feat: support ThroughputLimit in samplers #1300
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,205 @@ | ||
| package collect | ||
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| import ( | ||
| "context" | ||
| "fmt" | ||
| "math" | ||
| "strconv" | ||
| "strings" | ||
| "sync" | ||
| "time" | ||
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| "github.com/honeycombio/refinery/config" | ||
| "github.com/honeycombio/refinery/internal/peer" | ||
| "github.com/honeycombio/refinery/metrics" | ||
| "github.com/honeycombio/refinery/pubsub" | ||
| "github.com/jonboulle/clockwork" | ||
| ) | ||
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| const emaThroughputTopic = "ema_throughput" | ||
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| // EMAThroughputCalculator encapsulates the logic to calculate a throughput value using an Exponential Moving Average (EMA). | ||
| type EMAThroughputCalculator struct { | ||
| Config config.Config `inject:""` | ||
| Metrics metrics.Metrics `inject:"metrics"` | ||
| Clock clockwork.Clock `inject:""` | ||
| Pubsub pubsub.PubSub `inject:""` | ||
| Peer peer.Peers `inject:""` | ||
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| throughputLimit uint | ||
| weight float64 // Smoothing factor for EMA | ||
| intervalLength time.Duration // Length of the interval | ||
| hostID string | ||
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| mut sync.RWMutex | ||
| throughputs map[string]throughputReport | ||
| clusterEMA uint | ||
| weightedEventTotal float64 // Internal count of events in the current interval | ||
| done chan struct{} | ||
| } | ||
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| // NewEMAThroughputCalculator creates a new instance of EMAThroughputCalculator. | ||
| func (c *EMAThroughputCalculator) Start() error { | ||
| cfg := c.Config.GetThroughputCalculatorConfig() | ||
| c.throughputLimit = uint(cfg.Limit) | ||
| c.done = make(chan struct{}) | ||
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| // if throughput limit is not set, disable the calculator | ||
| if c.throughputLimit == 0 { | ||
| return nil | ||
| } | ||
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| c.intervalLength = time.Duration(cfg.AdjustmentInterval) | ||
| if c.intervalLength == 0 { | ||
| c.intervalLength = 15 * time.Second | ||
| } | ||
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| c.weight = cfg.Weight | ||
| if c.weight == 0 { | ||
| c.weight = 0.5 | ||
| } | ||
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| peerID, err := c.Peer.GetInstanceID() | ||
| if err != nil { | ||
| return err | ||
| } | ||
| c.hostID = peerID | ||
| c.throughputs = make(map[string]throughputReport) | ||
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| c.Metrics.Register("cluster_throughput", "gauge") | ||
| c.Metrics.Register("cluster_ema_throughput", "gauge") | ||
| c.Metrics.Register("individual_throughput", "gauge") | ||
| c.Metrics.Register("ema_throughput_publish_error", "counter") | ||
| // Subscribe to the throughput topic so we can react to throughput | ||
| // changes in the cluster. | ||
| c.Pubsub.Subscribe(context.Background(), emaThroughputTopic, c.onThroughputUpdate) | ||
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| // have a centralized peer metric service that's responsible for publishing and | ||
| // receiving peer metrics | ||
| // it could have a channel that's receiving metrics from different source | ||
| // it then only send a message if the value has changed and it has passed the configured interval for the metric | ||
| // there could be a third case that basically says you have to send it now because we have passed the configured interval and we haven't send a message about this metric since the last interval | ||
| go func() { | ||
| ticker := c.Clock.NewTicker(c.intervalLength) | ||
| defer ticker.Stop() | ||
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| for { | ||
| select { | ||
| case <-c.done: | ||
| return | ||
| case <-ticker.Chan(): | ||
| currentThroughput := c.updateEMA() | ||
| err := c.Pubsub.Publish(context.Background(), emaThroughputTopic, newThroughputMessage(currentThroughput, peerID).String()) | ||
| if err != nil { | ||
| c.Metrics.Count("ema_throughput_publish_error", 1) | ||
| } | ||
| } | ||
| } | ||
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| }() | ||
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| return nil | ||
| } | ||
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| func (c *EMAThroughputCalculator) onThroughputUpdate(ctx context.Context, msg string) { | ||
| throughputMsg, err := unmarshalThroughputMessage(msg) | ||
| if err != nil { | ||
| return | ||
| } | ||
| c.mut.Lock() | ||
| c.throughputs[throughputMsg.peerID] = throughputReport{ | ||
| key: throughputMsg.peerID, | ||
| throughput: throughputMsg.throughput, | ||
| timestamp: c.Clock.Now(), | ||
| } | ||
| c.mut.Unlock() | ||
| } | ||
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| func (c *EMAThroughputCalculator) Stop() { | ||
| close(c.done) | ||
| } | ||
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| // IncrementEventCount increments the internal event count by a specified amount. | ||
| func (c *EMAThroughputCalculator) IncrementEventCount(count float64) { | ||
| c.mut.Lock() | ||
| c.weightedEventTotal += count | ||
| c.mut.Unlock() | ||
| } | ||
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| // updateEMA calculates the current throughput and updates the EMA. | ||
| func (c *EMAThroughputCalculator) updateEMA() uint { | ||
| c.mut.Lock() | ||
| defer c.mut.Unlock() | ||
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| var totalThroughput float64 | ||
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| for _, report := range c.throughputs { | ||
| if c.Clock.Since(report.timestamp) > c.intervalLength*2 { | ||
| delete(c.throughputs, report.key) | ||
| continue | ||
| } | ||
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| totalThroughput += float64(report.throughput) | ||
| } | ||
| c.Metrics.Gauge("cluster_throughput", totalThroughput) | ||
| c.clusterEMA = uint(math.Ceil(c.weight*totalThroughput + (1-c.weight)*float64(c.clusterEMA))) | ||
| c.Metrics.Gauge("cluster_ema_throughput", c.clusterEMA) | ||
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| // calculating throughput for the next interval | ||
| currentThroughput := float64(c.weightedEventTotal) / c.intervalLength.Seconds() | ||
| c.Metrics.Gauge("individual_throughput", currentThroughput) | ||
| c.weightedEventTotal = 0 // Reset the event count for the new interval | ||
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| return uint(currentThroughput) | ||
| } | ||
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| // GetSamplingRateMultiplier calculates and returns a sampling rate multiplier | ||
| // based on the difference between the configured throughput limit and the current throughput. | ||
| func (c *EMAThroughputCalculator) GetSamplingRateMultiplier() float64 { | ||
| if c.throughputLimit == 0 { | ||
| return 1.0 // No limit set, so no adjustment needed | ||
| } | ||
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| c.mut.RLock() | ||
| currentEMA := c.clusterEMA | ||
| c.mut.RUnlock() | ||
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| if currentEMA <= c.throughputLimit { | ||
| return 1.0 // Throughput is within the limit, no adjustment needed | ||
| } | ||
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| return float64(currentEMA) / float64(c.throughputLimit) | ||
| } | ||
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| type throughputReport struct { | ||
|
There was a problem hiding this comment. This code can be refactored to be a shared logic in both stress relief and throughput calculator There was a problem hiding this comment. Yes, they're quite similar. Would it make sense to go even farther, and bundle the updates into the same messages? So the system maintains a map of named values that can be updated internally by each peer, and the peers send the map through pubsub? |
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| key string | ||
| throughput uint | ||
| timestamp time.Time | ||
| } | ||
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| type throughputMessage struct { | ||
| peerID string | ||
| throughput uint | ||
| } | ||
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| func newThroughputMessage(throughput uint, peerID string) *throughputMessage { | ||
| return &throughputMessage{throughput: throughput, peerID: peerID} | ||
| } | ||
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| func (msg *throughputMessage) String() string { | ||
| return msg.peerID + "|" + fmt.Sprint(msg.throughput) | ||
| } | ||
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| func unmarshalThroughputMessage(msg string) (*throughputMessage, error) { | ||
|
There was a problem hiding this comment. This gives me an idea. Instead of taking a string for a message type, Pubsub could take a PubsubMessage, which would maybe just embed encoding.TextMarshaler and encoding.TextUnmarshaler. That would kind of normalize the way we do these pack and unpack things for pubsub. Or we could build a general-purpose PubsubMessage class that has the ability to add named fields. |
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| if len(msg) < 2 { | ||
| return nil, fmt.Errorf("empty message") | ||
| } | ||
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| parts := strings.SplitN(msg, "|", 2) | ||
| throughput, err := strconv.Atoi(parts[1]) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
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| return newThroughputMessage(uint(throughput), parts[0]), nil | ||
| } | ||
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We should only publish if the throughput is different from the previous calculation
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Agreed.