Failure Modes and Edge Cases: What Breaks and How to Handle It

Where Things Go Wrong: Both patterns have distinct failure modes that surface at scale. Understanding these edge cases separates good designs from production disasters. Full Refresh Failures: Job overruns are the most common failure. A pipeline that completes at 2 a.m. when the table is 50 GB starts finishing at 8 a.m. once it hits 2 TB. Executives expecting dashboards at 9 a.m. see stale data. The failure compounds: if Monday's job runs late and overlaps with Tuesday's scheduled start, you get cascading delays. Partial visibility is another trap. If your pipeline truncates the target table early in the job, then takes 4 hours to reload, consumers see an empty or half loaded table during that window. Queries fail or return incomplete results. The fix is atomic table swaps: write to a staging table, validate with row counts and checksums, then swap pointers atomically so consumers see an instant cutover. Full refresh also loses historical snapshots unless you explicitly retain them. If you overwrite the table daily, you cannot easily answer questions like