistentProbabilityBased sampler records unbiased adjusted counts + +The `ConsistentProbabilityBased` Sampler with non-zero probability +MUST set `p` so that the adjusted count interpreted from the +`tracestate` is an unbiased estimate of the number of representative +spans in the population. + +##### Requirement: ConsistentProbabilityBased sampler sets r for non-root span + +If `r` is not set on the input `tracecontext` and the Span is not a +root span, `ConsistentProbabilityBased` SHOULD set `r` as if it were a +root span and warn the user that a potentially inconsistent trace +is being produced. + +##### Requirement: ConsistentProbabilityBased sampler decides not to sample for probabilities less than 2**-62 + +If the configured sampling probability is in the interval `[0, +2**-62)`, the Sampler MUST decide not to sample. + +#### Examples: Consistent probability samplers + +##### Example: Setting R-value for a root span + +A new root span is sampled by a consistent probability sampler at 25%. +A new r-value should be generated (see the appendix for suitable +methods), in this example r-value 5 is used which happens 1.5625% of +the time and indicates to sample: + +``` +tracestate: ot=r:5;p:2 +``` + +The span would be sampled because p-value 2 is less than or equal to +r-value 5. An example `tracestate` where r-value 1 indicates not to +sample at 25%: + +``` +tracestate: ot=r:1 +``` + +This span would not be sampled because p-value 2 (corresponding with +25% sampling) is greater than r-value 1. + +##### Example: Handling inconsistent P-value + +When either the consistent probability sampler or the parent-based +consistent probability sampler receives a sampled context but +invalid p-value, for example, + +``` +tracestate: ot=r:4;p:73 +``` + +the `tracestate` will have its p-value stripped. The r-value is kept, +and the sampler should act as if the following had been received: + +``` +tracestate: ot=r:4 +``` + +The consistent probability sampler will make its own (consistent) +decision using the r-value that was received. + +The parent-based consistent probability sampler will in this case +follow the `sampled` flag. If the context is sampled, the resulting +span will have an r-value without a p-value, which indicates unknown +adjusted count. + +##### Example: Handling corrupt R-value + +A non-root span receives: + +``` +tracestate: ot=r:100;p:10 +``` + +where the r-value is out of its valid range. The r-value and p-value +are stripped during validation, according to the invariants. In this +case, the sampler will act as though no `tracestate` were received. + +The parent-based consistent probability sampler will sample or not +sample based on the `sampled` flag, in this case. If the context is +sampled, the recorded span will have an r-value without a p-value, +which indicates unknown adjusted count. + +The consistent probability sampler will generate a new r-value and +make a new sampling decision while warning the user of a corrupt and +potentially inconsistent r-value. + +### Composition rules + +When more than one Sampler participates in the decision to sample a +context, their decisions can be combined using composition rules. In +all cases, the combined decision to sample is the logical-OR of the +Samplers' decisions (i.e., sample if at least one of the composite +Samplers decides to sample). + +To combine p-values from two consistent probability Sampler decisions, +the Sampler with the greater probability takes effect. The output +p-value becomes the minimum of the two values for `p`. + +To combine a consistent probability Sampler decision with a +non-probability Sampler decision, p-value 63 is used to signify zero +adjusted count. If the probability Sampler decides to sample, its +p-value takes effect. If the probability Sampler decides not to +sample when the non-probability sample does sample, p-value 63 takes +effect signifying zero adjusted count. + +#### List of requirements + +##### Requirement: Combining multiple sampling decisions using logical `or` + +When multiple samplers are combined using composition, the sampling +decision MUST be to sample if at least one of the combined samplers +decides to sample. + +##### Requirement: Combine multiple consistent probability samplers using the minimum p-value + +When combining Sampler decisions for multiple consistent probability +Samplers and at least one decides to sample, the minimum of the "yes" +decision `p` values MUST be set in the `tracestate`. + +##### Requirement: Unset p when multiple consistent probability samplers decide not to sample + +When combining Sampler decisions for multiple consistent probability +Samplers and none decides to sample, p-value MUST be unset in the +`tracestate`. + +##### Requirement: Use probability sampler p-value when its decision to sample is combined with non-probability samplers + +When combining Sampler decisions for a consistent probability Sampler +and a non-probability Sampler, and the probability Sampler decides to +sample, its p-value MUST be set in the `tracestate` regardless of the +non-probability Sampler decision. + +##### Requirement: Use p-value 63 when a probability sampler decision not to sample is combined with a non-probability sampler decision to sample + +When combining Sampler decisions for a consistent probability Sampler +and a non-probability Sampler, and the probability Sampler decides not +to sample but the non-probability does sample, p-value 63 MUST be set +in the `tracestate`. + +#### Examples: Composition + +##### Example: Probability and non-probability sampler in a root context + +In a new root context, a consistent probability sampler decides not to +set the sampled flag, adds `r:4` indicating that the trace is +consistently sampled at 6.5% (i.e., 1-in-16) and larger probabilities. + +The probability sampler decision is composed with a non-probability +sampler that decides to sample the context. Setting `sampled` when +the probability sampler has not sampled requires setting `p:63`, +indicating zero adjusted count. + +The resulting context: + +``` +traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 +tracestate: ot=r:4;p:63 +``` + +##### Example: Two consistent probability samplers + +Whether a root or non-root, if multiple consistent probability +samplers make a decision to sample a given context, the minimum +p-value is output in the tracestate. + +If a root context, the first of the samplers generates `r:15` and its +own p-value `p:10` (i.e., adjusted count 1024). The second of the two +probability samplers outputs a smaller adjusted count `p:8` (i.e., +adjusted count 256). + +The resulting context takes the smaller p-value: + +``` +traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 +tracestate: ot=r:15;p:8 +``` + +### Producer and consumer recommendations + +#### Trace producer: completeness + +As stated in the [completeness guarantee](#completeness-guarantee), +traces will be possibly incomplete when configuring multiple +consistent probability samplers in the same trace. One way to avoid +producing incomplete traces is to use parent-based samplers except for +root spans. + +There is a simple test for trace incompleteness, but it is a one-way +test and does not detect when child spans are uncollected. One way to +avoid producing incomplete traces is to avoid configuring +non-power-of-two sampling probabilities for non-root spans, because +completeness is not guaranteed for non-power-of-two sampling +probabilities. + +##### Recommendation: use non-descending power-of-two probabilities + +Complete subtraces will be produced when the sequence of sampling +probabilities from the root of a trace to its leaves consists of +non-descending powers of two. To ensure complete sub-traces are +produced, child samplers SHOULD be configured with a power-of-two +probability greater than or equal to the parent span's sampling +probability. + +#### Trace producer: correctness + +The use of tracestate to convey adjusted count information rests upon +trust between participants in a trace. Users are advised not to use a +Span-to-metrics pipeline when the parent sampling decision's +corresponding adjusted count is untrustworthy. + +The `ConsistentProbabilityBased` and +`ParentConsistentProbabilityBased` samplers can be used as delegates +of another sampler, for conditioning the choice of sampler on span and +other fixed attributes. However, for adjusted counts to be +trustworthy, the choice of non-root sampler