Add batch version of OrderedWindowElements in examples

[shunping]

A sister PR of #36575, but for batch data.

Notice that there is some difference on the arguments between the batch and the streaming versions, which I plan to address in a follow-up PR. The tests will also be consolidated into one.

[gemini-code-assist]

Summary of Changes

Hello @shunping, 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 extends the Apache Beam Python SDK examples by adding a batch version of the OrderedWindowElements PTransform. This new component enables users to process data within defined windows, ensuring elements are ordered by timestamp and providing flexible strategies to handle data gaps. It leverages Beam's state and timer features to generate context for filling empty windows or gaps at the beginning of windows, offering robust control over data continuity in batch pipelines.

Highlights

• New Batch Implementation: Introduces batch.py containing the OrderedWindowElements PTransform, designed for batch processing, complementing an existing streaming version.
• Windowing and Gap Filling Logic: Adds several DoFn classes (FanOutToWindows, FanOutToSlideBoundaries, GenerateContextDoFn, WindowGapFillingDoFn) to manage element assignment to windows, generate context for gaps, and intelligently fill those gaps.
• Configurable Gap Strategies: Implements a WindowGapStrategy enum (with options like IGNORE, DISCARD, FORWARD_FILL) to define how empty windows and gaps at the start of windows are handled.
• Comprehensive Testing: Includes batch_test.py with parameterized unit tests covering various windowing configurations, offsets, slide intervals, and all defined gap-filling strategies to ensure correctness.

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[shunping]

R: @claudevdm @liferoad

[shunping]

/gemini review

[github-actions]

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[gemini-code-assist]

Code Review

This pull request introduces a batch version of the OrderedWindowElements example, which is a great addition. The implementation correctly handles windowing, ordering, and gap-filling for batch data. I've provided a couple of suggestions. One is to simplify a complex piece of logic in GenerateContextDoFn for better readability. The other is to correct the test setup in batch_test.py by removing an erroneous streaming flag. Overall, the changes look good and the tests are comprehensive.