tidaldb/tidal/benches/ranking.rs
jx12n d5d1e7d81a feat(m11): observability+ops (m11p8) + perf-sweep wave 2 T2
m11p8 closes G-O + §1.4-3:
- Cluster metrics: breaker state, forwards, self-heal on /metrics; multi-shard sibling render (shard="N")
- Grafana cluster row + 8-rule Prometheus alert group
- Request-id / TraceLayer on both cluster routers; id rides forward hop
- Truthful status: flushed leader applied_events frontier; post-promote ShardId(0) keying fix
- Self-driving heal: tick_self_heal re-arms stuck-peer backlog every ~3s
- WAL PITR: wal.archive_dir, archive-before-delete gap-free
- tidalctl backup/restore with BLAKE3 content-hash verification
- Rolling-upgrade build_version handshake (N/N+1, never rejects) + Woodpecker release gate

perf-sweep wave 2 T2: one-get-per-type pre-pass in ranking executor
- signal_values.rs pre-fetches all signal kinds before scoring loop
- Eliminates per-item repeated DashMap lookups: −18.8% for_you, −31% under writes
- Byte-identical output verified with A/B test harness
2026-06-13 09:17:49 -06:00

189 lines
7.0 KiB
Rust

#![allow(clippy::unwrap_used)]
//! Criterion benchmarks for the ranking profile executor.
//!
//! Measures scoring latency for 200 candidates across different profiles:
//! - `trending`: exercises velocity reads + gate filtering
//! - `hot`: exercises view count reads + age computation
//! - `full_pipeline`: trending with gates (filter + sort + normalize)
use std::time::Duration;
use criterion::{Criterion, black_box, criterion_group, criterion_main};
use tidaldb::{
ranking::{ProfileExecutor, ProfileRegistry, builtins::register_builtins},
schema::{DecaySpec, EntityId, EntityKind, SchemaBuilder, Timestamp, Window},
signals::{NoopWalWriter, SignalLedger},
};
#[allow(clippy::cast_precision_loss)]
fn make_ledger_with_200_items() -> SignalLedger {
let mut builder = SchemaBuilder::new();
for sig in &["view", "share", "like"] {
let _ = builder
.signal(
sig,
EntityKind::Item,
DecaySpec::Exponential {
half_life: Duration::from_secs(7 * 24 * 3600),
},
)
.windows(&[Window::OneHour, Window::SevenDays])
.velocity(true)
.add();
}
let schema = builder.build().unwrap();
let ledger = SignalLedger::new(schema, Box::new(NoopWalWriter));
let base_ns = 1_708_000_000_000_000_000u64;
for i in 0u64..200 {
let entity_id = EntityId::new(i + 1);
let ts = Timestamp::from_nanos(base_ns - i * 3_600_000_000_000);
ledger
.record_signal("view", entity_id, (200 - i) as f64, ts)
.unwrap();
ledger
.record_signal("share", entity_id, (i % 10) as f64, ts)
.unwrap();
ledger
.record_signal("like", entity_id, (i % 5) as f64, ts)
.unwrap();
}
ledger
}
fn bench_score_200_trending(c: &mut Criterion) {
let ledger = make_ledger_with_200_items();
let mut registry = ProfileRegistry::new();
register_builtins(&mut registry).unwrap();
let profile = registry.get("trending").unwrap().clone();
let executor = ProfileExecutor::new(&ledger);
let candidates: Vec<EntityId> = (1..=200).map(EntityId::new).collect();
let now = Timestamp::from_nanos(1_708_000_000_000_000_000u64);
c.bench_function("score_200_trending", |b| {
b.iter(|| executor.score(black_box(&candidates), black_box(&profile), black_box(now)));
});
}
fn bench_score_200_hot(c: &mut Criterion) {
let ledger = make_ledger_with_200_items();
let mut registry = ProfileRegistry::new();
register_builtins(&mut registry).unwrap();
let profile = registry.get("hot").unwrap().clone();
let executor = ProfileExecutor::new(&ledger);
let candidates: Vec<EntityId> = (1..=200).map(EntityId::new).collect();
let now = Timestamp::from_nanos(1_708_000_000_000_000_000u64);
c.bench_function("score_200_hot", |b| {
