Cherry Pick RateLimiter SDK changes to Beam 2.71 release

[tarun-google]

Cherry Pick RateLimiter SDK changes to Beam 2.71 release

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[gemini-code-assist]

Summary of Changes

Hello @tarun-google, 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 cherry-picks a set of changes related to the RateLimiter SDK into the Beam 2.71 release. The primary goal is to refine the rate limiting mechanism by renaming key methods for clarity, enhancing the EnvoyRateLimiter for distributed environments through serialization support, and integrating this rate limiting capability directly into the ML inference framework. These updates provide more robust control over external service interactions within Beam pipelines.

Highlights

• Rate Limiter Method Renaming: The core rate limiting method has been renamed from throttle() to allow() across the RateLimiter abstract base class and its EnvoyRateLimiter implementation. This change clarifies the method's intent, indicating whether a request is permitted rather than just if it's being throttled.
• EnvoyRateLimiter Serialization Support: Added __getstate__ and __setstate__ methods to the EnvoyRateLimiter class. This enables proper serialization and deserialization of the rate limiter, which is crucial for Beam's distributed processing where objects might need to be pickled and unpickled across workers.
• Integration with ML Inference Handlers: The RemoteModelHandler in apache_beam.ml.inference.base now supports an optional rate_limiter parameter. This allows users to apply a global rate limit to inference requests, ensuring that external ML services are not overwhelmed. A new RateLimitExceeded exception has also been introduced.
• New Vertex AI Rate Limiter Example: A new example file, rate_limiter_vertex_ai.py, has been added. This example demonstrates how to use the EnvoyRateLimiter in conjunction with VertexAIModelHandlerJSON to control the rate of inference requests to a Vertex AI endpoint.
• Updated Test Cases: Existing test cases for the EnvoyRateLimiter have been updated to reflect the throttle() to allow() method rename. Additionally, new test cases have been added to base_test.py to validate the integration of the rate limiter within the RunInference transform and to test scenarios where rate limits are exceeded.

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[Abacn]

Consider add an item under new feature in https://github.com/apache/beam/blob/master/CHANGES.md

[tarun-google]

created #37308 should i cherrypick this too after merging?

[tarun-google]

@damccorm

[damccorm]

Thanks!