cannot be conditioned on +the parent's sampled trace flag or the OpenTelemetry tracestate +r-value and p-value, as these decisions would lead to incorrect +adjusted counts. + +For example, the built-in [`ParentBased` sampler](sdk.md#parentbased) +supports configuring the delegated-to sampler based on whether the parent +context is remote or non-remote, sampled or unsampled. If a +`ParentBased` sampler delegates to a `ConsistentProbabilityBased` +sampler only for unsampled contexts, the resulting Span-to-metrics +pipeline will (probably) overcount spans. + +##### Recommendation: sampler delegation + +For non-root spans, composite samplers SHOULD NOT condition the choice +of delegated-to sampler based on the parent's sampled flag or +OpenTelemetry tracestate. + +#### Trace producer: interoperability with `ParentBased` sampler + +The OpenTelemetry built-in `ParentBased` sampler is interoperable with +the `ConsistentProbabilityBased` sampler, provided that the +delegated-to sampler does not change the decision that determined its +selection. For example, it is safe to configure an alternate +`ParentBased` sampler delegate for unsampled spans, provided the +decision does not change to sampled. + +Because the `ParentBased` sampler honors the sampled trace flag, and +OpenTelemetry SDKs include the tracestate in the `Span` data, which +means a system can be upgraded to probability sampling by just +replacing `TraceIDRatioBased` samplers with conforming +`ConsistentProbabilityBased` samplers everywhere in the trace. + +#### Trace producer: interoperability with `TraceIDRatioBased` sampler + +The [`TraceIDRatioBased` specification](sdk.md#traceidratiobased) +includes a RECOMMENDATION against being used for non-root spans +because it does not specify how to make the sampler decision +consistent across the trace. A `TraceIDRatioBased` sampler at the +root span is interoperable with a `ConsistentParentProbabilityBased` +sampler in terms of completeness, although the resulting spans will +have unknown adjusted count. + +When a `TraceIDRatioBased` sampler is configured for a non-root span, +several cases arise where an incorrect OpenTelemetry tracestate can be +generated. Consider for example a trace with three spans where the +root (R) has a `ConsistentProbabilityBased` sampler, the root's child +(P) has a `TraceIDRatioBased` sampler, and the grand-child (C) has a +`ParentBased` sampler. Because the `TraceIDRatioBased` sampler change +the intermediate sampled flag without updating the OpenTelemetry +tracestate, we have the following cases: + +1. If `TraceIDRatioBased` does not change P's decision, the trace is + complete and all spans' adjusted counts are correct. +2. If `TraceIDRatioBased` changes P's decision from no to yes, the + consumer will observe a (definitely) incomplete trace containing P + and C. Both spans will have invalid OpenTelemetry tracestate, + leading to unknown adjusted count in this case. +3. If `TraceIDRatioBased` changes the sampling decision from yes to + no, the consumer will observe singleton trace with correct adjusted + count. The consumer cannot determine that R has two unsampled + descendants. + +As these cases demonstrate, users can expect incompleteness and +unknown adjusted count when using `TraceIDRatioBased` samplers for +non-root spans, but this goes against the originally specified +warning. + +#### Trace consumer + +Trace consumers are expected to apply the simple one-way test for +incompleteness. When non-root spans are configured with independent +sampling probabilities, traces may be complete in a way that cannot be +detected. Because of the one-way test, consumers wanting to ensure +complete traces are expected to know the minimum sampling probability +across the system. + +Ignoring accidental data loss, a trace will be complete if all its +spans are sampled with consistent probability samplers and the trace's +r-value is larger than the corresponding smallest power of two greater +than or equal to the minimum sampling probability across the trace. + +Due to the `ConsistentProbabilityBased` Sampler requirement about +setting `r` when it is unset for a non-root span, trace consumers are +advised to check traces for r-value consistency. When a single trace +contains more than a single distinct `r` value, it means the trace was +not correctly sampled at the root for probability sampling. While the +adjusted count of each span is correct in this scenario, it may be +impossible to detect complete traces. + +##### Recommendation: Recognize inconsistent r-values + +When a single trace contains spans with `tracestate` values containing +more than one distinct value for `r`, the consumer SHOULD recognize +the trace as inconsistently sampled. + +### Appendix: Statistical test requirements + +This section specifies a test that can be implemented to ensure basic +conformance with the requirement that sampling decisions are unbiased. + +The goal of this test specification is to be simple to implement and +not require advanced statistical skills or libraries to be successful. + +This test is not meant to evaluate the performance of a random number +generator. This test assumes the underlying RNG is of good quality +and checks that the sampler produces the expected proportionality with +a high degree of statistical confidence. + +One of the challenges of this kind of test is that probabilistic tests +are expected to occasionally produce exceptional results. To make +this a strict test for random behavior, we take the following approach: + +- Generate a pre-determined list of 20 random seeds +- Use fixed values for significance level (5%) and trials (20) +- Use a population size of 100,000 spans +- For each trial, simulate the population and compute ChiSquared + test statistic +- Locate the first seed value in the ordered list such that the + Chi-Squared significance test fails exactly once out of 20 trials + +To create this test, perform the above sequence using the seed values +from the predetermined list, in order, until a seed value is found +with exactly one failure. This is expected to happen fairly often and +is required to happen once among the 20 available seeds. After +calculating the index of the first seed with exactly one ChiSquared +failure, record it in the test. For continuous integration testing, +it is only necessary to re-run the test using the predetermined seed +index. + +As specified, the Chi-Squared test has either one or two degrees of +freedom, depending on whether the sampling probability is an exact +power of two or not. + +#### Test procedure: non-powers of two + +In this case there are two degrees of freedom for the Chi-Squared test. +The following table summarizes the test parameters. + +| Test case | Sampling probability | Lower, Upper p-value when sampled | Expectlower | Expectupper | Expectunsampled | +|-----------|----------------------|-----------------------------------|------------------------|------------------------|----------------------------| +| 1 | 0.900000 | 0, 1 | 10000 | 80000 | 10000 | +| 2 | 0.600000 | 0, 1 | 40000 | 20000 | 40000 | +| 3 | 0.330000 | 1, 2 | 17000 | 16000 | 67000 | +| 4 | 0.130000 | 2, 3 | 12000 | 1000 | 87000 | +| 5 | 0.100000 | 3, 4 | 2500 | 7500 | 90000 | +| 6 | 0.050000 | 4, 5 | 1250 | 3750 | 95000 | +| 7 | 0.017000 | 5, 6 | 1425 | 275 | 98300 | +| 8 | 0.010000 | 6, 7 | 562.5 | 437.5 | 99000 | +| 9 | 0.005000 | 7, 8 | 281.25 | 218.75 | 99500 | +| 10 | 0.002900 | 8, 9 | 100.625 | 189.375 | 99710 | +| 11 | 0.001000 | 9, 10 | 95.3125 | 4.6875 | 99900 | +| 12 | 0.000500 | 10, 11 | 47.65625 | 2.34375 | 99950 | + +The formula for computing Chi-Squared in this case is: + +``` +ChiSquared = math.Pow(sampled_lowerP - expect_lowerP, 2) / expect_lowerP + + math.Pow(sampled_upperP - expect_upperP, 2) / expect_upperP + + math.Pow(100000 - sampled_lowerP - sampled_upperP - expect_unsampled, 2) / expect_unsampled +``` + +This should be compared with 0.102587, the value of the Chi-Squared +distribution for two degrees of freedom with significance level 5%. +For each probability in the table above, the test is required to +demonstrate a seed that produces exactly one ChiSquared value less +than 0.102587. + +##### Requirement: Pass 12 non-power-of-two statistical tests + +For the test with 20 trials and 100,000 spans each, the test MUST +demonstrate a random number generator seed such that the ChiSquared +test statistic is below 0.102587 exactly 1 out of 20 times. + +#### Test