pingora_limits/rate.rs
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// Copyright 2024 Cloudflare, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! The rate module defines the [Rate] type that helps estimate the occurrence of events over a
//! period of time.
use crate::estimator::Estimator;
use std::hash::Hash;
use std::sync::atomic::{AtomicBool, AtomicU64, Ordering};
use std::time::{Duration, Instant};
/// Input struct to custom functions for calculating rate. Includes the counts
/// from the current interval, previous interval, the configured duration of an
/// interval, and the fraction into the current interval that the sample was
/// taken.
///
/// Ex. If the interval to the Rate instance is `10s`, and the rate calculation
/// is taken at 2 seconds after the start of the current interval, then the
/// fraction of the current interval returned in this struct will be `0.2`
/// meaning 20% of the current interval has elapsed
#[non_exhaustive]
#[derive(Debug, Clone, Copy, PartialEq, PartialOrd)]
pub struct RateComponents {
pub prev_samples: isize,
pub curr_samples: isize,
pub interval: Duration,
pub current_interval_fraction: f64,
}
/// A stable rate estimator that reports the rate of events in the past `interval` time.
/// It returns the average rate between `interval` * 2 and `interval` while collecting the events
/// happening between `interval` and now.
///
/// This estimator ignores events that happen less than once per `interval` time.
pub struct Rate {
// 2 slots so that we use one to collect the current events and the other to report rate
red_slot: Estimator,
blue_slot: Estimator,
red_or_blue: AtomicBool, // true: the current slot is red, otherwise blue
start: Instant,
// Use u64 below instead of Instant because we want atomic operation
reset_interval_ms: u64, // the time interval to reset `current` and move it to `previous`
last_reset_time: AtomicU64, // the timestamp in ms since `start`
interval: Duration,
}
// see inflight module for the meaning for these numbers
const HASHES: usize = 4;
const SLOTS: usize = 1024; // This value can be lower if interval is short (key cardinality is low)
impl Rate {
/// Create a new `Rate` with the given interval.
pub fn new(interval: std::time::Duration) -> Self {
Rate::new_with_estimator_config(interval, HASHES, SLOTS)
}
/// Create a new `Rate` with the given interval and Estimator config with the given amount of hashes and columns (slots).
#[inline]
pub fn new_with_estimator_config(
interval: std::time::Duration,
hashes: usize,
slots: usize,
) -> Self {
Rate {
red_slot: Estimator::new(hashes, slots),
blue_slot: Estimator::new(hashes, slots),
red_or_blue: AtomicBool::new(true),
start: Instant::now(),
reset_interval_ms: interval.as_millis() as u64, // should be small not to overflow
last_reset_time: AtomicU64::new(0),
interval,
}
}
fn current(&self, red_or_blue: bool) -> &Estimator {
if red_or_blue {
&self.red_slot
} else {
&self.blue_slot
}
}
fn previous(&self, red_or_blue: bool) -> &Estimator {
if red_or_blue {
&self.blue_slot
} else {
&self.red_slot
}
}
fn red_or_blue(&self) -> bool {
self.red_or_blue.load(Ordering::SeqCst)
}
/// Return the per second rate estimation.
pub fn rate<T: Hash>(&self, key: &T) -> f64 {
let past_ms = self.maybe_reset();
if past_ms >= self.reset_interval_ms * 2 {
// already missed 2 intervals, no data, just report 0 as a short cut
return 0f64;
}
self.previous(self.red_or_blue()).get(key) as f64 / self.reset_interval_ms as f64 * 1000.0
}
/// Report new events and return number of events seen so far in the current interval.
pub fn observe<T: Hash>(&self, key: &T, events: isize) -> isize {
self.maybe_reset();
self.current(self.red_or_blue()).incr(key, events)
}
// reset if needed, return the time since last reset for other fn to use
fn maybe_reset(&self) -> u64 {
// should be short enough not to overflow
let now = Instant::now().duration_since(self.start).as_millis() as u64;
let last_reset = self.last_reset_time.load(Ordering::SeqCst);
let past_ms = now - last_reset;
if past_ms < self.reset_interval_ms {
// no need to reset
return past_ms;
}
let red_or_blue = self.red_or_blue();
match self.last_reset_time.compare_exchange(
last_reset,
now,
Ordering::SeqCst,
Ordering::Acquire,
) {
Ok(_) => {
// first clear the previous slot
self.previous(red_or_blue).reset();
// then flip the flag to tell others to use the reset slot
self.red_or_blue.store(!red_or_blue, Ordering::SeqCst);
// if current time is beyond 2 intervals, the data stored in the previous slot
// is also stale, we should clear that too
if now - last_reset >= self.reset_interval_ms * 2 {
// Note that this is the previous one now because we just flipped self.red_or_blue
self.current(red_or_blue).reset();
}
}
Err(new) => {
