Documentation
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Index ¶
Constants ¶
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Variables ¶
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Functions ¶
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Types ¶
type Config ¶
type Config struct {
InitialGuess time.Duration // The starting performance assumption for a new resolver.
EvictionThreshold time.Duration // How long a key can be unused before being evicted. (e.g., 30 * time.Minute)
CleanupInterval time.Duration // How often the planner checks for stale keys. (e.g., 5 * time.Minute)
}
Config holds configuration for the planner.
type KeyPlan ¶
type KeyPlan struct {
// contains filtered or unexported fields
}
KeyPlan manages the statistics for a single key and makes decisions about its resolvers. This struct is now entirely lock-free, using a sync.Map to manage its stats.
func (*KeyPlan) SelectResolver ¶
SelectResolver implements the Thompson Sampling decision rule.
func (*KeyPlan) UpdateStats ¶
UpdateStats performs the Bayesian update for the given resolver's statistics.
func (*KeyPlan) UpdateStatsOverGuess ¶
UpdateStatsOverGuess is like UpdateStats but only updates if the duration is worse than the initial guess. This can help reduce noise from very fast responses that might not reflect true performance (or cancelled ones)..
type Planner ¶
type Planner struct {
// contains filtered or unexported fields
}
Planner is the top-level entry point for creating and managing plans for different keys. It is safe for concurrent use and includes a background routine to evict old keys.
func New ¶
New creates a new Planner with the specified configuration and starts its cleanup routine.
func NewNoopPlanner ¶
func NewNoopPlanner() *Planner
func (*Planner) GetKeyPlan ¶
GetKeyPlan retrieves the plan for a specific key, creating it if it doesn't exist.
func (*Planner) StopCleanup ¶
func (p *Planner) StopCleanup()
StopCleanup gracefully terminates the background cleanup goroutine.
type ThompsonStats ¶
type ThompsonStats struct {
// contains filtered or unexported fields
}
ThompsonStats holds the parameters for the Normal-gamma distribution, which models our belief about the performance (execution time) of a strategy.
func NewThompsonStats ¶
func NewThompsonStats(initialGuess time.Duration) *ThompsonStats
NewThompsonStats creates a new stats object with a diffuse prior, representing our initial uncertainty about a strategy's performance.
func (*ThompsonStats) Sample ¶
func (ts *ThompsonStats) Sample(r *rand.Rand) float64
Sample draws a random execution time from the learned distribution. This is the core of Thompson Sampling: we sample from our belief and act greedily on that sample.
func (*ThompsonStats) Update ¶
func (ts *ThompsonStats) Update(duration time.Duration)
Update performs a Bayesian update on the distribution's parameters using the new data point (the observed execution duration). It is the responsibility of the caller to enforce synchronization if multiple goroutines may call Update concurrently.
Source Files