[Dataflow Streaming] Activate SourceState Finalizers before submitting workitem to harness threads

[arunpandianp]

Adding a filter for failed items in #38920. Making this change so finalizers from failed items get scheduled even if the work item gets cancelled.

[gemini-code-assist]

Summary of Changes

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This pull request improves the robustness of Dataflow streaming work scheduling by ensuring that finalizers associated with work items are processed immediately upon scheduling. By moving the finalization logic into the scheduling flow, the system guarantees that finalizers for failed items are executed even if the corresponding work item is subsequently cancelled, preventing potential resource leaks or missed cleanup tasks.

Highlights

• Finalizer Lifecycle Management: Refactored the scheduling logic to ensure SourceState finalizers are activated before work items are submitted to harness threads, improving reliability for failed items.
• API Consolidation: Removed the explicit queueAppliedFinalizeIds method in favor of passing appliedFinalizeIds directly into the scheduleWork method, centralizing the finalization trigger.

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[arunpandianp]

R: @scwhittle

[gemini-code-assist]

Code Review

This pull request refactors the handling of applied finalize IDs in the streaming worker. Instead of queueing them separately via queueAppliedFinalizeIds, they are now passed directly to StreamingWorkScheduler.scheduleWork and finalized alongside the work item's source state finalize IDs before work is scheduled. A review comment suggests adding empty checks before calling commitFinalizer.finalizeCommits to avoid unnecessary overhead and potential lock contention on the critical path when there are no finalize IDs.

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[github-actions]

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[gemini-code-assist]

Code Review

This pull request moves the execution of pending OnCommit callbacks (commitFinalizer.finalizeCommits) from the processWork method to the scheduleWork method in StreamingWorkScheduler.java. The reviewer raised a high-severity concern that executing these finalizers synchronously on the scheduling/dispatching thread can block the main dispatching loop, potentially leading to severe performance bottlenecks or thread starvation if the finalizers perform blocking I/O or run arbitrary user code. It is recommended to offload this execution asynchronously or handle it within the work item's lifecycle.

Important

The consumer version of Gemini Code Assist on GitHub is being sunset. Starting June 18, 2026, new organization installations will be blocked, and all code review activity will officially cease on July 17, 2026.
For more details on the timeline and next steps, please review the Help Documentation.