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01 WITH weekly AS (
02 SELECT user_id,
03 DATE_TRUNC('week', ts) AS wk
04 FROM events
05 GROUP BY 1, 2
06 )
07 SELECT a.wk, COUNT(*) AS churned
08 FROM weekly a
09 LEFT JOIN weekly b
10 ON ...Real schemas, real execution, real feedback. No multiple choice.
SELECT DISTINCT ON (user_id, event_type) user_id, event_type, ts FROM events_log WHERE ts >= NOW() - INTERVAL '7 days' ORDER BY user_id, event_type, ts DESC; -- [SUCCESS] 12,401 rows · 124 ms
Postgres-native dedup; cleaner than ROW_NUMBER for this case.
Group ts to the nearest second before deduping — otherwise near-duplicates 100ms apart slip through.
Curated paths based on your target stack. Generated from your JD; updated as you progress.
Window functions, recursive CTEs, optimization for BigQuery and Snowflake.
Pandas vectorization, PySpark, async ingestion patterns.
Idempotent pipelines, exactly-once delivery, backfills at scale.
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