apache/beam

[Feature Request]: Cache the BigQuery table definition instead of calling tables.get() from every worker

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#34,076 opened on Feb 26, 2025

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 (9 comments) (0 reactions) (2 assignees)Java (7,313 stars) (4,097 forks)batch import
P2good first issuenew featurepythonstale

Description

What would you like to happen?

When calling BigQuery's tables.get method, today, we are calling it from every Dataflow worker. This is resulting in customers hitting Quota issues. Please can we cache the Table definition and re-use for all workers instead of calling the method from every worker.

https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/get

https://github.com/apache/beam/blob/9a1e7bf4cd399177e5de7fe28bad741cade452a5/sdks/python/apache_beam/io/gcp/bigquery.py#L902-L903

https://github.com/apache/beam/blob/9a1e7bf4cd399177e5de7fe28bad741cade452a5/sdks/python/apache_beam/io/gcp/bigquery_tools.py#L565

Issue Priority

Priority: 2 (default / most feature requests should be filed as P2)

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Contributor guide

Tech stack
pythongcp
Domain
backenddatacloud
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
blocked
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
PythonBigQuery APICachingApache Beam SDK
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
35
Research direction
Investigate the existing calls to tables.get() in the Python SDK, specifically in bigquery.py (line 902-903) and bigquery tools.py (line 565) as linked in the issue. Determine a caching strategy that avoids calling the API from every worker. Consider using a shared cache across workers or a lazy initialization pattern. Review the 9 comments in the issue for any proposed solutions or maintainer feedback.