writeonce/docs/stories/databasev2/03-wal-checkpoint.md

track	iteration	was_language_iteration	status	readiness	chain
databasev2	3	32	pending	refine	6

databasev2 3 — WAL checkpoint: disk space reclamation and bounded replay

Moved 2026-08-26 from the language track, where this was iteration 32. Part of Story — databasev2: the database beyond RAM. Content unchanged by the move; its dependencies are restated in that track index.

Format: product/story-iteration-template. Part of Story — one language, one runtime, one database, one binary — the track this iteration was authored in before the 2026-08-26 move.

Inserted 2026-08-21 (stage-3 guarantee refinement found the hole): the WAL is append-only FOREVER — no checkpoint, no truncation exists in the engine or anywhere on the roadmap. Disk grows without bound and replay time grows with history, so restart cost rises with every write the program ever made. RAM reclamation already exists (deleted rows free their slot — 04-db-binding.md: "Ids are never reused; slots are"); this iteration is the DISK half. LAST in the concurrency chain: stage 3 → 22 → 31 → 24 → 23 → 32 — it wants 22's measured replay/restart numbers to justify its policy and must compose with 23's group-commit write path.

Goals

• Disk space is reclaimed. A checkpoint writes the live store as a snapshot and truncates the WAL behind it; deleted rows and overwritten versions stop occupying disk forever.
• Replay is bounded. Startup replays snapshot + WAL tail, not the program's whole write history — restart time becomes a function of store size, not store age.
• Every existing guarantee holds byte-for-byte. Ack-after-durable, replay-whole-or-not-at-all, torn-tail drop, ids never reused — a checkpoint changes where bytes live, never what an ack means. A crash DURING checkpoint recovers from the previous snapshot + full tail: the old WAL is not truncated until the new snapshot is durable.

Acceptance Criteria (draft — the spec refines)

• Given a store with N rows after many writes and deletes, when a checkpoint completes, then disk usage reflects the live rows (plus the WAL tail), and a restart replays snapshot + tail to the byte-identical store.
• Given kill -9 at ANY instant during a checkpoint, when the process restarts, then recovery produces the same consistent store as if the checkpoint had never started — no acknowledged write lost, no partial snapshot ever read.
• Given the iteration-22 restart benchmark re-run after checkpoint lands, when replay time is measured on an aged store, then the bounded-replay improvement is recorded as a before/after delta. The "before" now EXISTS (databasev2 1, 2026-08-27): db-bench's replay leg measures ≈5.5 µs per WAL record, and — the number this iteration is actually about — 1.9× the boot cost for an identical live dataset once the same rows have been updated once each (20 000 rows: 110 ms at 20 000 records, 211 ms at 40 000). Boot cost tracks history, not data, which is exactly what a checkpoint collapses. Metrics: replay.inserts.*, replay.history.*, replay.history_penalty_x.
• Given writes arriving while a checkpoint runs (the DB actor serializes statements; the checkpoint must not stall them beyond the stated budget), when the mixed load completes, then every ack held its durability contract and the tail contains exactly the post-snapshot writes.

Out Of Scope

• MVCC / multi-version reads — the store is update-in-place RAM; "old versions" exist only as WAL history, which is exactly what truncation reclaims.
• Incremental/streaming backup, point-in-time recovery — a snapshot is a recovery artifact here, not a backup product.
• Cross-shard checkpoint coordination — the WAL is owner-shard-only (stage 3's rule); one shard, one checkpoint.
• Compression, dedup, tiering — measure first (22), add only what a number justifies.

Info

Forks the spec must settle:

1. Snapshot format — a row-image dump of the live store (simple, O(live rows)) vs a rewritten-compacted WAL (reuses replay machinery, O(live rows) too but stays in one format). Leaning: row-image dump in the WAL's existing record grammar, so replay needs no second decoder.
2. Trigger policy — size threshold (WAL bytes vs snapshot bytes ratio), boot-time compaction, explicit call, or some mix. Leaning: ratio threshold checked at commit, plus manual trigger for tests; decided against 22's numbers.
3. Write availability during checkpoint — stop-the-world dump (simplest; the DB actor just runs one long "statement") vs fork-and-dump vs incremental copy. Leaning: measure the stop-the-world pause on the 1M-row store first (22); complexity only if the pause breaks a stated budget.
4. Composition with 23 — the snapshot's durability barrier rides the same per-shard ring (WRITE+FSYNC chain, then the truncate); ordering vs in-flight group commits must be stated normatively in 04-db-binding.md's WAL section.

Proposed Solution

Brainstorm → spec → plan after 23 lands (the write path it composes with). Correction (2026-08-27): this said "using 22's aged-store replay numbers as the policy input", but iteration 22 produced no such numbers — it proved restart correctness and never timed it, and bench/baseline.json carried zero replay metrics until databasev2 1 added them. The policy input is the replay leg's ≈5.5 µs/record and its 1.9× history penalty. Extend 04-db-binding.md's WAL section with the snapshot format the way the record grammar is documented today.

Hazard: compaction invalidates every resident: keys offset

Surfaced while refining this iteration and recorded here so it is not rediscovered late. Iteration 2's resident: keys stores a WAL byte offset per row and reads the row back with pread at that offset. Compaction — whichever of the two shapes below wins — rewrites the log and moves every record, so every stored offset becomes wrong. Not stale-but-readable: pointing at an arbitrary byte in a rewritten file, which is a correctness fault, not a performance one.

So the two iterations are coupled and the coupling has to be designed, not discovered: either compaction rebuilds the offset map as it rewrites (it knows both addresses, so this is the cheap direction), or the snapshot persists the map and compaction is forbidden while any resident: keys table is live. The first is almost certainly right, but it means compaction cannot be written as a pure file operation that ignores in-memory table state.