DATA OPS
BigQuery Backfill Missing Partitions After Query Failure
Detects which date partitions a failed scheduled query skipped, runs a bounded backfill for exactly that window, and reports the recovered row counts to Discord.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled query fails on partitioned loadBigQuery
- ActionCompute missing partition date windowBigQuery
- LogicWindow within auto-backfill cap?
- ActionSchedule backfill for missing datesBigQuery
- OutputPost recovered row counts to DiscordDiscord
What it does
When a scheduled query that loads a partitioned table fails, the destination ends up with a gap. This workflow computes the missing date range by comparing expected run dates against partitions actually present, then issues a backfill scoped to only the gap — never a full-table reload — and confirms the recovered partitions.
When to use it
Use it for daily or hourly ingestion queries writing into date-partitioned tables, where a single missed run leaves a hole that downstream dashboards read as zero. It restores continuity without the cost and risk of reprocessing history you already have.
How it works
- 1A BigQuery run-failure event identifies the affected scheduled query and destination table.
- 2An action queries the destination's existing partitions and the transfer config's run history to find the missing date window.
- 3A logic guard caps the window (for example, refuses to backfill more than 14 days automatically) and routes anything larger to manual review.
- 4Within the cap, the workflow schedules a BigQuery backfill run for precisely the missing dates.
- 5After completion it reads recovered row counts per partition and posts a Discord summary table so on-call can confirm the gap is closed.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect DiscordCommunity channels + voice + bots.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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