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flink-forward-sf-2017's Introduction

Flink Forward San Francisco 2017 Slides and Videos

In April 2017, Flink Forward came to San Francisco to welcome the Apache Flink community to one day of training and one day of conference.

All the slides have been collected under folder slides, you can download directly. All the videos are available on YouTube Channel.

🔥 is the session which is recommended to see based on my opinion (Jark Wu).

Sessions

  • 🔥Stephan Ewen - Convergence of real-time analytics & data-driven applications: SlideShare and Video
  • Srikanth Satya - Pravega: SlideShare and Video
  • Erik de Nooij - StreamING models, Realtime model deployment of ML capabilites: SlideShare and Video
  • Monal Daxini - Stream Processing with Flink at Netflix: SlideShare and Video
  • Chinmay Soman - Real Time Analytics in the Real World: SlideShare and Video
  • S. Satya & T. Kaitchuck - Pravega: Storage Reimagined for Streaming World: SlideShare and Video
  • James Malone - Make The Cloud Work For You: SlideShare and Video
  • Dean Wampler - Streaming Deep Learning Scenarios with Flink: SlideShare and Video
  • Shaoxuan Wang & Xiaowei Jiang - Blinks Improvements to Flink SQL And TableAPI: SlideShare and Video
  • Hardwick, Hester & Brelloch - Dynamically Configured Stream Processing Using Flink & Kafka: SlideShare and Video
  • Scott Kidder - Building a Real-Time Anomaly-Detection System with Flink @ Mux: SlideShare and Video
  • 🔥Kenneth Knowles - Portable stateful big data processing in Apache Beam: SlideShare and Video
  • Cliff Resnick & Seth Wiesman - From Zero to Streaming: SlideShare and Video
  • Trevor Grant - Introduction to Online Machine Learning Algorithms: SlideShare and Video
  • K. & M. Bode - Queryable State or How to Build a Billing System w/o a Database: SlideShare and Video
  • Liu & Mai - AthenaX: Uber’s streaming processing platform on Flink: SlideShare and Video
  • 🔥Wang & Wang - Runtime Improvements in Blink for Large Scale Streaming at Alibaba: SlideShare and Video
  • Konstantinos Kloudas - Extending Flink’s Streaming APIs: SlideShare and Video
  • Joe Olson - Flink, Queryable State, and High Frequency Time Series Data: SlideShare and Video
  • 🔥Jamie Grier - Apache Flink: The Latest and Greatest: SlideShare and Video
  • Malo Deniélou - No shard left behind: Dynamic Work Rebalancing and other adaptive features in Apache Beam: SlideShare and Video
  • 🔥Stefan Richter - Improvements for large state and recovery in Flink: SlideShare and Video
  • S. Sundararaman - Experiences w/ Streaming vs Micro-Batch for Online Learning: SlideShare and Video
  • 🔥Timo Walther - Table & SQL API– unified APIs for batch & stream processing: SlideShare and Video
  • Eron Wright - Introducing Flink TensorFlow: SlideShare and Video
  • 🔥Ufuk Celebi - The Stream Processor as a Database: SlideShare and Video
  • 🔥Till Rohrmann - Redesigning Flink’s Distributed Architecture: SlideShare and Video
  • 🔥Stephan Ewen - Experiences running Flink at Very Large Scale: SlideShare and Video
  • Tzu-Li (Gordon) Tai - Joining the Scurry of Squirrels: Contributing to Flink: SlideShare and Video
  • E. K. Joseph & R. Yadav - Flink meet DC/OS – Deploying Flink at Scale: SlideShare and Video
  • Ted Dunning - Non-Flink Machine Learning on Flink: SlideShare and Video

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