procedure: exact powers of two + +In this case there is one degree of freedom for the Chi-Squared test. +The following table summarizes the test parameters. + +| Test case | Sampling probability | P-value when sampled | Expectsampled | Expectunsampled | +|-----------|----------------------|----------------------|--------------------------|----------------------------| +| 13 | 0x1p-01 (0.500000) | 1 | 50000 | 50000 | +| 14 | 0x1p-04 (0.062500) | 4 | 6250 | 93750 | +| 15 | 0x1p-07 (0.007812) | 7 | 781.25 | 99218.75 | + +The formula for computing Chi-Squared in this case is: + +``` +ChiSquared = math.Pow(sampled - expect_sampled, 2) / expect_sampled + + math.Pow(100000 - sampled - expect_unsampled, 2) / expect_unsampled +``` + +This should be compared with 0.003932, the value of the Chi-Squared +distribution for one degree of freedom with significance level 5%. +For each probability in the table above, the test is required to +demonstrate a seed that produces exactly one ChiSquared value less +than 0.003932. + +##### Requirement: Pass 3 power-of-two statistical tests + +For the test with 20 trials and 100,000 spans each, the test MUST +demonstrate a random number generator seed such that the ChiSquared +test statistic is below 0.003932 exactly 1 out of 20 times. + +#### Test implementation + +The recommended structure for this test uses a table listing the 15 +probability values, the expected p-values, whether the ChiSquared +statistic has one or two degrees of freedom, and the index into the +predetermined list of seeds. + +``` + for _, test := range []testCase{ + // Non-powers of two + {0.90000, 1, twoDegrees, 3}, + {0.60000, 1, twoDegrees, 2}, + {0.33000, 2, twoDegrees, 2}, + {0.13000, 3, twoDegrees, 1}, + {0.10000, 4, twoDegrees, 0}, + {0.05000, 5, twoDegrees, 0}, + {0.01700, 6, twoDegrees, 2}, + {0.01000, 7, twoDegrees, 2}, + {0.00500, 8, twoDegrees, 2}, + {0.00290, 9, twoDegrees, 4}, + {0.00100, 10, twoDegrees, 6}, + {0.00050, 11, twoDegrees, 0}, + + // Powers of two + {0x1p-1, 1, oneDegree, 0}, + {0x1p-4, 4, oneDegree, 0}, + {0x1p-7, 7, oneDegree, 1}, + } { +``` + +Note that seed indexes in the example above have what appears to be +the correct distribution. The five 0s, two 1s, five 2s, one 3s, and +one 4 demonstrate that it is relatively easy to find examples where +there is exactly one failure. Probability 0.001, with seed index 6 in +this case, is a reminder that outliers exist. Further significance +testing of this distribution is not recommended. + +## Appendix + +### Methods for generating R-values + +The method used for generating r-values is not specified, in order to +leave the implementation freedom to optimize. Typically, when the +TraceId is known to contain at a 62-bit substring of random bits, +R-values can be derived directly from the 62 random bits of TraceId +by: + +1. Count the leading zeros +2. Count the leading ones +3. Count the trailing zeros +4. Count the trailing ones. + +```golang +import ( + "math/rand" + "math/bits" +) + +func nextRValueLeading() int { + x := uint64(rand.Int63()) // 63 least-significant bits are random + y := x << 1 | 0x3 // 62 most-significant bits are random + return bits.LeadingZeros64(y) +} +``` + +If the TraceId contains unknown or insufficient randomness, another +approach is to generate random bits until the first true or false +value. + +``` +func nextRValueGenerated() int { + for r := 0; r < 62; r++ { + if rand.Bool() == true { + return r + } + } + return 62 +} +``` + +Any scheme that produces r-values shown in the following table is +considered conforming. + +| r-value | Probability of r-value | +| ---------------- | ------------------------ | +| 0 | 1/2 | +| 1 | 1/4 | +| 2 | 1/8 | +| 3 | 1/16 | +| ... | ... | +| 0 <= r <= 61 | 2**-(r+1) | +| ... | ... | +| 59 | 2**-60 | +| 60 | 2**-61 | +| 61 | 2**-62 | +| 62 | 2**-62 | diff --git a/specification/trace/tracestate-probability-sampling.md b/specification/trace/tracestate-probability-sampling.md index 9b6b10d92d8..8a6d769a9ef 100644 --- a/specification/trace/tracestate-probability-sampling.md +++ b/specification/trace/tracestate-probability-sampling.md @@ -1,1061 +1,11 @@ -# TraceState: Probability Sampling +# TraceState Probability Sampling **Status**: [Development](../document-status.md) -
-Table of Contents +The contents of the [experimental probability sampling specification](./tracestate-probability-sampling-experimental.md) have been saved for future reference. - - -- [Overview](#overview) - * [Definitions](#definitions) - + [Sampling](#sampling) - + [Adjusted count](#adjusted-count) - + [Sampler](#sampler) - + [Parent-based sampler](#parent-based-sampler) - + [Probability sampler](#probability-sampler) - + [Consistent probability sampler](#consistent-probability-sampler) - + [Trace completeness](#trace-completeness) - + [Non-probability sampler](#non-probability-sampler) - + [Always-on consistent probability sampler](#always-on-consistent-probability-sampler) - + [Always-off sampler](#always-off-sampler) -- [Consistent Probability sampling](#consistent-probability-sampling) - * [Conformance](#conformance) - * [Completeness guarantee](#completeness-guarantee) - * [Context invariants](#context-invariants) - + [Sampled flag](#sampled-flag) - - [Requirement: Inconsistent p-values are unset](#requirement-inconsistent-p-values-are-unset) - + [P-value](#p-value) - - [Requirement: Out-of-range p-values are unset](#requirement-out-of-range-p-values-are-unset) - + [R-value](#r-value) - - [Requirement: Out-of-range r-values unset both p and r](#requirement-out-of-range-r-values-unset-both-p-and-r) - - [Requirement: R-value is generated with the correct probabilities](#requirement-r-value-is-generated-with-the-correct-probabilities) - + [Examples: Context invariants](#examples-context-invariants) - - [Example: Probability sampled context](#example-probability-sampled-context) - - [Example: Probability unsampled](#example-probability-unsampled) - * [Samplers](#samplers) - + [ParentConsistentProbabilityBased sampler](#parentconsistentprobabilitybased-sampler) - - [Requirement: ParentConsistentProbabilityBased API](#requirement-parentconsistentprobabilitybased-api) - - [Requirement: ParentConsistentProbabilityBased does not modify valid tracestate](#requirement-parentconsistentprobabilitybased-does-not-modify-valid-tracestate) - - [Requirement: ParentConsistentProbabilityBased calls the configured root sampler for root spans](#requirement-parentconsistentprobabilitybased-calls-the-configured-root-sampler-for-root-spans) - - [Requirement: ParentConsistentProbabilityBased respects the sampled flag for non-root spans](#requirement-parentconsistentprobabilitybased-respects-the-sampled-flag-for-non-root-spans) - + [ConsistentProbabilityBased sampler](#consistentprobabilitybased-sampler) - - [Requirement: TraceIdRatioBased API compatibility](#requirement-traceidratiobased-api-compatibility) - - [Requirement: ConsistentProbabilityBased sampler sets r for root span](#requirement-consistentprobabilitybased-sampler-sets-r-for-root-span) - - [Requirement: ConsistentProbabilityBased sampler unsets p when not sampled](#requirement-consistentprobabilitybased-sampler-unsets-p-when-not-sampled) - - [Requirement: ConsistentProbabilityBased sampler sets p when sampled](#requirement-consistentprobabilitybased-sampler-sets-p-when-sampled) - - [Requirement: ConsistentProbabilityBased sampler records unbiased adjusted counts](#requirement-consistentprobabilitybased-sampler-records-unbiased-adjusted-counts) - - [Requirement: ConsistentProbabilityBased sampler sets r for non-root span](#requirement-consistentprobabilitybased-sampler-sets-r-for-non-root-span) - - [Requirement: ConsistentProbabilityBased sampler decides not to sample for probabilities less than 2**-62](#requirement-consistentprobabilitybased-sampler-decides-not-to-sample-for-probabilities-less-than-2-62) - + [Examples: Consistent probability samplers](#examples-consistent-probability-samplers) - - [Example: Setting R-value for a root span](#example-setting-r-value-for-a-root-span) - - [Example: Handling inconsistent P-value](#example-handling-inconsistent-p-value) - - [Example: Handling corrupt R-value](#example-handling-corrupt-r-value) - * [Composition rules](#composition-rules) - + [List of requirements](#list-of-requirements) - - [Requirement: Combining multiple sampling decisions using logical `or`](#requirement-combining-multiple-sampling-decisions-using-logical-or) - - [Requirement: Combine