Bucket each cache entry into 5°×5° spatial chunks matching the layout
used by Weather.GridCache. fetch_bounds/3 now walks only the chunks
intersecting the viewport instead of the full 92k-cell CONUS map; a
typical zoomed viewport hits ~1500 cells per chunk × the chunks the
viewport overlaps instead of scanning all 92k.
Public API and observable behavior unchanged. Add cross-chunk-boundary
regression tests so future refactors can't silently flatten the layout.
ScoreCache held 437 entries × ~1.94 MiB each (~850 MiB per pod) of
{band_mhz, valid_time} grids — data already on NFS as compact .prop
files. NotifyListener and ScoreCacheReconciler both eagerly materialised
every band into ETS on each Rust completion / 60s sweep, so 5 hot
replicas wasted ~4.2 GiB of redundant cache and OOMed at 6 GiB.
Bound the cache to 32 entries with eviction by oldest valid_time, drop
the eager warm loops, and let LiveView callers lazy-fill via the
existing ScoresFile read path. ScoreCacheReconciler had no remaining
purpose and is deleted; runbook + prom_ex counters updated to match.
Steady-state cache footprint ~60 MiB per pod instead of ~850 MiB.
Hot pods were restart-looping every ~25 minutes on liveness probe
timeouts. Root cause: ScoreCacheReconciler mirrored every .prop file
from NFS into ETS, including 7 days of GEFS Day 2-7 forecasts. With
23 bands × 43 valid_times × ~2 MB per grid = 1.95 GB in the
propagation_score_cache table alone; GC sweeps starved the
scheduler enough that /live dropped its 3 s budget.
The /map UI only ever requests the [now-1h, now+18h] window. Share
that bound as Propagation.hot_cache_window/0 and apply it in the
reconciler's disk-scan path plus NotifyListener's post-warm prune.
Long-horizon GEFS files stay on disk and are still served via the
lazy read_from_disk_and_cache path when requested directly.
Adds ScoreCache.prune_outside_window/2 (inclusive bounds) and
updates the reconciler tests to use relative-to-now timestamps
since hardcoded fixture dates now drift out of window.
Two wins in the /map hot path.
1. preload_forecast fired on every Leaflet moveend — which arrives in
bursts during pan/zoom — and each firing read + filtered + shipped
18 forecast-hour score lists (up to 90k cells per hour at full
CONUS view) over the LiveView websocket. Now debounced to the
trailing edge: the user must stop moving for 750 ms before we pay
the preload cost. select_band and propagation_updated go through
the same scheduler so a storm of PubSub updates during an hourly
chain also coalesces.
2. ScoreCache.grid_to_filtered_list walked the 92k-cell grid twice
(Enum.filter then Enum.map) and allocated an intermediate tuple
list between them. Enum.reduce emits only in-bounds result maps
directly — halves map traversal + drops the tuple intermediate.
Telemetry showed the application-master process holding ~830 MiB of
terms from warm_grid_cache_from_latest_profile — the data lives in
the app master's heap and never GCs because the process is idle.
Running it in a Task.start lets the terms die with the task.
Mark GridCache, MrmsCache, NexradCache, and ScoreCache ETS tables
:compressed. The scored-band-map and HRRR grid data are map-heavy;
compression trims hundreds of MiB at a few percent CPU cost.
Memoise HRRR .idx responses in Microwaveprop.Cache. Published idx
files are immutable for a model run, but the hourly chain re-fetches
the same URL dozens of times across forecast hours. Cuts ~10s per
repeat out of hrrr_fetch_idx.
Force a garbage collect at the end of HrrrFetchWorker.perform to
reclaim the refc binary heap held from GRIB2 ranges before the Oban
producer hands the process its next job.
- ScoreCache stores {band, valid_time} as %{{lat, lon} => score} map so
point lookups are O(1); adds fetch_point/4 and valid_times/1
- available_valid_times/1 reads directly from ScoreCache when warm,
falls back to DB on cold start
- point_forecast/3 iterates cached valid_times and uses fetch_point/4
instead of hitting the DB per click
- NexradCache: node-local ETS cache of decoded n0q PNG pixel buffers
keyed by 5-minute rounded timestamp; skips ~1-5s HTTP+decode on
concurrent/repeat clicks within the same window
- MapLive: start_async the rain_scatter fetch so point_detail renders
immediately with a pending marker; push rain_scatter_update when
NEXRAD resolves
- MapLive: preload all 18 remaining forecast hours for the current
viewport after mount/band change/propagation_updated; client caches
them and renders timeline scrubs instantly without a server roundtrip.
Adds set_selected_time event for fast-path state sync.
- Propagation map JS: forecastCache map + drawScatterMarkers helper,
timeline click uses preloaded cache when available
- Add ScoreCache GenServer with node-local ETS table keyed by
{band, valid_time}, subscribed to "propagation:cache" PubSub topic so
every pod stays in sync with a single hourly compute
- scores_at/3 checks cache first, falls back to DB and populates on miss
- PropagationGridWorker warms and broadcasts the cache for each band
after every forecast hour upsert; prunes >2h old entries
- Replace per-pixel string-keyed Map with flat Int8Array over the CONUS
grid in propagation_map_hook.ts to eliminate allocations in the tile
rasterization hot loop (interpolateScore / propagationReach)
