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Not doing this means that if requests are sent batched and the stream fails for some reason related to batching (like duplicated work token) all of the requests are retried at the same time and are likely to rebatch the same way. Adding backoff means the requests will be sent differently.


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R: @arunpandianp

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Summary of Changes

Hello @scwhittle, 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 enhances the robustness of the GrpcGetDataStream in Dataflow Streaming by implementing a more comprehensive backoff strategy for cancelled requests and other retriable exceptions. This change aims to prevent scenarios where batched requests, upon cancellation, would immediately retry and potentially re-encounter the same failure conditions, leading to a cycle of unproductive retries. By introducing a unified backoff mechanism, the system can space out retries, allowing for better recovery and more efficient resource utilization.

Highlights

  • Backoff for Cancellation Exceptions: The GrpcGetDataStream now explicitly applies a backoff strategy when requests are cancelled, preventing immediate, repeated failures of batched requests that might re-batch in the same problematic way.
  • Unified Backoff Logic: The backoff mechanism has been refactored to be applied consistently across all retriable exceptions within the issueRequest method, ensuring a more robust and predictable retry strategy.
  • Reduced Initial Backoff Duration: The initial backoff duration for FluentBackoff has been decreased from 10 milliseconds to 1 millisecond, potentially allowing for quicker initial retries while still benefiting from exponential backoff.
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