Jack McCluskey

A brief dive into improving Beam Python performance, looking at both currently available best practices as well as looking forward to free threaded Python runtimes.

This session focuses on the mechanics of the Beam Python SDK’s type hinting infrastructure and best practices for users, along with a discussion about current limitations and future improvements

This session will provide an overview of how to utilize large language models (LLMs) using Apache Beam’s RunInference framework. The prime example for the talk will be running the Gemma open model on Dataflow, outlining considerations and common pitfalls when writing pipelines with LLMs.

Over the past year, the Beam Go Sdk has rolled out several features to support native streaming DoFns. This talk will dig into those features and discuss how they can be used to build streaming pipelines written entirely in Go. Attendees will come away with an understanding of some of the...