multiple consistent probability samplers using the minimum p-value](#requirement-combine-multiple-consistent-probability-samplers-using-the-minimum-p-value) - - [Requirement: Unset p when multiple consistent probability samplers decide not to sample](#requirement-unset-p-when-multiple-consistent-probability-samplers-decide-not-to-sample) - - [Requirement: Use probability sampler p-value when its decision to sample is combined with non-probability samplers](#requirement-use-probability-sampler-p-value-when-its-decision-to-sample-is-combined-with-non-probability-samplers) - - [Requirement: Use p-value 63 when a probability sampler decision not to sample is combined with a non-probability sampler decision to sample](#requirement-use-p-value-63-when-a-probability-sampler-decision-not-to-sample-is-combined-with-a-non-probability-sampler-decision-to-sample) - + [Examples: Composition](#examples-composition) - - [Example: Probability and non-probability sampler in a root context](#example-probability-and-non-probability-sampler-in-a-root-context) - - [Example: Two consistent probability samplers](#example-two-consistent-probability-samplers) - * [Producer and consumer recommendations](#producer-and-consumer-recommendations) - + [Trace producer: completeness](#trace-producer-completeness) - - [Recommendation: use non-descending power-of-two probabilities](#recommendation-use-non-descending-power-of-two-probabilities) - + [Trace producer: correctness](#trace-producer-correctness) - - [Recommendation: sampler delegation](#recommendation-sampler-delegation) - + [Trace producer: interoperability with `ParentBased` sampler](#trace-producer-interoperability-with-parentbased-sampler) - + [Trace producer: interoperability with `TraceIDRatioBased` sampler](#trace-producer-interoperability-with-traceidratiobased-sampler) - + [Trace consumer](#trace-consumer) - - [Recommendation: Recognize inconsistent r-values](#recommendation-recognize-inconsistent-r-values) - * [Appendix: Statistical test requirements](#appendix-statistical-test-requirements) - + [Test procedure: non-powers of two](#test-procedure-non-powers-of-two) - - [Requirement: Pass 12 non-power-of-two statistical tests](#requirement-pass-12-non-power-of-two-statistical-tests) - + [Test procedure: exact powers of two](#test-procedure-exact-powers-of-two) - - [Requirement: Pass 3 power-of-two statistical tests](#requirement-pass-3-power-of-two-statistical-tests) - + [Test implementation](#test-implementation) -- [Appendix](#appendix) - * [Methods for generating R-values](#methods-for-generating-r-values) - - - -
- -## Overview - -Probability sampling allows OpenTelemetry tracing users to lower span -collection costs by the use of randomized sampling techniques. The -objectives are: - -- Compatible with the existing W3C trace context `sampled` flag -- Spans can be accurately counted using a Span-to-metrics pipeline -- Traces tend to be complete, even though spans may make independent sampling decisions. - -This document specifies an approach based on an "r-value" and a -"p-value". At a very high level, r-value is a source of randomness -and p-value encodes the sampling probability. A context is sampled -when `p <= r`. - -Significantly, by including the r-value and p-value in the -OpenTelemetry `tracestate`, these two values automatically propagate -through the context and are recorded on every Span. This allows Trace -consumers to correctly count spans simply by interpreting the p-value -on a given span. - -For efficiency, the supported sampling probabilities are limited to -powers of two. P-value is derived from sampling probability, which -equals `2**-p`, thus p-value is encoded using an unsigned integer. - -For example, a p-value of 3 indicates a sampling probability of 1/8. - -Since the W3C trace context does not specify that any of the 128 bits -in a TraceID are true uniform-distributed random bits, the r-value is -introduced as an additional source of randomness. - -The recommended method of generating an "r-value" is to count the -number of leading 0s in a string of 62 random bits, however, it is not -required to use this approach. - -### Definitions - -#### Sampling - -Sampling is a family of techniques for collecting and analyzing only a -fraction of a complete data set. Individual items that are "sampled" -are taken to represent one or more spans when collected and counted. -The representivity of each span is used in a Span-to-Metrics pipeline -to accurately count spans. - -Sampling terminology uses "population" to refer to the complete set of -data being sampled from. In OpenTelemetry tracing, "population" -refers to all spans. - -In probability sampling, the representivity of individual sample items -is generally known, whereas OpenTelemetry also recognizes -"non-probability" sampling approaches, in which representivity is not -explicitly quantified. - -#### Adjusted count - -Adjusted count is a measure of representivity, the number of spans in -the population that are represented by the individually sampled span. -Span-to-metrics pipelines can be built by adding the adjusted count of -each sample span to a counter of matching spans. - -For probability sampling, adjusted count is defined as the reciprocal -(i.e., mathematical inverse) of sampling probability. - -For non-probability sampling, adjusted count is unknown. - -Zero adjusted count is defined in a way that supports composition of -probability and non-probability sampling. Zero is assigned as the -adjusted count when a probability sampler does not select a span. - -Thus, there are three meaningfully distinct categories of adjusted count: - -| Adjusted count is | Interpretation | -| -- | -- | -| _Unknown_ | The adjusted count is not known, possibly as a result of a non-probability sampler. Items in this category should not be counted. | -| _Zero_ | The adjusted count is known; the effective count of the item is zero. | -| _Non-zero_ | The adjusted count is known; the effective count of the item is greater than zero. | - -#### Sampler - -A Sampler provides configurable logic, used by the SDK, for selecting -which Spans are "recorded" and/or "sampled" in a tracing client -library. To "record" a span means to build a representation of it in -the client's memory, which makes it eligible for being exported. To -"sample" a span implies setting the W3C `sampled` flag, recording the -span, and exporting the span when it is finished. - -OpenTelemetry supports spans that are "recorded" and not "sampled" -for in-process observability of live spans (e.g., z-pages). - -The Sampler interface and the built-in Samplers defined by -OpenTelemetry decide immediately whether to sample a span, and the -child context immediately propagates the decision. - -#### Parent-based sampler - -A Sampler that makes its decision to sample based on the W3C `sampled` -flag from the context is said to use parent-based sampling. - -#### Probability sampler - -A probability Sampler is a Sampler that knows immediately, for each -of its decisions, the probability that the span had of being selected. - -Sampling probability is defined as a number less than or equal to 1 -and greater than 0 (i.e., `0 < probability <= 1`). The case of 0 -probability is treated as a special, non-probabilistic case. - -#### Consistent probability sampler - -A consistent probability sampler is a Sampler that supports -independent sampling decisions at each span in a trace while -maintaining that traces will be complete with a certain minimum -probability across the trace. - -Consistent probability sampling requires that for any span in a given -trace, if a Sampler with lesser sampling probability selects the span -for sampling, then the span would also be selected by a Sampler -configured with greater sampling probability. - -#### Trace completeness - -A trace is said to be complete when all of the spans belonging to the -trace are collected. When at least one span is collected but not all -spans are collected, the trace is considered incomplete. - -Trace incompleteness may happen on purpose (e.g., through sampling -configuration), or by accident (e.g., through collection errors). The -OpenTelemetry trace data model supports a _one-way_ test for -incompleteness: for any non-root span, the trace is definitely -incomplete if the span's parent span was not collected. - -Incomplete traces that result from sampling configuration (i.e., on -purpose) are known as partial traces. An important subset