San Francisco
10-11 Apr 2017
10-11 Apr 2017
Flink Forward is the premier conference on Apache Flink®
Watch all Flink Forward SF Videos here- Imperial Ballroom
- Spring
- Osaka
08:00 am
08:00 am - 08:40 am
Registration Start
08:40 am
08:40 am - 09:00 am
Opening & Announcements
Srikanth Satya
Jamie Grier
09:00 am
09:00 am - 09.40 am
Keynote: Stream Processing with Flink at Netflix
Monal Daxini
09:50 am
10:30 am
10:30 am - 11:00 am
Coffee Break
11:00 am
11:00 am - 11:40 am
Flink meet DC/OS – Deploying Flink at Scale
Ecosystem
Technology
Technology
Elizabeth K. Joseph
Ravi Yadav
11:00 am - 11:40 am
StreamING models, how ING adds models at runtime to catch fraudsters
Applications
Erik de Nooij
11:00 am - 11:40 am
Experiences running Flink at Very Large Scale
Applications
Technology
Technology
Stephan Ewen
11:45 am
11:45 am - 12:05 pm
Using Flink and Queryable State to Buffer High Frequency Time Series Data
Applications
Joe Olson
11:45 am - 12:05 pm
Joining the Scurry of Squirrels: Contributing to Apache Flink
Community
Tzu-Li (Gordon) Tai
11:45 am - 12:05 pm
AthenaX : Uber’s streaming processing platform on Flink
Applications
Haohui Mai
Bill Liu
12:10 pm
12:10 pm - 12:50 pm
Queryable State or How to Build a Billing System Without a Database
Applications
Konstantin Knauf
Maximilian Bode
12:10 pm - 12:50 pm
Portable stateful big data processing in Apache Beam
Ecosystem
Kenneth Knowles
12:10 pm - 12:50 pm
Apache Flink: The Latest and Greatest
Technology
Jamie Grier
12:50 pm
12:50 pm - 2:00 pm
Lunch Break
2:00 pm
2:00 pm - 2:40 pm
From Zero to Streaming: Getting to production with Apache Flink
Applications
Cliff Resnick
Seth Wiesman
2:00 pm - 2:40 pm
Redesigning Apache Flink’s Distributed Architecture
Technology
Till Rohrmann
2:00 pm - 2:40 pm
Introducing Flink TensorFlow
Machine Learning
Ecosystem
Ecosystem
Eron Wright
2:45 pm
2:45 pm - 3:05 pm
Experiences with Streaming vs Micro-Batch for Online Learning
Machine Learning
Ecosystem
Ecosystem
Swaminathan Sundararaman
2:45 pm - 3:05 pm
Building a Real-Time Anomaly-Detection System with Flink @ Mux
Applications
Scott Kidder
2:45 pm - 3:05 pm
The Stream Processor as a Database: Building Online Applications directly on Streams
Technology
Ufuk Celebi
3:10 pm
3:10 pm - 3:50 pm
Non-Flink Machine Learning on Flink
Machine Learning
Ecosystem
Ecosystem
Ted Dunning
3:10 pm - 3:50 pm
Improvements for large state and recovery in Flink
Technology
Stefan Richter
3:10 pm - 3:50 pm
Runtime Improvements in Blink for Large Scale Streaming at Alibaba
Applications
Technology
Technology
Feng Wang
Zhijiang Wang
3:50 pm
3:50 pm - 4:20 pm
Coffee Break
4:20 pm
4:20 pm - 5:00 pm
Dynamically Configured Stream Processing using Flink & Kafka
Applications
David Brelloch
Sean Hester
David Hardwick
4:20 pm - 5:00 pm
Blink’s Improvements to Flink SQL & TableAPI
Applications
Technology
Technology
Shaoxuan Wang
Xiaowei Jiang
5:05 pm
5:05 pm - 5:45 pm
Streaming Deep Learning Scenarios with Flink
Applications
Ecosystem
Ecosystem
Dean Wampler
5:05 pm - 5:45 pm
Table & SQL API – unified APIs for batch and stream processing
Technology
Timo Walther
5:05 pm - 5:45 pm
No shard left behind: Dynamic work rebalancing and Autoscaling in Apache Beam
Ecosystem
Malo Deniélou
5:50 pm
5:50 pm - 6:30 pm
Introduction to Online Machine Learning Algorithms
Machine Learning
Ecosystem
Ecosystem
Trevor Grant
5:50 pm - 6:30 pm
Extending Flink’s Streaming APIs
Technology
Konstantinos Kloudas
5:50 pm - 6:30 pm
Pravega: Storage Reimagined for Streaming World
Technology
Srikanth Satya
Tom Kaitchuck
6:30 pm
6:30 pm - 7:10 pm
Closing Keynote: Convergence of real-time analytics and data-driven applications
Applications
Technology
Technology
Stephan Ewen
7:10 pm
7:10 pm - 22:00 pm