Each /weather/tiles request was running the full ScalarFile decode path
(File.read → gunzip → Msgpax.unpack → normalize) for any non-analysis
valid_time, because GridCache deliberately skipped forecast hours to keep
memory low. With 21 simultaneous viewport tiles all hitting the same few
chunk files, each tile took 1.5-3.2s of contended IO + CPU.
On a GridCache miss when a ScalarFile exists, hydrate GridCache from the
file once (deduped via the existing claim_fill primitive) and serve all
subsequent reads from ETS. Bound memory with prune_keep_latest/1 — keep
the 24 most-recently-touched valid_times, which covers a full HRRR run
(analysis + 18 forecasts) plus a few stragglers from the previous run.
In the steady state, the first viewport read for a given forecast hour
takes one full ScalarFile decode (~50-100 ms for 92k cells); every
subsequent tile, point lookup, and viewport read for the same hour
serves from ETS in <1 ms.
Graham McIntire
b67c0e88c0