Beam Summit 2024 Sessions


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Title Speaker(s) Recording Slides
Project Shield: How we use Beam to defend democracy and free expression, and how we got started!
 Marc Howard
Data Lineage in Beam
 Rohit Sinha
Ordered processing in Apache Beam
 Sergei Lilichenko
Scaling Autonomous Driving with Apache Beam
 Sayat Satybaldiyev & Arwin Tio
Introducing Ordered List States
 Shunping Huang
Transitioning Uber Michelangelo's Batch Prediction from Apache Spark to Ray
 Baojun Liu
A New Local Runner Appears: Deep dive on Prism
 Robert Burke
Avoid HTTP Request Duplicates with SCIO, a custom AsyncHttpParDoFn and State & Timers
 Alberto López Serna
How we Migrated our JSON DB to a Relational DB using Apache Beam / Dataflow
 Lakshmanan Arumugam
Accelerating CDC Data Ingestion with Apache Beam: A Qlik-to-BigQuery Journey
 Bipin Upadhyaya
Implementing a Beam SDK: A Deep Dive into the Swift SDK
 Byron Ellis
Processing Data from a Web API: A step by step guide
 Damon Douglas
How Beam ML Optimizes Serving Large Models
 Danny McCormick
Introduction to Beam YAML
 Jeff Kinard
Throttling Detection and Reactive Worker Downscaling
 Yi Hu
Beam YAML and Protobuf
 Ferran Fernandez & Austin Bennett
Multi-Modal LLM Data Processing with Apache Beam
 Konstantin Buschmeier, Jasper Van den Bossche & Iris Luden
Troubleshooting Python pipelines with process monitoring tools.
 Valentyn Tymofieiev
Breaking the Language Barrier: Easy Cross-Language with Generated Python Wrappers
 Ahmed Abualsaud
Real-Time Fraud Prevention with Apache Beam
 Hai Sadon
The SolaceIO connector: how was it made and why
 Matt Mays
using pub/subIO writeMessageDynamic() function in a Python pipeline to use dynamic topic destination
 Olu Akinlaja
Improving Stability for Running Python SDK with Flink Runner
 Lydian Lee
Using Dead Letter Queues with Beam
 John Casey
Using LLMs with Beam and RunInference
 Reza Rokni
Innovating the Data & AI Platform
 Yasmeen Ahmad
Lessons Learned from MLOps for GenAI at Google Scale
 Prakash Chockalingam
Beam SDKs Don't Have to Look the Same
 Robert Burke
Drools ParDo and SCIO: a goodbye microservices tale
 Alberto López Serna
Troubleshooting Beam/Dataflow ML Pipelines Related Common Issues
 Rajkumar Gupta
At Least Once Streaming vs Exactly Once: Cost saving vs data accuracy
 Ihaffa Murtopo
BeamStack: An open source Framework for running Machine Learning Pipelines with Apache Beam
 Olufunbi Babalola
Reuniting the Two Distant Cousins: Calling a Beam Pipeline from an Airflow Job
 Sadeeq Akintola
A Low Code Structured Approach to Deploying Apache Beam ML Workloads on Kubernetes using BeamStack
 Charles Adetiloye & Nate Salawe
Cost Effective Solutions for Beam pipelines in Dataflow
 Sharan Teja Malyala
Dataflow Streaming: The evolution of real-time data processing
 Tom Stepp
Beam YAML: Advanced topics
 Jeff Kinard
RAG Data Ingestion Using Apache Beam
 Jasper Van den Bossche & Konstantin Buschmeier
Usage Billing with BEAM @ LinkedIn
 Narayanan Venkiteswaran & Jinjing Bi
Realtime Forecasting using Beam
 Ravi Magham
Streaming Processing for RAG Architectures
 Pablo Rodriguez Defino & Namita Sharma
Cost Optimization of Dataflow Pipelines
 Sergei Lilichenko
Workshop: Multiple Input, Multiple output, Multi-Modal Inference: Streaming ML with Dataflow
 Wei Hsia
Dataflow CI/CD
 Surjit Singh
RAG Data Ingestion and Enrichment Pipeline using Redis and OpenSearch Vector Database in Apache Beam
 Ayush Pandey
Beam for Large-Scale, Accelerated ML Inference at Google
 Uday Kalra