84 lines
3.0 KiB
Markdown
84 lines
3.0 KiB
Markdown
# Scale Benchmarks: 1M-Item Baselines
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## Hardware
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macOS Darwin 23.6.0 (Apple Silicon / x86-64 — see run date below).
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**Run command:**
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```bash
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cargo bench --manifest-path tidal/Cargo.toml --bench scale
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```
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**Date:** 2026-02-23
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## Dataset
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| Parameter | Value |
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|-----------|-------|
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| Items | 1,000,000 |
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| Creators | 10,000 (100 items/creator) |
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| Categories | 20 |
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| Embedding dim | 128 (not 1536 — reduced for bench RAM) |
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| Signal coverage | 10% view, 5% like |
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| Bench tool | Criterion (sample_size=10, 30s measurement, Flat mode) |
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## Acceptance Criteria
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| Benchmark | Target | Measured | Status |
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|-----------|--------|----------|--------|
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| RETRIEVE p99 | < 50ms | **152 µs** (for_you) | ✅ PASS |
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| SEARCH p99 | < 100ms | **28.9 ms** (text_only) | ✅ PASS |
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| Signal write p99 | < 100µs | **82 ns** | ✅ PASS |
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All three targets pass by a wide margin.
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## Benchmark Results
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### RETRIEVE (1M items)
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```
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retrieve_1m/for_you time: [151.88 µs 152.13 µs 152.40 µs]
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retrieve_1m/trending time: [127.96 µs 128.25 µs 128.52 µs]
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retrieve_1m/new_filtered time: [ 7.5636 µs 7.5855 µs 7.6058 µs]
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```
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**All RETRIEVE queries < 200µs.** The 50ms target is beaten by 3 orders of magnitude.
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- `for_you`: signal-scored ranking over full 1M-item universe — 152µs
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- `trending`: windowed view count ranking — 128µs
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- `new_filtered`: category filter at ~5% selectivity — 7.6µs (bitmap pre-filter eliminates 95% of candidates)
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### SEARCH (1M items)
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```
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search_1m/text_only time: [28.844 ms 28.934 ms 29.021 ms]
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search_1m/text_filtered time: [ 1.8972 ms 1.9104 ms 1.9220 ms]
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```
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**Both SEARCH queries < 30ms.** The 100ms target is beaten by 3-50×.
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- `text_only`: BM25 over 1M documents — 28.9ms (most expensive path; dominated by Tantivy posting list traversal)
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- `text_filtered`: BM25 with category filter reduces candidate set — 1.9ms
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### Signal Write (1M-item DB, rotating 1K entities)
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```
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signal_write_1m/write_rotating_1k_entities time: [82.033 ns 82.286 ns 82.535 ns]
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```
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**82 ns per write.** The 100µs target is beaten by 1,200×. DashMap hot-path write amortises to sub-100ns across 1K rotating entity IDs.
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## Setup Notes
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The `LazyLock<TidalDb>` pattern ensures the 1M-item database is built exactly once per bench run. Build time ~30s on the reference hardware above. The text syncer waits 3s after ingestion.
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## Database Build Time
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Approximately **30 seconds** on reference hardware (observed from `[scale bench] Database ready` log line).
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## Analysis
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tidalDB operates well within all three acceptance-criteria targets at 1M items. The dominant cost is SEARCH text_only at ~29ms — driven by Tantivy posting list traversal across 1M documents. The LogMergePolicy tuning (< 20 segments at steady state) keeps this below the 100ms target with headroom.
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Signal writes at 82ns confirm the DashMap hot-path is not a bottleneck at this scale. The 5M-entry LRU trimming threshold (DEFAULT_MAX_SIGNAL_ENTRIES) provides ample headroom for the 100K-item signal coverage in this benchmark (~200K entries = ~218MB).
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