Skip to content

Use time.monotonic() for duration checks in databricks provider#69758

Open
magic-peach wants to merge 1 commit into
apache:mainfrom
magic-peach:fix-duration-timing-monotonic
Open

Use time.monotonic() for duration checks in databricks provider#69758
magic-peach wants to merge 1 commit into
apache:mainfrom
magic-peach:fix-duration-timing-monotonic

Conversation

@magic-peach

Copy link
Copy Markdown

Duration and timeout comparisons should use time.monotonic() instead of time.time() to be immune to system clock adjustments (NTP, DST, etc.). This aligns with the project coding standard documented in AGENTS.md.

Changes:

  • databricks_base.py: Replace time.time() with time.monotonic() in Azure metadata cache TTL checks (both sync and async versions)
  • databricks.py trigger: Replace time.time() with time.monotonic() in the polling loop timeout check
  • mixins.py: Replace time.time() with time.monotonic() in SQL statement execution timeout checks, and fix grammar error in comment ("important steps; if a query takes to log" → "important step; if a query takes too long")

Note: time.time() is correctly retained for token expiry comparisons (lines 337, 378, 640, 1021, 1066) because those compare against wall-clock Unix timestamps received from the Databricks server.


Was generative AI tooling used to co-author this PR?
  • Yes — Claude Code (Opus 4.7)

Generated-by: Claude Code (Opus 4.7) following the guidelines


Drafted-by: Claude Code (Opus 4.7) (no human review before posting)

Duration and timeout comparisons should use time.monotonic() instead
of time.time() to be immune to system clock adjustments (NTP, DST,
etc.). This aligns with the project coding standard documented in
AGENTS.md.

Also fixes a grammar error in a comment: 'important steps; if a
query takes to log' -> 'important step; if a query takes too long'.

Signed-off-by: Akanksha Trehun <akankshatrehun@gmail.com>
@boring-cyborg

boring-cyborg Bot commented Jul 11, 2026

Copy link
Copy Markdown

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

  • Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
  • In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
  • Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
  • Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
  • Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
  • Be sure to read the Airflow Coding style.
  • Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
    Apache Airflow is a community-driven project and together we are making it better 🚀.
    In case of doubts contact the developers at:
    Mailing List: dev@airflow.apache.org
    Slack: https://s.apache.org/airflow-slack

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant