Extending the Yahoo! Streaming Benchmark & Winning Twitter Hack-Week with Flink

Please join us for an exciting evening to learn more about Real-Time stream processing with Apache Flink (http://flink.apache.org) from Jamie Grier (https://www.linkedin.com/in/jamiegrier) who is Director of Applications Engineering at data Artisans (http://data-artisans.com).

RSVP Details: You must have your full name as it appears on your ID on your meetup account to pass beyond building security. Guests must join the NYC Apache Flink Meetup.

Sponsor: McKinsey & Company (http://www.mckinsey.com/)

Schedule:

6:00 pm - 6:30 pm : Networking, pizza and drinks

6:30 pm - 6:45 pm: Flink Community Update by Slim Baltagi

6:45 pm – 8:00 pm : Talk by Jamie Grier

Talk description: In this talk Jamie will be delving further into the recent work he’s done with Apache Flink which resulted in the recent blog post published on February 2nd, 2016: “Extending the Yahoo! Streaming Benchmark and Winning Twitter Hack-Week with Apache Flink” (http://data-artisans.com/extending-the-yahoo-streaming-benchmark/)

Jamie will go through some comparisons between Storm (and other systems like it) and Flink both in terms of processing guarantees and performance.

He’ll also talk about some of the new architectural patterns that can be realized via a modern stateful stream processing system like Flink and what kind of advantages these patterns provide.

Bio: Jamie Grier is Director of Applications Engineering at data Artisans where he’s extremely excited to be able to help others realize the potential of Flink in their own projects. His goal is to help others design systems to solve challenging problems in the real world.Jamie has been working in the field of streaming computation for the last decade. This has spanned everything from ultra-high-performance video stream acquisition and processing to social media analytics.

Prior to joining data Artisans, Jamie was at Twitter working on rethinking the real-time analytics stack with the goals of making it much more efficient and also capable of computing accurate results in real-time without relying on the “Lambda Architecture” for correctness.

Jamie is interested in streaming computation and mechanically sympathetic software architectures. He is particularly interested in building systems that are both high performance and highly scalable and his favorite quote is “You can have a second computer once you’ve shown you know how to use the first one”