Add test window function to ReadByFormatIntegrationTestBase

[yalimu-g]

Add test window function to ReadByFormatIntegrationTestBase

[gemini-code-assist]

Summary of Changes

Hello @yalimu-g, 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 introduces a new integration test to the BigQuery Spark connector's test suite. The primary goal is to confirm that Spark SQL's window functions, particularly those involving partitionBy, work correctly when processing data sourced from BigQuery. This enhancement helps ensure the robustness and reliability of data transformations performed using the connector.

Highlights

• New Integration Test: An integration test testWindowFunctionPartitionBy has been added to ReadByFormatIntegrationTestBase to validate the correct behavior of Spark SQL window functions when reading data via the BigQuery connector.
• Window Function Validation: The new test specifically verifies the partitionBy clause of a window function, ensuring that row_number() operates as expected across partitioned data.
• Public Dataset Usage: The test utilizes a public BigQuery dataset (bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_20210131) to provide a realistic testing environment for the window function.

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[gemini-code-assist]

Code Review

This pull request adds an integration test for using a window function on a DataFrame read from BigQuery. The implementation is mostly correct, but the window specification can be improved for readability and to ensure the test is deterministic. I've suggested using column names directly in partitionBy and ordering by a specific column instead of a literal to make the test more robust.

[yalimu-g]

/gcbrun

[yalimu-g]

/gcbrun

[yalimu-g]

/gcbrun

[davidrabinowitz]

The readDataFormat is controlled by the dataFormat variable, this method is redundant

[yalimu-g]

Yeah, all the tests called this provided with "ARROW" format. This function is to answer the Issue 's question and prove that the "AVRO" format works with overriding the dataFormat in this case. Please let me know if you think we should remove or refactor.

[davidrabinowitz]

Yes, this should be controlled by Parameterized tests (https://github.com/junit-team/junit4/wiki/parameterized-tests)

[yalimu-g]

Added the parameterized tests in Spark35ReadByFormatIntegrationTest.

[yalimu-g]

/gcbrun

[yalimu-g]

/gcbrun