of the -partial traces are those which are also complete subtraces. A -complete subtrace is defined at a span when every descendant span is -collected. - -Since the test for an incompleteness is one-way, it is important to -know which sampling configurations may lead to incomplete traces. -Sampling configurations that lead naturally to complete traces and -complete subtraces are [discussed below](#trace-producer-completeness). - -#### Non-probability sampler - -A non-probability sampler is a Sampler that makes its decisions not -based on chance, but instead uses arbitrary logic and internal state. -The adjusted count of spans sampled by a non-probability sampler is -unknown. - -#### Always-on consistent probability sampler - -An always-on sampler is another name for a consistent probability -sampler with probability equal to one. - -#### Always-off sampler - -An always-off Sampler has the effect of disabling a span completely, -effectively excluding it from the population. This is defined as a -non-probability sampler, not a zero-percent probability sampler, -because the spans are effectively unrepresented. - -## Consistent Probability sampling - -The consistent sampling scheme adopted by OpenTelemetry propagates two -values via the context, termed "p-value" and "r-value". - -Both fields are propagated via the OpenTelemetry `tracestate` under -the `ot` vendor tag using the rules for [tracestate -handling](tracestate-handling.md). Both fields are represented as -unsigned decimal integers requiring at most 6 bits of information. - -This sampling scheme selects items from among a fixed set of 63 -distinct probability values. The set of supported probabilities -includes the integer powers of two between 1 and 2**-62. Zero -probability and probabilities smaller than 2**-62 are treated as a -special case of "ConsistentAlwaysOff" sampler, just as unit -probability (i.e., 100%) describes a special case of -"ConsistentAlwaysOn" sampler. - -R-value encodes which among the 63 possibilities will consistently -decide to sample for a given trace. Specifically, r-value specifies -the smallest probability that will decide to sample a given trace in -terms of the corresponding p-value. For example, a trace with r-value -0 will sample spans configured for 100% sampling, while r-value 1 will -sample spans configured for 50% or 100% sampling, and so on through -r-value 62, for which a consistent probability sampler will decide -"yes" at every supported probability (i.e., greater than or equal to -2**-62). - -P-value encodes the adjusted count for child contexts (i.e., consumers -of `tracestate`) and consumers of sampled spans to record for use in -Span-to-metrics pipelines. A special p-value of 63 is defined to mean -zero adjusted count, which helps define composition rules for -non-probability samplers. - -An invariant will be stated that connects the `sampled` trace flag -found in `traceparent` context to the r-value and p-value found in -`tracestate` context. - -### Conformance - -Consumers of OpenTelemetry `tracestate` data are expected to validate -the probability sampling fields before interpreting the data. This -applies to the two samplers specified here as well as consumers of -span data, who are expected to validate `tracestate` before -interpreting span adjusted counts. - -Producers of OpenTelemetry `tracestate` containing p-value and r-value -fields are required to meet the behavioral requirements stated for the -`ConsistentProbabilityBased` sampler and to ensure statistically valid -outcomes. A test suite is included in this specification so that -users and consumers of OpenTelemetry `tracestate` can be assured of -accuracy in Span-to-metrics pipelines. - -### Completeness guarantee - -This specification defines consistent sampling for power-of-two -sampling probabilities. When a sampler is configured with a -non-power-of-two sampling probability, the sampler will -probabilistically choose between the nearest powers of two. - -When a single consistent probability sampler is used at the root of a -trace and all other spans use a parent-based sampler, the resulting -traces are always complete (ignoring collection errors). This -property holds even for non-power-of-two sampling probabilities. - -When multiple consistent probability samplers are used in the same -trace, in general, trace completeness is ensured at the smallest power -of two greater than or equal to the minimum sampling probability -across the trace. - -### Context invariants - -The W3C `traceparent` (version 0) contains three fields of -information: the TraceId, the SpanId, and the trace flags. The -`sampled` trace flag has been defined by W3C to signal an intent to -sample the context. - -The [Sampler API](sdk.md#sampler) is responsible for setting the -`sampled` flag and the `tracestate`. - -P-value and r-value are set in the OpenTelemetry `tracestate`, under -the vendor tag `ot`, using the identifiers `p` and `r`. P-value is an -unsigned integer valid in the inclusive range `[0, 63]` (i.e., there -are 64 valid values). R-value is an unsigned integer valid in the -inclusive range `[0, 62]` (i.e., there are 63 valid values). P-value -and r-value are independent settings, each can be meaningfully set -without the other present. - -#### Sampled flag - -Probability sampling uses additional information to enable consistent -decision making and to record the adjusted count of sampled spans. -When both values are defined and in the specified range, the invariant -between r-value and p-value and the `sampled` trace flag states that -`((p <= r) == sampled) OR (sampled AND (p == 63)) == TRUE`. - -The invariant between `sampled`, `p`, and `r` only applies when both -`p` and `r` are present. When the invariant is violated, the -`sampled` flag takes precedence and `p` is unset from `tracestate` in -order to signal unknown adjusted count. - -##### Requirement: Inconsistent p-values are unset - -Samplers SHOULD unset `p` when the invariant between the `sampled`, -`p`, and `r` values is violated before using the `tracestate` to make -a sampling decision or interpret adjusted count. - -#### P-value - -Zero adjusted count is represented by the special p-value 63, -otherwise the p-value is set to the negative base-2 logarithm of -sampling probability: - -| p-value | Parent Probability | Adjusted count | -| ----- | ----------- | -- | -| 0 | 1 | 1 | -| 1 | 1/2 | 2 | -| 2 | 1/4 | 4 | -| ... | ... | ... | -| N | 2**-N | 2**N | -| ... | ... | ... | -| 61 | 2**-61 | 2**61 | -| 62 | 2**-62 | 2**62 | -| 63 | 0 | 0 | - -##### Requirement: Out-of-range p-values are unset - -Consumers SHOULD unset `p` from the `tracestate` if the unsigned -decimal value is greater than 63 before using the `tracestate` to make -a sampling decision or interpret adjusted count. - -#### R-value - -R-value is set in the `tracestate` by the Sampler at the root of the -trace, in order to support consistent probability sampling. When the -value is omitted or not present, child spans in the trace are not able -to participate in consistent probability sampling. - -R-value determines which sampling probabilities will decide to sample -or not decide to sample for spans of a given trace, as follows: - -| r-value | Implied sampling probabilities | -| ---------------- | ---------------------- | -| 0 | 1 | -| 1 | 1/2 and above | -| 2 | 1/4 and above | -| 3 | 1/8 and above | -| ... | ... | -| 0 <= r <= 61 | 2**-r and above | -| ... | ... | -| 59 | 2**-59 and above | -| 60 | 2**-60 and above | -| 61 | 2**-61 and above | -| 62 | 2**-62 and above | - -These probabilities are specified to ensure that conforming Sampler -implementations record spans with correct adjusted counts. The -recommended method of generating r-values is to count the number of -leading 0s in a string of 62 random bits, however it is not required -to use this approach. - -##### Requirement: Out-of-range r-values unset both p and r - -Samplers SHOULD unset both `r` and `p` from the `tracestate` if the -unsigned decimal value of `r` is greater than 62 before using the -`tracestate` to make a sampling decision. - -##### Requirement: R-value is generated with the correct probabilities - -Samplers MUST generate r-values using a randomized scheme that -produces each value with the probabilities equivalent to those -produced by counting the number of leading 0s in a string of 62 random -bits. - -#### Examples: Context invariants - -##### Example: Probability sampled context - -Consider a trace context with the following headers: - -``` -traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 -tracestate: ot=r:3;p:2 -``` - -The `traceparent` contents in this example example are repeated from -the [W3C specification](https://www.w3.org/TR/trace-context/#examples-of-http-traceparent-headers)) -and have the following base64-encoded field values: - -``` -base16(version) = 00 -base16(trace-id) = 4bf92f3577b34da6a3ce929d0e0e4736 -base16(parent-id) = 00f067aa0ba902b7 -base16(trace-flags) = 01 // (i.e., sampled) -``` - -The `tracestate` header contains OpenTelemetry string `r:3;p:2`, -containing decimal-encoded p-value and r-value: - -``` -base10(r) = 3 -base10(p) = 2 -``` - -Here, r-value 3 indicates that a consistent probability sampler -configured with probability 12.5% (i.e., 1-in-8) or greater will -sample the trace. The p-value 2 indicates that the parent that set -the `sampled` flag was configured to sample at 25% (i.e., 1-in-4). -This trace context is consistent because `p <= r` is true and the -`sampled` flag is set. - -##### Example: Probability unsampled - -This example has an unsampled context where only the r-value is set. - -``` -traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-00 -tracestate: ot=r:3 -``` - -This supports consistent probability sampling in child contexts by -virtue of having an r-value. P-value is not set, consistent with an -unsampled context. - -### Samplers - -#### ParentConsistentProbabilityBased sampler - -The `ParentConsistentProbabilityBased` sampler is meant as an optional -replacement for the [`ParentBased` Sampler](sdk.md#parentbased). It is -required to first validate the `tracestate` and then respect the -`sampled` flag in the W3C traceparent. - -##### Requirement: ParentConsistentProbabilityBased API - -The `ParentConsistentProbabilityBased` Sampler constructor SHOULD take -a single Sampler argument, which is the Sampler to use in case the -`ParentConsistentProbabilityBased` Sampler is called for a root span. - -##### Requirement: ParentConsistentProbabilityBased does not modify valid tracestate - -The `ParentConsistentProbabilityBased` Sampler MUST NOT modify a -valid `tracestate`. - -##### Requirement: ParentConsistentProbabilityBased calls the configured root sampler for root spans - -The `ParentConsistentProbabilityBased` Sampler MUST delegate to the -configured root Sampler when there is not a valid parent trace context. - -##### Requirement: ParentConsistentProbabilityBased respects the sampled flag for non-root spans - -The `ParentConsistentProbabilityBased` Sampler MUST decide to sample -the span according to the value of the `sampled` flag in the W3C -traceparent header. - -#### ConsistentProbabilityBased sampler - -The `ConsistentProbabilityBased` sampler is meant as an optional -replacement for the [`TraceIdRatioBased` -Sampler](sdk.md#traceidratiobased). In the case where it is used as a -root sampler, the `ConsistentProbabilityBased` sampler is required to -produce a valid `tracestate`. In the case where it is used in a -non-root context, it is required to validate the incoming `tracestate` -and to produce a valid `tracestate` for the outgoing context. - -The `ConsistentProbabilityBased` sampler is required to support -probabilities that are not exact powers of two. To do so, -implementations are required to select between the nearest powers of -two probabilistically. For example, 5% sampling can be achieved by -selecting 1/16 sampling 60% of the time and 1/32 sampling 40% of the -time. - -##### Requirement: TraceIdRatioBased API compatibility - -The `ConsistentProbabilityBased` Sampler MUST have the same -constructor signature as the built-in `TraceIdRatioBased` sampler in -each OpenTelemetry SDK. - -##### Requirement: ConsistentProbabilityBased sampler sets r for root span - -The `ConsistentProbabilityBased` Sampler MUST set `r` when it makes a -root sampling decision. - -##### Requirement: ConsistentProbabilityBased sampler unsets p when not sampled - -The `ConsistentProbabilityBased` Sampler MUST unset `p` from the -`tracestate` when it decides not to sample. - -##### Requirement: ConsistentProbabilityBased sampler sets p when sampled - -The `ConsistentProbabilityBased` Sampler MUST set `p` when it decides -to sample according to its configured sampling probability. - -##### Requirement: ConsistentProbabilityBased sampler records unbiased adjusted counts - -The `ConsistentProbabilityBased` Sampler with non-zero probability -MUST set `p` so that the adjusted count interpreted from the -`tracestate` is an unbiased estimate of the number of representative -spans in the population. - -##### Requirement: ConsistentProbabilityBased sampler sets r for non-root span - -If `r` is not set on the input `tracecontext` and the Span is not a -root span, `ConsistentProbabilityBased` SHOULD set `r` as if it were a -root span and warn the user that a potentially inconsistent trace -is being produced. - -##### Requirement: ConsistentProbabilityBased sampler decides not to sample for probabilities less than 2**-62 - -If the configured sampling probability is in the interval `[0, -2**-62)`, the Sampler MUST decide not to sample. - -#### Examples: Consistent probability samplers - -##### Example: Setting R-value for a root span - -A new root span is sampled by a consistent probability sampler at 25%. -A new r-value should be generated (see the appendix for suitable -methods), in this example r-value 5 is used which happens 1.5625% of -the time and indicates to sample: - -``` -tracestate: ot=r:5;p:2 -``` - -The span would be sampled because p-value 2 is less than or equal to -r-value 5. An example `tracestate` where r-value 1 indicates not to -sample at 25%: - -``` -tracestate: ot=r:1 -``` - -This span would not be sampled because p-value 2 (corresponding with -25% sampling) is greater than r-value 1. - -##### Example: Handling inconsistent P-value - -When either the consistent probability sampler or the parent-based -consistent probability sampler receives a sampled context but -invalid p-value, for example, - -``` -tracestate: ot=r:4;p:73 -``` - -the `tracestate` will have its p-value stripped. The r-value is kept, -and the sampler should act as if the following had been received: - -``` -tracestate: ot=r:4 -``` - -The consistent probability sampler will make its own (consistent) -decision using the r-value that was received. - -The parent-based consistent probability sampler will in this case -follow the `sampled` flag. If the context is sampled, the resulting -span will have an r-value without a p-value, which indicates unknown -adjusted count. - -##### Example: Handling corrupt R-value - -A non-root span receives: - -``` -tracestate: ot=r:100;p:10 -``` - -where the r-value is out of its valid range. The r-value and p-value -are stripped during validation, according to the invariants. In this -case, the sampler will act as though no `tracestate` were received. - -The parent-based consistent probability sampler will sample or not -sample based on the `sampled` flag, in this case. If the context is -sampled, the recorded span will have an r-value without a p-value, -which indicates unknown adjusted count. - -The consistent probability sampler will generate a new r-value and -make a new sampling decision while warning the user of a corrupt and -potentially inconsistent r-value. - -### Composition rules - -When more than one Sampler participates in the decision to sample a -context, their decisions can be combined using composition rules. In -all cases, the combined decision to sample is the logical-OR of the -Samplers' decisions (i.e., sample if at least one of the composite -Samplers decides to sample). - -To combine p-values from two consistent probability Sampler decisions, -the Sampler with the greater probability takes effect. The output -p-value becomes the minimum of the two values for `p`. - -To combine a consistent probability Sampler decision with a -non-probability Sampler decision, p-value 63 is used to signify zero -adjusted count. If the probability Sampler decides to sample, its -p-value takes effect. If the probability Sampler decides not to -sample when the non-probability sample does sample, p-value 63 takes -effect signifying zero adjusted count. - -#### List of requirements - -##### Requirement: Combining multiple sampling decisions using logical `or` - -When multiple samplers are combined using composition, the sampling -decision MUST be to sample