OK frames carry the event id, so clients pair replies by id rather
than by arrival order. NIP-01 also treats OK true as "accepted," not
"fsynced." That removes two constraints the plan was carrying:
- no per-connection FIFO requirement on OKs
- no need to delay OKs until after batch fsync
Tier 1 can fan OKs out as soon as the per-row INSERT returns inside
the open transaction, hiding the group-commit fsync entirely from
publisher latency. Tier 2 drops the order-preserving commit log and
just sends OKs straight to outQueue. The pipelined benchmark now
checks one-OK-per-event-id rather than ordering.
Four sketches, queued by impact, each grounded in current code paths
and observed benchmark numbers:
- event-ingestion-batching: SQLite group commit + EVENT pipelining +
off-thread Schnorr verify. Targets 5–10× EPS on a fast SSD.
- live-broadcast-fanout-index: indexed filter matching to replace the
O(N_subs × N_filters) per-event walk in LiveEventStore. Targets
flat fanout p99 up to high subscriber counts.
- connection-scaling: shrink the per-session outQueue footprint
(currently the dominant per-conn cost), tune Ktor CIO group sizes,
reduce JSON parse allocations. Targets 10 000+ concurrent conns.
- negentropy-large-corpus: id-and-time-only snapshot path so NEG-OPEN
on a 5M-event store doesn't materialise full Event objects, plus
bounded-window defaults and concurrent-session caps.
Each plan names the verification benchmark to add. Plans are queued,
not committed work — README orders them by expected impact.
Claude