Apache Flink Meetup @ResearchGate

We’re very excited to announce our first Apache Flink Meetup in 2017. This time we will have talks presented by our host ResearchGate and by data Artisans. Join us for an evening of pizza, beer, and the latest and greatest on Apache Flink®.

http://photos4.meetupstatic.com/photos/event/a/4/9/8/600_457602136.jpeg

Agenda (work in progress):

1. Introduction by ResearchGate

2. Joining Infinity – Windowless Stream Processing with Flink

By Sanjar Akhmedov, ResearchGate (https://www.researchgate.net/)

The extensive set of high-level Flink primitives makes it easy to join windowed streams. However, use cases that don’t have windows can prove to be more complicated, making it necessary to leverage operator state and low-level primitives to manually implement a continuous join. This talk will focus on the anomalies that present themselves when performing streaming joins with infinite windows, and the problems encountered operating topologies that back user-facing data. We will describe the approach taken at ResearchGate to implement and maintain a consistent join result of change data capture streams.

Sanjar Akhmedov is a software engineer at ResearchGate, with a focus on Flink and Hadoop stack. He is interested in distributed data processing, journaling systems and performance optimization.

3. Extending Flink's Streaming APIs

By Kostas Kloudas, data Artisans (http://data-artisans.com/)

As more and more organizations and individual users turn to Apache Flink for their streaming workloads, there is a bigger demand for additional functionality out-of-the-box. On one hand, there is demand for more low-level APIs that allow for more control, while on the other, users ask for more high-level additions that make the common cases easier to express. This talk will present the new concepts added to the Datastream API in Flink-1.2 and for the upcoming Flink-1.3 release that tried to consolidate the aforementioned goals. We will talk, among others, about the ProcessFunction, a new low level stream processing primitive that gives the user full control over how each event is processed and can register and react to timers, changes in the windowing logic that allow for more flexible windowing strategies, side outputs, and new features concerning the Flink connectors.

Kostas Kloudas is a Flink Contributor, currently working with data Artisans to make Apache Flink® the best open-source stream processing engine and your data’s best friend. Before joining data Artisans, Kostas was a postdoctoral researcher at IST in Lisbon and even before that he obtained a PhD in Computer Science from INRIA (France), His main research focus was in cloud storage and distributed processing.