if at least one of the combined samplers -decides to sample. - -##### Requirement: Combine multiple consistent probability samplers using the minimum p-value - -When combining Sampler decisions for multiple consistent probability -Samplers and at least one decides to sample, the minimum of the "yes" -decision `p` values MUST be set in the `tracestate`. - -##### Requirement: Unset p when multiple consistent probability samplers decide not to sample - -When combining Sampler decisions for multiple consistent probability -Samplers and none decides to sample, p-value MUST be unset in the -`tracestate`. - -##### Requirement: Use probability sampler p-value when its decision to sample is combined with non-probability samplers - -When combining Sampler decisions for a consistent probability Sampler -and a non-probability Sampler, and the probability Sampler decides to -sample, its p-value MUST be set in the `tracestate` regardless of the -non-probability Sampler decision. - -##### Requirement: Use p-value 63 when a probability sampler decision not to sample is combined with a non-probability sampler decision to sample - -When combining Sampler decisions for a consistent probability Sampler -and a non-probability Sampler, and the probability Sampler decides not -to sample but the non-probability does sample, p-value 63 MUST be set -in the `tracestate`. - -#### Examples: Composition - -##### Example: Probability and non-probability sampler in a root context - -In a new root context, a consistent probability sampler decides not to -set the sampled flag, adds `r:4` indicating that the trace is -consistently sampled at 6.5% (i.e., 1-in-16) and larger probabilities. - -The probability sampler decision is composed with a non-probability -sampler that decides to sample the context. Setting `sampled` when -the probability sampler has not sampled requires setting `p:63`, -indicating zero adjusted count. - -The resulting context: - -``` -traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 -tracestate: ot=r:4;p:63 -``` - -##### Example: Two consistent probability samplers - -Whether a root or non-root, if multiple consistent probability -samplers make a decision to sample a given context, the minimum -p-value is output in the tracestate. - -If a root context, the first of the samplers generates `r:15` and its -own p-value `p:10` (i.e., adjusted count 1024). The second of the two -probability samplers outputs a smaller adjusted count `p:8` (i.e., -adjusted count 256). - -The resulting context takes the smaller p-value: - -``` -traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01 -tracestate: ot=r:15;p:8 -``` - -### Producer and consumer recommendations - -#### Trace producer: completeness - -As stated in the [completeness guarantee](#completeness-guarantee), -traces will be possibly incomplete when configuring multiple -consistent probability samplers in the same trace. One way to avoid -producing incomplete traces is to use parent-based samplers except for -root spans. - -There is a simple test for trace incompleteness, but it is a one-way -test and does not detect when child spans are uncollected. One way to -avoid producing incomplete traces is to avoid configuring -non-power-of-two sampling probabilities for non-root spans, because -completeness is not guaranteed for non-power-of-two sampling -probabilities. - -##### Recommendation: use non-descending power-of-two probabilities - -Complete subtraces will be produced when the sequence of sampling -probabilities from the root of a trace to its leaves consists of -non-descending powers of two. To ensure complete sub-traces are -produced, child samplers SHOULD be configured with a power-of-two -probability greater than or equal to the parent span's sampling -probability. - -#### Trace producer: correctness - -The use of tracestate to convey adjusted count information rests upon -trust between participants in a trace. Users are advised not to use a -Span-to-metrics pipeline when the parent sampling decision's -corresponding adjusted count is untrustworthy. - -The `ConsistentProbabilityBased` and -`ParentConsistentProbabilityBased` samplers can be used as delegates -of another sampler, for conditioning the choice of sampler on span and -other fixed attributes. However, for adjusted counts to be -trustworthy, the choice of non-root sampler cannot be conditioned on -the parent's sampled trace flag or the OpenTelemetry tracestate -r-value and p-value, as these decisions would lead to incorrect -adjusted counts. - -For example, the built-in [`ParentBased` sampler](sdk.md#parentbased) -supports configuring the delegated-to sampler based on whether the parent -context is remote or non-remote, sampled or unsampled. If a -`ParentBased` sampler delegates to a `ConsistentProbabilityBased` -sampler only for unsampled contexts, the resulting Span-to-metrics -pipeline will (probably) overcount spans. - -##### Recommendation: sampler delegation - -For non-root spans, composite samplers SHOULD NOT condition the choice -of delegated-to sampler based on the parent's sampled flag or -OpenTelemetry tracestate. - -#### Trace producer: interoperability with `ParentBased` sampler - -The OpenTelemetry built-in `ParentBased` sampler is interoperable with -the `ConsistentProbabilityBased` sampler, provided that the -delegated-to sampler does not change the decision that determined its -selection. For example, it is safe to configure an alternate -`ParentBased` sampler delegate for unsampled spans, provided the -decision does not change to sampled. - -Because the `ParentBased` sampler honors the sampled trace flag, and -OpenTelemetry SDKs include the tracestate in the `Span` data, which -means a system can be upgraded to probability sampling by just -replacing `TraceIDRatioBased` samplers with conforming -`ConsistentProbabilityBased` samplers everywhere in the trace. - -#### Trace producer: interoperability with `TraceIDRatioBased` sampler - -The [`TraceIDRatioBased` specification](sdk.md#traceidratiobased) -includes a RECOMMENDATION against being used for non-root spans -because it does not specify how to make the sampler decision -consistent across the trace. A `TraceIDRatioBased` sampler at the -root span is interoperable with a `ConsistentParentProbabilityBased` -sampler in terms of completeness, although the resulting spans will -have unknown adjusted count. - -When a `TraceIDRatioBased` sampler is configured for a non-root span, -several cases arise where an incorrect OpenTelemetry tracestate can be -generated. Consider for example a trace with three spans where the -root (R) has a `ConsistentProbabilityBased` sampler, the root's child -(P) has a `TraceIDRatioBased` sampler, and the grand-child (C) has a -`ParentBased` sampler. Because the `TraceIDRatioBased` sampler change -the intermediate sampled flag without updating the OpenTelemetry -tracestate, we have the following cases: - -1. If `TraceIDRatioBased` does not change P's decision, the trace is - complete and all spans' adjusted counts are correct. -2. If `TraceIDRatioBased` changes P's decision from no to yes, the - consumer will observe a (definitely) incomplete trace containing P - and C. Both spans will have invalid OpenTelemetry tracestate, - leading to unknown adjusted count in this case. -3. If `TraceIDRatioBased` changes the sampling decision from yes to - no, the consumer will observe singleton trace with correct adjusted - count. The consumer cannot determine that R has two unsampled - descendants. - -As these cases demonstrate, users can expect incompleteness and -unknown adjusted count when using `TraceIDRatioBased` samplers for -non-root spans, but this goes against the originally specified -warning. - -#### Trace consumer - -Trace consumers are expected to apply the simple one-way test for -incompleteness. When non-root spans are configured with independent -sampling probabilities, traces may be complete in a way that cannot be -detected. Because of the one-way test, consumers wanting to ensure -complete traces are expected to know the minimum sampling probability -across the system. - -Ignoring accidental data loss, a trace will be complete if all its -spans are sampled with consistent probability samplers and the trace's -r-value is larger than the corresponding smallest power of two greater -than or equal to the minimum sampling probability across the trace. - -Due to the `ConsistentProbabilityBased` Sampler requirement about -setting `r` when it is unset for a non-root span, trace consumers are -advised to check traces for r-value consistency. When a single trace -contains more than a single distinct `r` value, it means the trace was -not correctly sampled at the root for probability sampling. While the -adjusted count of each span is correct in this scenario, it may be -impossible to detect complete traces. - -##### Recommendation: Recognize inconsistent r-values - -When a single trace contains spans with `tracestate` values containing -more than one distinct value for `r`, the consumer SHOULD recognize -the trace as inconsistently sampled. - -### Appendix: Statistical test requirements - -This section specifies a test that can be implemented to ensure basic -conformance with the requirement that sampling decisions are unbiased. - -The goal of this test specification is to be simple to implement and -not require advanced statistical skills or libraries to be successful. - -This test is not meant to evaluate the performance of a random number -generator. This test assumes the underlying RNG is of good quality -and checks that the sampler produces the expected proportionality with -a high degree of statistical confidence. - -One of the challenges of this kind of test is that probabilistic tests -are expected to occasionally produce exceptional results. To make -this a strict test for random behavior, we take the following approach: - -- Generate a pre-determined list of 20 random seeds -- Use fixed values for significance level (5%) and trials (20) -- Use a population size of 100,000 spans -- For each trial, simulate the population and compute ChiSquared - test statistic -- Locate the first seed value in the ordered list such that the - Chi-Squared significance test fails exactly once out of 20 trials - -To create this test, perform the above sequence using the seed values -from the predetermined list, in order, until a seed value is found -with exactly one failure. This is expected to happen fairly often and -is required to happen once among the 20 available seeds. After -calculating the index of the first seed with exactly one ChiSquared -failure, record it in the test. For continuous integration testing, -it is only necessary to re-run the test using the predetermined seed -index. - -As specified, the Chi-Squared test has either one or two degrees of -freedom, depending on whether the sampling probability is an exact -power of two or not. - -#### Test procedure: non-powers of two - -In this case there are two degrees of freedom for the Chi-Squared test. -The following table summarizes the test parameters. - -| Test case | Sampling probability | Lower, Upper p-value when sampled | Expectlower | Expectupper | Expectunsampled | -|-----------|----------------------|-----------------------------------|------------------------|------------------------|----------------------------| -| 1 | 0.900000 | 0, 1 | 10000 | 80000 | 10000 | -| 2 | 0.600000 | 0, 1 | 40000 | 20000 | 40000 | -| 3 | 0.330000 | 1, 2 | 17000 | 16000 | 67000 | -| 4 | 0.130000 | 2, 3 | 12000 | 1000 | 87000 | -| 5 | 0.100000 | 3, 4 | 2500 | 7500 | 90000 | -| 6 | 0.050000 | 4, 5 | 1250 | 3750 | 95000 | -| 7 | 0.017000 | 5, 6 | 1425 | 275 | 98300 | -| 8 | 0.010000 | 6, 7 | 562.5 | 437.5 | 99000 | -| 9 | 0.005000 | 7, 8 | 281.25 | 218.75 | 99500 | -| 10 | 0.002900 | 8, 9 | 100.625 | 189.375 | 99710 | -| 11 | 0.001000 | 9, 10 | 95.3125 | 4.6875 | 99900 | -| 12 | 0.000500 | 10, 11 | 47.65625 | 2.34375 | 99950 | - -The formula for computing Chi-Squared in this case is: - -``` -ChiSquared = math.Pow(sampled_lowerP - expect_lowerP, 2) / expect_lowerP + - math.Pow(sampled_upperP - expect_upperP, 2) / expect_upperP + - math.Pow(100000 - sampled_lowerP - sampled_upperP - expect_unsampled, 2) / expect_unsampled -``` - -This should be compared with 0.102587, the value of the Chi-Squared -distribution for two degrees of freedom with significance level 5%. -For each probability in the table above, the test is required to -demonstrate a seed that produces exactly one ChiSquared value less -than 0.102587. - -##### Requirement: Pass 12 non-power-of-two statistical tests - -For the test with 20 trials and 100,000 spans each, the test MUST -demonstrate a random number generator seed such that the ChiSquared -test statistic is below 0.102587 exactly 1 out of 20 times. - -#### Test procedure: exact powers of two - -In this case there is one degree of freedom for the Chi-Squared test. -The following table summarizes the test parameters. - -| Test case | Sampling probability | P-value when sampled | Expectsampled | Expectunsampled | -|-----------|----------------------|----------------------|--------------------------|----------------------------| -| 13 | 0x1p-01 (0.500000) | 1 | 50000 | 50000 | -| 14 | 0x1p-04 (0.062500) | 4 | 6250 | 93750 | -| 15 | 0x1p-07 (0.007812) | 7 | 781.25 | 99218.75 | - -The formula for computing Chi-Squared in this case is: - -``` -ChiSquared = math.Pow(sampled - expect_sampled, 2) / expect_sampled + - math.Pow(100000 - sampled - expect_unsampled, 2) / expect_unsampled -``` - -This should be compared with 0.003932, the value of the Chi-Squared -distribution for one degree of freedom with significance level 5%. -For each probability in the table above, the test is required to -demonstrate a seed that produces exactly one ChiSquared value less -than 0.003932. - -##### Requirement: Pass 3 power-of-two statistical tests - -For the test with 20 trials and 100,000 spans each, the test MUST -demonstrate a random number generator seed such that the ChiSquared -test statistic is below 0.003932 exactly 1 out of 20 times. - -#### Test implementation - -The recommended structure for this test uses a table listing the 15 -probability values, the expected p-values, whether the ChiSquared -statistic has one or two degrees of freedom, and the index into the -predetermined list of seeds. - -``` - for _, test := range []testCase{ - // Non-powers of two - {0.90000, 1, twoDegrees, 3}, - {0.60000, 1, twoDegrees, 2}, - {0.33000, 2, twoDegrees, 2}, - {0.13000, 3, twoDegrees, 1}, - {0.10000, 4, twoDegrees, 0}, - {0.05000, 5, twoDegrees, 0}, - {0.01700, 6, twoDegrees, 2}, - {0.01000, 7, twoDegrees, 2}, - {0.00500, 8, twoDegrees, 2}, - {0.00290, 9, twoDegrees, 4}, - {0.00100, 10, twoDegrees, 6}, - {0.00050, 11, twoDegrees, 0}, - - // Powers of two - {0x1p-1, 1, oneDegree, 0}, - {0x1p-4, 4, oneDegree, 0}, - {0x1p-7, 7, oneDegree, 1}, - } { -``` - -Note that seed indexes in the example above have what appears to be -the correct distribution. The five 0s, two 1s, five 2s, one 3s, and -one 4 demonstrate that it is relatively easy to find examples where -there is exactly one failure. Probability 0.001, with seed index 6 in -this case, is a reminder that outliers exist. Further significance -testing of this distribution is not recommended. - -## Appendix - -### Methods for generating R-values - -The method used for generating r-values is not specified, in order to -leave the implementation freedom to optimize. Typically, when the -TraceId is known to contain at a 62-bit substring of random bits, -R-values can be derived directly from the 62 random bits of TraceId -by: - -1. Count the leading zeros -2. Count the leading ones -3. Count the trailing zeros -4. Count the trailing ones. - -```golang -import ( - "math/rand" - "math/bits" -) - -func nextRValueLeading() int { - x := uint64(rand.Int63()) // 63 least-significant bits are random - y := x << 1 | 0x3 // 62 most-significant bits are random - return bits.LeadingZeros64(y) -} -``` - -If the TraceId contains unknown or insufficient randomness, another -approach is to generate random bits until the first true or false -value. - -``` -func nextRValueGenerated() int { - for r := 0; r < 62; r++ { - if rand.Bool() == true { - return r - } - } - return 62 -} -``` - -Any scheme that produces r-values shown in the following table is -considered conforming. - -| r-value | Probability of r-value | -| ---------------- | ------------------------ | -| 0 | 1/2 | -| 1 | 1/4 | -| 2 | 1/8 | -| 3 | 1/16 | -| ... | ... | -| 0 <= r <= 61 | 2**-(r+1) | -| ... | ... | -| 59 | 2**-60 | -| 60 | 2**-61 | -| 61 | 2**-62 | -| 62 | 2**-62 | +This document is being updated with the specification finalized in [OTEP 235](https://github.com/open-telemetry/oteps/blob/main/text/trace/0235-sampling-threshold-in-trace-state.md), see [this tracking issue](https://github.com/open-telemetry/opentelemetry-specification/issues/1413).