shoney.arickathil
e7cb954884
- target 1: write path (update-through-query re-probe, triple index walk, per-field encode, whole-row WAL update record) — re-measure after 23, then decide - targets 2-4 recorded with owners (DB-RPC by design/24, mutex inbox /31, fsync bound /23) - board pending + comparison README link the register Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
69 lines
3.5 KiB
Markdown
69 lines
3.5 KiB
Markdown
# Performance targets — measured, named, waiting
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A register like [`discarded.md`](discarded.md)/[`learnings.md`](learnings.md):
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optimization candidates that exist because a NUMBER says so, not a
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hunch. Every row cites its measurement (the db-bench campaign,
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`bench/baseline.json`, or the [go-sqlite comparison](../../bench/compare/go-sqlite/README.md))
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and names an owner iteration when one exists. A target leaves this file
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by landing (delta recorded in the baseline) or by being rejected into
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`discarded.md` with its reason.
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## 1. The write path — update-through-query re-probes, insert re-encodes
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**Measured 2026-08-22** (go-sqlite comparison, N=20k, same machine,
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ext4): ram mixed writes 195,465 ops/s vs SQLite's 380,069 (×1.9
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behind); durable mixed writes 2,324 vs 3,257 (×1.4 behind) — while
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writeonce WINS durable seed ×1.4 and reads ×2.6–6.4. The write gap is
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specifically the UPDATE half of the mix.
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Suspected costs, in probable order (attribute before optimizing — the
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C-API microbench the 22 spec reserves exists for exactly this):
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1. **Update-through-query runs a whole query statement per update**:
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probe (now O(1)) + materialize an id `multi` (arena alloc) +
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`DB_GET_FIELD`/`DB_UPDATE_FIELD` builtin round-trips per touched
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field. SQLite's equivalent is one page write inside one statement.
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2. **`wo_row_update_field` walks every index three times** (shadow
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unique check, old-entry removal, new-entry add — three
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`touches`-loops over `t->indexes` per update; see
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`database/src/table.c`).
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3. **Insert encodes per field with a malloc per text/owned value**
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(`db_val_encode`) — visible as ram seed ×1.2 behind SQLite (245k vs
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297k) even though the durable flavor wins.
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4. **A WAL update record re-encodes the whole row**
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(`wo_wal_append_update` writes the row image, not a delta).
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**Owner:** none yet. Sequence note: iteration 23 (io_uring
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group-commit) rewrites the durable write path's syscall story anyway —
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re-measure after 23 lands, then decide whether the RAM-side costs
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(1–3) earn their own slice. Acceptance shape: ram write ops/s closes
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on SQLite's number with reads unharmed; baseline refreshed with the
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delta recorded.
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## 2. Cross-shard DB RPC halves concurrent read throughput
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**Measured 2026-08-22** (db-bench campaign): ram mixread 89,538 ops/s
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single-shard vs 44,918 at default cores; durable 9,211 vs 4,324. The
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DB actor serializes every statement on shard 0 and each op pays an
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envelope + park/unpark round-trip.
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**Owner: by design, priced deliberately** (story 8's settled decision
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1 — rejected alternatives: engine lock, partitioned tables "wait for a
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measured need"). THIS is the measured need's first data point; the
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recorded escalation path is partitioned/replicated read state, only if
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a real workload (iteration 24's chat) hurts. Not actionable before 24.
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## 3. The mutex inbox costs ~6× on cross-shard message rate
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**Measured 2026-08-22**: 16.7M msgs/s same-heap vs 2.85M cross-shard
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(`msgrate`). **Owner: iteration 31** (mailbox/backpressure decisions
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consume this number) and stage-2 deviation 4 (lock-free rings arrive
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only if the mutex is the measured bottleneck — at 2.85M msgs/s it is
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not the limiting factor for any current workload).
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## 4. Durable write throughput is fsync-bound at ~4.5k/s
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**Measured 2026-08-21**: durable seed 4,460 inserts/s vs ram 245k —
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the ~55× gap is one fdatasync per statement (~220µs each).
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**Owner: iteration 23** (io_uring group-commit) — its acceptance is
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literally this number moving while the crash battery stays green.
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