A corrected calculation or a missed feed may require processing historical records again. That operation can duplicate outputs, overload a source or trigger old notifications unless the team defines exactly what the rerun is allowed to change.
Related service: Custom software development- 01Define the historical scope and purpose.
- 02Preview source availability and affected outputs.
- 03Choose duplicate and replacement rules.
- 04Run with bounded concurrency.
- 05Reconcile before publishing the rebuilt result.
SECTION 01
Choose what replay means for each output
Identify whether the job adds missing records, replaces a period or recalculates every affected record. Define stable identities and how corrections update an existing result. PostgreSQL's conflict-handling documentation illustrates one database mechanism, but a safe rerun also depends on the business key, transaction boundaries and external effects.
Airflow's backfill documentation distinguishes reprocessing policies and concurrency controls. Those concepts are useful even in a simpler scheduled integration. Ask the agency to show the exact interval and processing version before execution. If the original source history is no longer available, explain that limitation rather than promising a faithful reconstruction.
SECTION 02
Illustrative example: correcting a shipment classification
Suppose a report classified a group of shipments using an outdated mapping. The team agrees to rebuild that month's reporting rows with the corrected version. It first writes a comparison result and checks which records change. Existing customer dispatch messages should not be sent again merely because the reporting records are replayed.
A failure halfway through the rebuild must leave a discoverable state. Restarting should complete the same intended result without doubling rows already processed. The team compares source counts, output counts and meaningful totals before publishing. This hypothetical example separates a controlled data repair from replaying the original operational workflow.
SECTION 03
Test interruption and coexistence with live work
Ask for a safe rehearsal with a small period, then interrupt and resume it. Test repeated runs, corrected source records and concurrent live updates. Decide whether live work pauses, writes to a separate version or follows another explicit coordination rule. A backfill should not quietly overwrite newer corrections.
Handoff should identify the operator, workload limits, comparison report and rollback or replacement procedure. Preserve the prior trusted output until the agreed checks pass where the architecture allows it. Start with bounded recovery rather than an unrestricted all-history button. The operational effort is part of the scope because replay is often used when the system is already under pressure.
SECTION 04
Frequently asked questions
Can we simply delete the old period and rerun?
Only with an explicitly approved recovery and dependency plan. Consider live updates, downstream references and what happens if rebuilding fails.
Does an upsert make every replay safe?
No. It addresses a particular database conflict. Business identity, external effects and concurrent changes still need deliberate handling.
What proves a backfill succeeded?
Reconciled records and meaningful totals for the agreed interval, using the intended processing version, with unresolved exceptions reported.
PRIMARY REFERENCES
Sources and further reading
These references cover the standards, platforms, or published prices discussed in the guide. Worked examples and checklists are our editorial guidance.
- Backfill controlsApache Airflow
- Insert conflict handlingPostgreSQL
EDITORIAL METHOD
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