{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/c01032e2e58b40a19394404b8f78d5a8\" frameborder=\"0\" width=\"1720\" height=\"1290\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1290,"width":1720,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1290,"thumbnail_width":1720,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/c01032e2e58b40a19394404b8f78d5a8-fbb88442e6037d41.gif","duration":166.272,"title":"ClickHouse tuning, live — same query, 1.8 GB → 6 MB scanned (runnable + CI-verified)","description":"A 3-minute runnable proof for the ClickHouse role. Same 50M-row events table in two schemas — naïve vs tuned. Both return the same answer, but the naïve one scans 50M rows / 1.8 GB while the tuned one reads 478K / 6 MB — ~280× less data, from ORDER BY + partitioning + a projection. Runs from one command (Docker only, synthetic data, no credentials), and a GitHub Actions job re-runs the benchmark on every push and fails if the tuning regresses.\n Repo: github.com/boheastill/clickhouse-dwh-tuning-demo3"}