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use crate::runtime::{Config, MetricsBatch, WorkerMetrics};
use std::time::{Duration, Instant};
/// Per-worker statistics. This is used for both tuning the scheduler and
/// reporting runtime-level metrics/stats.
pub(crate) struct Stats {
/// The metrics batch used to report runtime-level metrics/stats to the
/// user.
batch: MetricsBatch,
/// Instant at which work last resumed (continued after park).
///
/// This duplicates the value stored in `MetricsBatch`. We will unify
/// `Stats` and `MetricsBatch` when we stabilize metrics.
processing_scheduled_tasks_started_at: Instant,
/// Number of tasks polled in the batch of scheduled tasks
tasks_polled_in_batch: usize,
/// Exponentially-weighted moving average of time spent polling scheduled a
/// task.
///
/// Tracked in nanoseconds, stored as a `f64` since that is what we use with
/// the EWMA calculations
task_poll_time_ewma: f64,
}
/// How to weigh each individual poll time, value is plucked from thin air.
const TASK_POLL_TIME_EWMA_ALPHA: f64 = 0.1;
/// Ideally, we wouldn't go above this, value is plucked from thin air.
const TARGET_GLOBAL_QUEUE_INTERVAL: f64 = Duration::from_micros(200).as_nanos() as f64;
/// Max value for the global queue interval. This is 2x the previous default
const MAX_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL: u32 = 127;
/// This is the previous default
const TARGET_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL: u32 = 61;
impl Stats {
pub(crate) fn new(worker_metrics: &WorkerMetrics) -> Stats {
// Seed the value with what we hope to see.
let task_poll_time_ewma =
TARGET_GLOBAL_QUEUE_INTERVAL / TARGET_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL as f64;
Stats {
batch: MetricsBatch::new(worker_metrics),
processing_scheduled_tasks_started_at: Instant::now(),
tasks_polled_in_batch: 0,
task_poll_time_ewma,
}
}
pub(crate) fn tuned_global_queue_interval(&self, config: &Config) -> u32 {
// If an interval is explicitly set, don't tune.
if let Some(configured) = config.global_queue_interval {
return configured;
}
// As of Rust 1.45, casts from f64 -> u32 are saturating, which is fine here.
let tasks_per_interval = (TARGET_GLOBAL_QUEUE_INTERVAL / self.task_poll_time_ewma) as u32;
// If we are using self-tuning, we don't want to return less than 2 as that would result in the
// global queue always getting checked first.
tasks_per_interval.clamp(2, MAX_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL)
}
pub(crate) fn submit(&mut self, to: &WorkerMetrics) {
self.batch.submit(to, self.task_poll_time_ewma as u64);
}
pub(crate) fn about_to_park(&mut self) {
self.batch.about_to_park();
}
pub(crate) fn unparked(&mut self) {
self.batch.unparked();
}
pub(crate) fn inc_local_schedule_count(&mut self) {
self.batch.inc_local_schedule_count();
}
pub(crate) fn start_processing_scheduled_tasks(&mut self) {
self.batch.start_processing_scheduled_tasks();
self.processing_scheduled_tasks_started_at = Instant::now();
self.tasks_polled_in_batch = 0;
}
pub(crate) fn end_processing_scheduled_tasks(&mut self) {
self.batch.end_processing_scheduled_tasks();
// Update the EWMA task poll time
if self.tasks_polled_in_batch > 0 {
let now = Instant::now();
// If we "overflow" this conversion, we have bigger problems than
// slightly off stats.
let elapsed = (now - self.processing_scheduled_tasks_started_at).as_nanos() as f64;
let num_polls = self.tasks_polled_in_batch as f64;
// Calculate the mean poll duration for a single task in the batch
let mean_poll_duration = elapsed / num_polls;
// Compute the alpha weighted by the number of tasks polled this batch.
let weighted_alpha = 1.0 - (1.0 - TASK_POLL_TIME_EWMA_ALPHA).powf(num_polls);
// Now compute the new weighted average task poll time.
self.task_poll_time_ewma = weighted_alpha * mean_poll_duration
+ (1.0 - weighted_alpha) * self.task_poll_time_ewma;
}
}
pub(crate) fn start_poll(&mut self) {
self.batch.start_poll();
self.tasks_polled_in_batch += 1;
}
pub(crate) fn end_poll(&mut self) {
self.batch.end_poll();
}
pub(crate) fn incr_steal_count(&mut self, by: u16) {
self.batch.incr_steal_count(by);
}
pub(crate) fn incr_steal_operations(&mut self) {
self.batch.incr_steal_operations();
}
pub(crate) fn incr_overflow_count(&mut self) {
self.batch.incr_overflow_count();
}
}