Skip to content

chore: Fix flaky range partition test#4072

Merged
lqiu96 merged 6 commits intomainfrom
fix-flaky-range-partition-test
Jan 20, 2026
Merged

chore: Fix flaky range partition test#4072
lqiu96 merged 6 commits intomainfrom
fix-flaky-range-partition-test

Conversation

@lqiu96
Copy link
Member

@lqiu96 lqiu96 commented Jan 20, 2026

Fixes: #4073 and #4074

@lqiu96 lqiu96 requested a review from jinseopkim0 January 20, 2026 19:21
@product-auto-label product-auto-label bot added size: s Pull request size is small. api: bigquery Issues related to the googleapis/java-bigquery API. labels Jan 20, 2026
@gemini-code-assist
Copy link
Contributor

Summary of Changes

Hello @lqiu96, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves a flakiness issue in an integration test for BigQuery range partitioning. The change ensures that the test correctly identifies and validates the properties of the specific table it creates, preventing erroneous passes due to the presence of other similar tables in the test environment. This improves the reliability of the test suite.

Highlights

  • Flaky Test Fix: Addressed a flakiness issue in the testListTablesWithRangePartitioning integration test. The previous implementation could incorrectly pass if another range-partitioned table already existed in the dataset, leading to false positives.
  • Improved Table Identification: Modified the test logic to explicitly identify and assert properties on the specific range-partitioned table created within the test. This is achieved by comparing the TableId of iterated tables with the createdRangePartitioningTable.
  • Refactored Assertion Logic: Removed the found boolean flag and the assertTrue(found) assertion. The test now directly asserts the range partitioning details on the correctly identified table, making the test more robust and accurate.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature Command Description
Code Review /gemini review Performs a code review for the current pull request in its current state.
Pull Request Summary /gemini summary Provides a summary of the current pull request in its current state.
Comment @gemini-code-assist Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help /gemini help Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

  1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution.

Copy link
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

The pull request aims to fix a flaky range partition test. While the refactoring from an Iterator and while loop to a for-each loop improves readability, a critical logical flaw was introduced. The original test explicitly asserted that the created range-partitioned table was found. The current changes remove this explicit assertion, meaning if the table is not found in the listTables result, the test will silently pass without verifying the table's existence or its partitioning properties. This can lead to false positives and hide actual issues, making the test unreliable.

@lqiu96 lqiu96 marked this pull request as ready for review January 20, 2026 20:08
@lqiu96 lqiu96 requested review from a team January 20, 2026 20:08
@product-auto-label product-auto-label bot added size: m Pull request size is medium. and removed size: s Pull request size is small. labels Jan 20, 2026
@lqiu96 lqiu96 added the kokoro:force-run Add this label to force Kokoro to re-run the tests. label Jan 20, 2026
@yoshi-kokoro yoshi-kokoro removed the kokoro:force-run Add this label to force Kokoro to re-run the tests. label Jan 20, 2026
@lqiu96 lqiu96 merged commit bd5835f into main Jan 20, 2026
25 of 26 checks passed
@lqiu96 lqiu96 deleted the fix-flaky-range-partition-test branch January 20, 2026 22:28
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

api: bigquery Issues related to the googleapis/java-bigquery API. size: m Pull request size is medium.

Projects

None yet

Development

Successfully merging this pull request may close these issues.

Flaky ITBigQueryTest.testListTablesWithRangePartitioning test

3 participants