fix: state window handle all-null datablock error

[Tony2h]

Description

Please briefly describe the code changes in this pull request.

Checklist

Please check the items in the checklist if applicable.

• Is the user manual updated?
• Are the test cases passed and automated?
• Is there no significant decrease in test coverage?

[gemini-code-assist]

Summary of Changes

Hello @Tony2h, 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 critical issue in the state window aggregation mechanism, specifically addressing errors that occurred when processing data blocks containing entirely null values or when state windows extended across multiple data blocks. The changes involve significant refactoring of the aggregation logic, introducing more robust handling for partial data blocks and nulls, and ensuring that state windows are correctly processed, initialized, and reset. This enhances the reliability and accuracy of state window operations, especially in complex data streaming scenarios.

Highlights

• Refactored State Window Aggregation: The core logic for aggregating data within closed state windows has been extracted into a new helper function, processClosedStateWindow, improving modularity and readability of the code.
• Enhanced State Window Management: A new resetWindowRowsSup function was introduced to ensure proper initialization and resetting of state window tracking structures, which is crucial for correct window boundary detection and aggregation.
• Improved Data Block Handling: The system now robustly handles state windows that span across multiple data blocks. This includes logic for merging partial blocks and carrying over unprocessed rows, ensuring continuity in state window calculations.
• Addressed All-Null Datablock Error: Specific logic has been implemented to correctly manage state windows when the state column contains all-null data blocks, preventing previous errors and ensuring accurate aggregation in such scenarios.
• New Test Cases for Null Handling: New test data (data3-3.csv) and a Python script to generate it (dataMoreThan4096.py) have been added to thoroughly validate the fix, particularly focusing on scenarios with numerous null values in state window columns.

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[Tony2h]

/gemini review

[gemini-code-assist]

Code Review

This pull request addresses an error in state window handling when a datablock is entirely composed of null values. The fix involves a significant refactoring of the state window aggregation logic. Now, it buffers unprocessed parts of a data block and merges them with subsequent blocks, which correctly handles state windows that span across multiple blocks, especially in the presence of nulls. The logic has also been improved by extracting helper functions like processClosedStateWindow, which enhances code clarity and maintainability. My review includes a critical comment to remove a leftover debug print statement and a couple of medium-severity suggestions for code and repository hygiene.

[Tony2h]

/gemini review

[gemini-code-assist]

Code Review

This pull request refactors the state window aggregation logic to correctly handle data blocks that span window boundaries, particularly addressing an issue with all-null data blocks. The changes introduce a mechanism to carry over partially processed data blocks (pUnfinishedBlock) to subsequent processing loops, ensuring that state windows are correctly demarcated and aggregated even when they cross block boundaries.

Key changes include:

• Extracting a processClosedStateWindow function to encapsulate window processing logic, improving code reuse and readability.
• Modifying doStateWindowAggImpl to process slices of a data block, enabling partial processing.
• Updating openStateWindowAggOptr to manage block merging and carry-over of unfinished blocks.
• Adding a resetWindowRowsSup helper function to centralize state reset logic.

The overall approach is sound and addresses the described problem effectively. I have two suggestions: one critical fix to prevent a potential crash with empty data blocks, and one for improving performance and code clarity by moving a redundant check out of a loop.