Optimise PackManager.bulk_query_id using SQL aggregation #2171
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alastair wants to merge 2 commits into
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Optimise PackManager.bulk_query_id using SQL aggregation #2171alastair wants to merge 2 commits into
alastair wants to merge 2 commits into
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The "unpublished sounds" calculation used a cached value of p.sounds.count() total sounds which already counted only public sounds. This meant that unpublished sounds always showed 0 (total public sounds - total public sounds). Instead, compute all (sounds - public sounds), and only show the count to the pack owner.
The old implementation prefetched every public sound of every pack (with license, geotag and tags) and aggregated per-pack data in Python, so its cost scaled with the total number of sounds in the packs. Rewrite it to compute the same data with four bounded queries: 1. Pack queryset annotated with per-pack aggregates (total sound count, ratings, distinct license pairs, geotag existence) 2. Window query selecting the top-3 newest public sounds per pack 3. Grouped SoundTag query for per-pack tag counts 4. SoundSimilarityVector lookup for the selected sounds Warm render of the profile-page "latest packs" section for a user with large packs drops from ~130 ms to ~36 ms, with section HTML verified byte-identical against a production data snapshot.
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Issue(s)
#1387
Description
The old implementation prefetched every public sound of every pack
(with license, geotag and tags) and aggregated per-pack data in Python,
so its cost scaled with the total number of sounds in the packs.
Rewrite it to compute the same data in sql.
Runtime for a user with large packs goes down from ~130 ms to ~36 ms
Deployment steps: