`merge::match_faces` reads every local face's box and model to pair the
other device's faces with ours. It took 54 ms of a steady-state merge on the
reference library (19,000 faces).
A `faces` row is eight kilobytes -- the embedding, the crop, the dense
landmarks -- and `model_id` sits past the embedding, so reading it opened
each row's overflow pages:
SCAN f
SEARCH r USING INTEGER PRIMARY KEY (rowid=?)
`faces_box (image_id, model_id, x, y, w, h)` holds every column the scan
asks for:
SCAN f USING COVERING INDEX faces_box
SEARCH r USING INTEGER PRIMARY KEY (rowid=?)
The local scan went from 38 ms to 8 ms (sqlite3 on a copy, aggregated so
output formatting is not timed), and `match_faces` from 54 ms to 30-37 ms;
what remains is the other device's half. That is read from its snapshot,
which has whatever indexes its build made -- this one will carry
`faces_box` in its uploads -- and whose rows have had their crops stripped.
The bench merges a full copy with crops, so it overstates that half.
Created on first use in `match_faces`, with CREATE INDEX IF NOT EXISTS,
rather than by a migration, for the reason `keywords::ensure_term_index`
gives: a schema version bump makes older builds refuse the snapshot, and an
extra index is invisible to them. The first merge after the upgrade builds
it (about a second, once). Its prefix duplicates `faces_image_model`, which
is left alone; the planner takes either for an (image_id, model_id) probe.
Tables checksum the same after the bench run as after the old build's.
dtourolle
ae0281fedd