1 | use crate::runtime::{Config, MetricsBatch, WorkerMetrics}; |
2 | |
3 | use std::time::{Duration, Instant}; |
4 | |
5 | /// Per-worker statistics. This is used for both tuning the scheduler and |
6 | /// reporting runtime-level metrics/stats. |
7 | pub(crate) struct Stats { |
8 | /// The metrics batch used to report runtime-level metrics/stats to the |
9 | /// user. |
10 | batch: MetricsBatch, |
11 | |
12 | /// Instant at which work last resumed (continued after park). |
13 | /// |
14 | /// This duplicates the value stored in `MetricsBatch`. We will unify |
15 | /// `Stats` and `MetricsBatch` when we stabilize metrics. |
16 | processing_scheduled_tasks_started_at: Instant, |
17 | |
18 | /// Number of tasks polled in the batch of scheduled tasks |
19 | tasks_polled_in_batch: usize, |
20 | |
21 | /// Exponentially-weighted moving average of time spent polling scheduled a |
22 | /// task. |
23 | /// |
24 | /// Tracked in nanoseconds, stored as a `f64` since that is what we use with |
25 | /// the EWMA calculations |
26 | task_poll_time_ewma: f64, |
27 | } |
28 | |
29 | /// How to weigh each individual poll time, value is plucked from thin air. |
30 | const TASK_POLL_TIME_EWMA_ALPHA: f64 = 0.1; |
31 | |
32 | /// Ideally, we wouldn't go above this, value is plucked from thin air. |
33 | const TARGET_GLOBAL_QUEUE_INTERVAL: f64 = Duration::from_micros(200).as_nanos() as f64; |
34 | |
35 | /// Max value for the global queue interval. This is 2x the previous default |
36 | const MAX_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL: u32 = 127; |
37 | |
38 | /// This is the previous default |
39 | const TARGET_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL: u32 = 61; |
40 | |
41 | impl Stats { |
42 | pub(crate) fn new(worker_metrics: &WorkerMetrics) -> Stats { |
43 | // Seed the value with what we hope to see. |
44 | let task_poll_time_ewma = |
45 | TARGET_GLOBAL_QUEUE_INTERVAL / TARGET_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL as f64; |
46 | |
47 | Stats { |
48 | batch: MetricsBatch::new(worker_metrics), |
49 | processing_scheduled_tasks_started_at: Instant::now(), |
50 | tasks_polled_in_batch: 0, |
51 | task_poll_time_ewma, |
52 | } |
53 | } |
54 | |
55 | pub(crate) fn tuned_global_queue_interval(&self, config: &Config) -> u32 { |
56 | // If an interval is explicitly set, don't tune. |
57 | if let Some(configured) = config.global_queue_interval { |
58 | return configured; |
59 | } |
60 | |
61 | // As of Rust 1.45, casts from f64 -> u32 are saturating, which is fine here. |
62 | let tasks_per_interval = (TARGET_GLOBAL_QUEUE_INTERVAL / self.task_poll_time_ewma) as u32; |
63 | |
64 | // If we are using self-tuning, we don't want to return less than 2 as that would result in the |
65 | // global queue always getting checked first. |
66 | tasks_per_interval.clamp(2, MAX_TASKS_POLLED_PER_GLOBAL_QUEUE_INTERVAL) |
67 | } |
68 | |
69 | pub(crate) fn submit(&mut self, to: &WorkerMetrics) { |
70 | self.batch.submit(to, self.task_poll_time_ewma as u64); |
71 | } |
72 | |
73 | pub(crate) fn about_to_park(&mut self) { |
74 | self.batch.about_to_park(); |
75 | } |
76 | |
77 | pub(crate) fn unparked(&mut self) { |
78 | self.batch.unparked(); |
79 | } |
80 | |
81 | pub(crate) fn inc_local_schedule_count(&mut self) { |
82 | self.batch.inc_local_schedule_count(); |
83 | } |
84 | |
85 | pub(crate) fn start_processing_scheduled_tasks(&mut self) { |
86 | self.batch.start_processing_scheduled_tasks(); |
87 | |
88 | self.processing_scheduled_tasks_started_at = Instant::now(); |
89 | self.tasks_polled_in_batch = 0; |
90 | } |
91 | |
92 | pub(crate) fn end_processing_scheduled_tasks(&mut self) { |
93 | self.batch.end_processing_scheduled_tasks(); |
94 | |
95 | // Update the EWMA task poll time |
96 | if self.tasks_polled_in_batch > 0 { |
97 | let now = Instant::now(); |
98 | |
99 | // If we "overflow" this conversion, we have bigger problems than |
100 | // slightly off stats. |
101 | let elapsed = (now - self.processing_scheduled_tasks_started_at).as_nanos() as f64; |
102 | let num_polls = self.tasks_polled_in_batch as f64; |
103 | |
104 | // Calculate the mean poll duration for a single task in the batch |
105 | let mean_poll_duration = elapsed / num_polls; |
106 | |
107 | // Compute the alpha weighted by the number of tasks polled this batch. |
108 | let weighted_alpha = 1.0 - (1.0 - TASK_POLL_TIME_EWMA_ALPHA).powf(num_polls); |
109 | |
110 | // Now compute the new weighted average task poll time. |
111 | self.task_poll_time_ewma = weighted_alpha * mean_poll_duration |
112 | + (1.0 - weighted_alpha) * self.task_poll_time_ewma; |
113 | } |
114 | } |
115 | |
116 | pub(crate) fn start_poll(&mut self) { |
117 | self.batch.start_poll(); |
118 | |
119 | self.tasks_polled_in_batch += 1; |
120 | } |
121 | |
122 | pub(crate) fn end_poll(&mut self) { |
123 | self.batch.end_poll(); |
124 | } |
125 | |
126 | pub(crate) fn incr_steal_count(&mut self, by: u16) { |
127 | self.batch.incr_steal_count(by); |
128 | } |
129 | |
130 | pub(crate) fn incr_steal_operations(&mut self) { |
131 | self.batch.incr_steal_operations(); |
132 | } |
133 | |
134 | pub(crate) fn incr_overflow_count(&mut self) { |
135 | self.batch.incr_overflow_count(); |
136 | } |
137 | } |
138 | |