126 lines
3.2 KiB
Rust
126 lines
3.2 KiB
Rust
use std::sync::Arc;
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use portable_atomic::{AtomicF32, Ordering};
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use serde::ser::Serializer;
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use serde::Serialize;
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use tokio::task::JoinHandle;
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use tokio::time::Duration;
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use watermill::quantile::RollingQuantile;
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use watermill::stats::Univariate;
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pub struct RollingQuantileLatency {
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/// Join handle for the latency calculation task.
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pub join_handle: JoinHandle<()>,
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/// Send to update with each request duration.
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latency_tx: flume::Sender<f32>,
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/// rolling quantile latency in seconds. Updated async.
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seconds: Arc<AtomicF32>,
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}
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/// Task to be spawned per-RollingMedianLatency for calculating the value
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struct RollingQuantileLatencyTask {
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/// Receive to update each request duration
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latency_rx: flume::Receiver<f32>,
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/// Current estimate and update time
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seconds: Arc<AtomicF32>,
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/// quantile value.
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quantile: RollingQuantile<f32>,
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}
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impl RollingQuantileLatencyTask {
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fn new(
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latency_rx: flume::Receiver<f32>,
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seconds: Arc<AtomicF32>,
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q: f32,
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window_size: usize,
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) -> Self {
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let quantile = RollingQuantile::new(q, window_size).unwrap();
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Self {
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latency_rx,
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seconds,
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quantile,
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}
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}
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/// Run the loop for updating latency.
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async fn run(mut self) {
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while let Ok(rtt) = self.latency_rx.recv_async().await {
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self.update(rtt);
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}
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}
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/// Update the estimate object atomically.
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fn update(&mut self, rtt: f32) {
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self.quantile.update(rtt);
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self.seconds
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.store(self.quantile.get(), portable_atomic::Ordering::Relaxed);
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}
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}
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impl RollingQuantileLatency {
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#[inline]
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pub fn record(&self, duration: Duration) {
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self.record_secs(duration.as_secs_f32())
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}
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/// if the channel is full (unlikely), entries will be silently dropped
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#[inline]
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pub fn record_secs(&self, secs: f32) {
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// self.latency_tx.send_async(secs).await.unwrap()
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let _ = self.latency_tx.try_send(secs);
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}
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/// Current .
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#[inline]
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pub fn seconds(&self) -> f32 {
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self.seconds.load(portable_atomic::Ordering::Relaxed)
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}
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/// Current median.
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#[inline]
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pub fn latency(&self) -> Duration {
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Duration::from_secs_f32(self.seconds())
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}
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}
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impl RollingQuantileLatency {
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pub async fn spawn(quantile_value: f32, window_size: usize) -> Self {
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// TODO: how should queue size and window size be related?
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let (latency_tx, latency_rx) = flume::bounded(window_size);
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let seconds = Arc::new(AtomicF32::new(0.0));
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let task = RollingQuantileLatencyTask::new(
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latency_rx,
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seconds.clone(),
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quantile_value,
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window_size,
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);
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let join_handle = tokio::spawn(task.run());
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Self {
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join_handle,
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latency_tx,
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seconds,
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}
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}
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#[inline]
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pub async fn spawn_median(window_size: usize) -> Self {
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Self::spawn(0.5, window_size).await
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}
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}
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/// serialize as seconds
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impl Serialize for RollingQuantileLatency {
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fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
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where
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S: Serializer,
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{
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serializer.serialize_f32(self.seconds.load(Ordering::Relaxed))
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}
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}
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