Backfill

A backfill is a run of a pipeline over a range of past dates or partitions, rather than the newest data it normally processes. Teams backfill when a bug is fixed and old output needs correcting, when a new column or metric is added and history needs to reflect it, or when a pipeline is deployed for the first time and needs to populate everything before its normal launch date.

Backfills differ from ordinary incremental runs mainly in scale and risk: instead of processing one day of data, a backfill might touch months or years, which can be slow, expensive, and prone to overwhelming downstream systems if run at full speed. Well-designed workflow orchestration tools let an operator trigger a backfill for a specific date range and run each period through the same directed acyclic graph the pipeline normally uses, rather than requiring separate one-off code.

Backfills are only safe to rerun freely when the underlying tasks are idempotent; otherwise a backfill can double-count historical data instead of correcting it. They also interact with data freshness commitments, since a large backfill can compete for the same compute and queue capacity that current-day pipelines need to hit their freshness targets, so backfills are often throttled or scheduled outside peak hours.