b.iter(|| executor.score(black_box(&candidates), black_box(&profile), black_box(now)));
});
}
fn bench_score_200_full_pipeline(c: &mut Criterion) {
let ledger = make_ledger_with_200_items();
let mut registry = ProfileRegistry::new();
register_builtins(&mut registry).unwrap();
let profile = registry.get("trending").unwrap().clone();
let executor = ProfileExecutor::new(&ledger);
let candidates: Vec<EntityId> = (1..=200).map(EntityId::new).collect();
let now = Timestamp::from_nanos(1_708_000_000_000_000_000u64);
c.bench_function("score_200_full_pipeline", |b| {
b.iter(|| executor.score(black_box(&candidates), black_box(&profile), black_box(now)));
});
}
// ── T2: signal-value pre-pass (one `entries.get()` per signal type) ──────────
//
// `for_you` reads `view` twice per candidate at *different* aggregations
// (`Sort::Hot` reads `view` Value; a boost reads `view` DecayScore), so the
// pre-pass collapses two `DashMap` gets to one. The win is a shard-lock saved,
// so it is small single-threaded and grows under concurrent signal-write
// contention — hence the `_under_writes` variants. `with_signal_plan(false)`
// scores the same inputs through the direct per-term path for a true A/B.
fn for_you_profile() -> tidaldb::ranking::profile::RankingProfile {
let mut registry = ProfileRegistry::new();
register_builtins(&mut registry).unwrap();
registry.get("for_you").unwrap().clone()
}
fn bench_for_you_plan(c: &mut Criterion) {
let ledger = make_ledger_with_200_items();
let profile = for_you_profile();
let candidates: Vec<EntityId> = (1..=200).map(EntityId::new).collect();
let now = Timestamp::from_nanos(1_708_000_000_000_000_000u64);
for plan in [true, false] {
let executor = ProfileExecutor::new(&ledger).with_signal_plan(plan);
let id = if plan {
"for_you_plan"
} else {
"for_you_no_plan"
};
c.bench_function(id, |b| {
b.iter(|| executor.score(black_box(&candidates), black_box(&profile), black_box(now)));
});
}
}
#[allow(clippy::cast_precision_loss)]
fn bench_for_you_under_writes(c: &mut Criterion) {
use std::sync::{
Arc,
atomic::{AtomicBool, Ordering},
};
let profile = for_you_profile();
let candidates: Vec<EntityId> = (1..=200).map(EntityId::new).collect();
let now = Timestamp::from_nanos(1_708_000_000_000_000_000u64);
let mut group = c.benchmark_group("for_you_under_writes");
group.measurement_time(Duration::from_secs(8));
for plan in [true, false] {
let ledger = Arc::new(make_ledger_with_200_items());
let stop = Arc::new(AtomicBool::new(false));
// Four writers continuously record `view`/`like` signals, contending the
// same shards the scorer reads — the scenario where collapsing gets pays.
let writers: Vec<_> = (0..4u64)
.map(|w| {
let ledger = Arc::clone(&ledger);
let stop = Arc::clone(&stop);
std::thread::spawn(move || {
let mut i = w;
while !stop.load(Ordering::Relaxed) {
let eid = EntityId::new((i % 200) + 1);
let ts = Timestamp::from_nanos(1_708_000_000_000_000_000u64 + i * 1000);
let _ = ledger.record_signal("view", eid, 1.0, ts);
let _ = ledger.record_signal("like", eid, 1.0, ts);
i += 4;
}
})
})
.collect();
let executor = ProfileExecutor::new(&ledger).with_signal_plan(plan);
let id = if plan { "plan" } else { "no_plan" };
group.bench_function(id, |b| {
b.iter(|| executor.score(black_box(&candidates), black_box(&profile), black_box(now)));
});
stop.store(true, Ordering::Relaxed);
for w in writers {
w.join().unwrap();
}
}
group.finish();
}
criterion_group!(
benches,
bench_score_200_trending,
bench_score_200_hot,
bench_score_200_full_pipeline,
bench_for_you_plan,
bench_for_you_under_writes
);
criterion_main!(benches);