// another thread beats us to it
assert!(new >= now - 1000); // double check that the new timestamp looks right
}
}
past_ms
}
/// Get the current rate as calculated with the given closure. This closure
/// will take an argument containing all the accessible information about
/// the rate from this object and allow the caller to make their own
/// estimation of rate based on:
///
/// 1. The accumulated samples in the current interval (in progress)
/// 2. The accumulated samples in the previous interval (completed)
/// 3. The size of the interval
/// 4. Elapsed fraction of current interval for this sample (0..1)
///
pub fn rate_with<F, T, K>(&self, key: &K, mut rate_calc_fn: F) -> T
where
F: FnMut(RateComponents) -> T,
K: Hash,
{
let past_ms = self.maybe_reset();
let (prev_samples, curr_samples) = if past_ms >= self.reset_interval_ms * 2 {
// already missed 2 intervals, no data, just report 0 as a short cut
(0, 0)
} else if past_ms >= self.reset_interval_ms {
(self.previous(self.red_or_blue()).get(key), 0)
} else {
let (prev_est, curr_est) = if self.red_or_blue() {
(&self.blue_slot, &self.red_slot)
} else {
(&self.red_slot, &self.blue_slot)
};
(prev_est.get(key), curr_est.get(key))
};
rate_calc_fn(RateComponents {
interval: self.interval,
prev_samples,
curr_samples,
current_interval_fraction: (past_ms % self.reset_interval_ms) as f64
/ self.reset_interval_ms as f64,
})
}
}
#[cfg(test)]
mod tests {
use float_cmp::assert_approx_eq;
use super::*;
use std::thread::sleep;
use std::time::Duration;
#[test]
fn test_observe_rate() {
let r = Rate::new(Duration::from_secs(1));
let key = 1;
// second: 0
let observed = r.observe(&key, 3);
assert_eq!(observed, 3);
let observed = r.observe(&key, 2);
assert_eq!(observed, 5);
assert_eq!(r.rate(&key), 0f64); // no estimation yet because the interval has not passed
// second: 1
sleep(Duration::from_secs(1));
let observed = r.observe(&key, 4);
assert_eq!(observed, 4);
assert_eq!(r.rate(&key), 5f64); // 5 rps
// second: 2
sleep(Duration::from_secs(1));
assert_eq!(r.rate(&key), 4f64);
// second: 3
sleep(Duration::from_secs(1));
assert_eq!(r.rate(&key), 0f64); // no event observed in the past 2 seconds
}
/// Assertion that 2 numbers are close within a generous margin. These
/// tests are doing a lot of literal sleeping, so the measured results
/// can't be accurate or consistent. This function does an assert with a
/// generous tolerance
fn assert_eq_ish(left: f64, right: f64) {
assert_approx_eq!(f64, left, right, epsilon = 0.15)
}
#[test]
fn test_observe_rate_custom_90_10() {
let r = Rate::new(Duration::from_secs(1));
let key = 1;
let rate_90_10_fn = |rate_info: RateComponents| {
let prev = rate_info.prev_samples as f64;
let curr = rate_info.curr_samples as f64;
(prev * 0.1 + curr * 0.9) / rate_info.interval.as_secs_f64()
};
// second: 0
let observed = r.observe(&key, 3);
assert_eq!(observed, 3);
let observed = r.observe(&key, 2);
assert_eq!(observed, 5);
assert_eq!(r.rate_with(&key, rate_90_10_fn), 5. * 0.9);
// second: 1
sleep(Duration::from_secs(1));
let observed = r.observe(&key, 4);
assert_eq!(observed, 4);
assert_eq!(r.rate_with(&key, rate_90_10_fn), 5. * 0.1 + 4. * 0.9);
// second: 2
sleep(Duration::from_secs(1));
assert_eq!(r.rate_with(&key, rate_90_10_fn), 4. * 0.1);
// second: 3
sleep(Duration::from_secs(1));
assert_eq!(r.rate_with(&key, rate_90_10_fn), 0f64);
}
// this is the function described in this post
// https://blog.cloudflare.com/counting-things-a-lot-of-different-things/
#[test]
fn test_observe_rate_custom_proportional() {
let r = Rate::new(Duration::from_secs(1));
let key = 1;
let rate_prop_fn = |rate_info: RateComponents| {
let prev = rate_info.prev_samples as f64;
let curr = rate_info.curr_samples as f64;
let interval_secs = rate_info.interval.as_secs_f64();
let interval_fraction = rate_info.current_interval_fraction;
let weighted_count = prev * (1. - interval_fraction) + curr * interval_fraction;
weighted_count / interval_secs
};
// second: 0
let observed = r.observe(&key, 3);
assert_eq!(observed, 3);
let observed = r.observe(&key, 2);
assert_eq!(observed, 5);
assert_eq_ish(r.rate_with(&key, rate_prop_fn), 0.);
// second 0.5
sleep(Duration::from_secs_f64(0.5));
assert_eq_ish(r.rate_with(&key, rate_prop_fn), 5. * 0.5);
// second: 1
sleep(Duration::from_secs_f64(0.5));
let observed = r.observe(&key, 4);
assert_eq!(observed, 4);
assert_eq_ish(r.rate_with(&key, rate_prop_fn), 5.);
// second 1.75
sleep(Duration::from_secs_f64(0.75));
assert_eq_ish(r.rate_with(&key, rate_prop_fn), 5. * 0.25 + 4. * 0.75);
// second: 2
sleep(Duration::from_secs_f64(0.25));
assert_eq_ish(r.rate_with(&key, rate_prop_fn), 4.);
// second: 3
sleep(Duration::from_secs(1));
assert_eq!(r.rate_with(&key, rate_prop_fn), 0f64);
}
}