bvandeusen
60533073ad
The recommendation metrics table was observable but not actionable: raw source strings (album:<uuid> one-offs) drowned the stable surfaces, and manual plays were excluded so skip rates had no control group. - SQL: include NULL-source rows (the baseline) and carry completion_n so family merges can weight avg_completion correctly. - Handler buckets raw sources into stable families (radio:<uuid> → Radio, album:/artist: → direct plays, etc.) grouped by surface intent: go-to / discovery / direct — each band judged against its job, since discovery mixes are expected to skip hotter. Families under 20 plays are flagged low-confidence, not hidden. - Settings card renders the baseline row and per-surface deltas in percentage points vs baseline (worse-than-baseline deltas in danger color), intent hint copy per group, low-data rows dimmed. - Pure-unit test for the bucketing/merge; DB test updated to the new contract (baseline included, radio:<uuid> collapse). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6
25 lines
1.2 KiB
SQL
25 lines
1.2 KiB
SQL
-- Recommendation observability (#796 phase 4). Per-source play outcomes so the
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-- operator can see whether each recommendation surface is landing and tune the
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-- taste weights. Source is stamped on play_events when a play is launched from
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-- a recommendation surface; NULL means the user picked the track manually —
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-- those rows are INCLUDED here as the baseline control group the surfaces are
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-- judged against (milestone #127: delta-vs-baseline is what makes the numbers
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-- actionable). Raw source strings are bucketed into stable surface families in
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-- the Go handler; completion_n is carried so family merges can weight
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-- avg_completion correctly.
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-- name: RecommendationSourceMetricsForUser :many
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-- $1 user_id, $2 window_days. plays/skips are counts; avg_completion is the
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-- mean completion ratio over the completion_n plays that recorded one.
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SELECT
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pe.source,
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count(*)::bigint AS plays,
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count(*) FILTER (WHERE pe.was_skipped)::bigint AS skips,
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count(pe.completion_ratio)::bigint AS completion_n,
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COALESCE(avg(pe.completion_ratio), 0)::float8 AS avg_completion
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FROM play_events pe
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WHERE pe.user_id = $1
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AND pe.started_at > now() - ($2::float8 * INTERVAL '1 day')
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GROUP BY pe.source
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ORDER BY plays DESC;
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