186 lines
6.3 KiB
Markdown
186 lines
6.3 KiB
Markdown
---
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description: flagd fractional custom operation
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---
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# Fractional Operation
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OpenFeature allows clients to pass contextual information which can then be used during a flag evaluation. For example, a client could pass the email address of the user.
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```js
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// Factional evaluation property name used in a targeting rule
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"fractional": [
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// Evaluation context property used to determine the split
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// Note using `cat` and `$flagd.flagKey` is the suggested default to seed your hash value and prevent bucketing collisions
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{
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"cat": [
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{ "var": "$flagd.flagKey" },
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{ "var": "email" }
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]
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},
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// Split definitions contain an array with a variant and relative weights
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[
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// Must match a variant defined in the flag definition
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"red",
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// The probability this variant is selected
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50
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],
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[
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// Must match a variant defined in the flag definition
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"green",
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// The probability this variant is selected
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50
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]
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]
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```
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If not specified, the default weight for a variant is set to `1`, so an alternative to the example above would be the following:
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```js
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// Factional evaluation property name used in a targeting rule
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"fractional": [
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// Evaluation context property used to determine the split
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// Note using `cat` and `$flagd.flagKey` is the suggested default to seed your hash value and prevent bucketing collisions
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{
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"cat": [
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{ "var": "$flagd.flagKey" },
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{ "var": "email" }
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]
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},
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// Split definitions contain an array with a variant and relative weights
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[
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// Must match a variant defined in the flag definition
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"red"
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],
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[
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// Must match a variant defined in the flag definition
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"green"
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]
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]
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```
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See the [headerColor](https://github.com/open-feature/flagd/blob/main/samples/example_flags.flagd.json#L88-#L133) flag.
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The `defaultVariant` is `red`, but it contains a [targeting rule](../flag-definitions.md#targeting-rules), meaning a fractional evaluation occurs for flag evaluation with a `context` object containing `email` and where that `email` value contains `@faas.com`.
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In this case, `25%` of the evaluations will receive `red`, `25%` will receive `blue`, and so on.
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Assignment is deterministic (sticky) based on the expression supplied as the first parameter (`{ "cat": [{ "var": "$flagd.flagKey" }, { "var": "email" }]}`, in this case).
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The value retrieved by this expression is referred to as the "bucketing value" and must be a string.
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Other primitive types can be used by casting the value using `"cat"` operator.
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For example, a less deterministic distribution can be achieved using `{ "cat": [{ "var": "$flagd.timestamp" }]}`.
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The bucketing value expression can be omitted, in which case a concatenation of the `targetingKey` and the `flagKey` will be used.
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The `fractional` operation is a custom JsonLogic operation which deterministically selects a variant based on
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the defined distribution of each variant (as a relative weight).
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This works by hashing ([murmur3](https://github.com/aappleby/smhasher/blob/master/src/MurmurHash3.cpp))
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the given data point, converting it into an int in the range [0, 99].
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Whichever range this int falls in decides which variant
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is selected.
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As hashing is deterministic we can be sure to get the same result every time for the same data point.
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The `fractional` operation can be added as part of a targeting definition.
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The value is an array and the first element is a nested JsonLogic rule which resolves to the hash key.
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This rule should typically consist of a seed concatenated with a session variable to use from the evaluation context.
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This value should typically be something that remains consistent for the duration of a users session (e.g. email or session ID).
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The seed is typically the flagKey so that experiments running across different flags are statistically independent, however, you can also specify another seed to either align or further decouple your allocations across different feature flags or use-cases.
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The other elements in the array are nested arrays with the first element representing a variant and the second being the relative weight for this option.
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There is no limit to the number of elements.
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> [!NOTE]
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> Older versions of the `fractional` operation were percentage based, and required all variants weights to sum to 100.
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## Example
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Flags defined as such:
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```json
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{
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"$schema": "https://flagd.dev/schema/v0/flags.json",
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"flags": {
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"headerColor": {
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"variants": {
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"red": "#FF0000",
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"blue": "#0000FF",
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"green": "#00FF00"
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},
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"defaultVariant": "red",
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"state": "ENABLED",
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"targeting": {
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"fractional": [
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{
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"cat": [
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{ "var": "$flagd.flagKey" },
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{ "var": "email" }
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]
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},
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[
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"red",
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50
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],
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[
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"blue",
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20
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],
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[
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"green",
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30
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]
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]
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}
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}
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}
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}
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```
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will return variant `red` 50% of the time, `blue` 20% of the time & `green` 30% of the time.
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Command:
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```shell
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curl -X POST "localhost:8013/flagd.evaluation.v1.Service/ResolveString" -d '{"flagKey":"headerColor","context":{"email": "foo@bar.com"}}' -H "Content-Type: application/json"
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```
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Result:
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```shell
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{"value":"#0000FF","reason":"TARGETING_MATCH","variant":"blue"}
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```
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Command:
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```shell
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curl -X POST "localhost:8013/flagd.evaluation.v1.Service/ResolveString" -d '{"flagKey":"headerColor","context":{"email": "foo@test.com"}}' -H "Content-Type: application/json"
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```
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Result:
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```json
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{"value":"#00FF00","reason":"TARGETING_MATCH","variant":"green"}
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```
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Notice that rerunning either curl command will always return the same variant and value.
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The only way to get a different value is to change the email or update the `fractional` configuration.
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### Migrating from legacy "fractionalEvaluation"
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If you are using a legacy fractional evaluation (`fractionalEvaluation`), it's recommended you migrate to `fractional`.
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The new `fractional` evaluator supports nested properties and JsonLogic expressions.
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To migrate, simply use a JsonLogic variable declaration for the bucketing property, instead of a string:
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old:
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```json
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"fractionalEvaluation": [
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"email",
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[ "red", 25 ], [ "blue", 25 ], [ "green", 25 ], [ "yellow", 25 ]
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]
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```
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new:
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```json
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"fractional": [
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{ "var": "email" },
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[ "red", 25 ], [ "blue", 25 ], [ "green", 25 ], [ "yellow", 25 ]
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]
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```
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