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Add Python sample for restoring multiple deleted BigQuery tables concurrently

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@alihanoz-google arbeitet bereits daran.

Seit 13.10.2026.

  • #14642 von @alihanoz-google — offen

Bewertung

Schwierigkeit
3/5
Geschätzter Aufwand
Ein halber Tag
Anfängerfreundlichkeit
15/100
Issue-Typ
Feature
Klarheit
Klar beschrieben
Aktivitätsstatus
Veraltet
Tech-Stack
gcp, python
Bereich
databases

Rechercherichtung

The work is a Python sample that queries INFORMATION_SCHEMA.TABLE_STORAGE for recently deleted tables, computes time-travel timestamps, and restores them concurrently with a ThreadPoolExecutor. Pull request #14642 is already open against this issue, so review or coordinate on that PR rather than starting a parallel implementation. Done means the sample runs against a test dataset and restores the tables to the destination dataset.

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Beschreibung

priority: p3 samples triage me type: feature request

Is your feature request related to a problem? Please describe.

Yes. Customers often need to restore multiple deleted BigQuery tables at once (e.g., after an accidental bulk deletion or dropping a dataset). Currently, the public documentation only provides examples for restoring a single table at a time, leaving users to figure out how to write their own concurrent restoration logic using time travel decorators and the INFORMATION_SCHEMA.

Describe the solution you'd like.

Add a Python sample script demonstrating how to programmatically query INFORMATION_SCHEMA.TABLE_STORAGE to find all recently deleted tables in a dataset, calculate their time travel timestamps, and restore them concurrently to a new destination dataset using the BigQuery Python client and a ThreadPoolExecutor.

This sample will be surfaced in the public BigQuery documentation via an include tag to help customers perform bulk restorations.

Describe alternatives you've considered.

The alternative is requiring users to manually restore tables one-by-one via the bq CLI or write their own custom bulk-restore scripts from scratch, which is error-prone and tedious for large datasets.

Additional context.

This sample was explicitly requested by the BigQuery tech writing team to be surfaced in the public documentation for recovering deleted tables (Internal tracking: cl/998554059, b/533404964).

I already have the code prepared and will open a Pull Request linking to this issue shortly!

Vorherrschende Sprache
Jupyter Notebook
Sterne
8.1k
Forks
6.7k
Ø Merge
3 T. 11 Std.
Gemergte PRs (30 T.)
12

Entwicklungsumgebung

Erste Schritte

  1. Lesen Sie das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreiben Sie ins Issue, dass Sie es übernehmen — das erspart doppelte Arbeit.
  3. Forken Sie das Repository und arbeiten Sie in einem Branch.
  4. Öffnen Sie einen Pull Request, der die Issue-Nummer nennt.

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