Vergangenes Meetup

Apache Flink Meetup @ data Artisans

Dieses Meetup liegt in der Vergangenheit

118 Personen haben teilgenommen

Bild des Veranstaltungsortes

Details

data Artisans (http://www.data-artisans.com) is moving to a new office just across the canal! But before we do, we'd like to invite all of the Berlin Squirrels to Tempelhofer Ufer 17 one last time for an evening of pizza, beer, and the latest and greatest on Apache Flink®.

Flink enthusiasts, come hang out with the data Artisans team and the local Flink community and ask dA's software engineers all of your pressing questions about Flink and stream processing.

Agenda (work in progress):

1. Introduction and community update from data Artisans

By Kostas Tzoumas & Robert Metzger, data Artisans

Our CEO Kostas and co-founder Robert will talk about data Artisans and give an update on developments in Flink: new features, users, and the growing community.

Kostas Tzoumas is PMC member of Apache Flink® and co-founder and CEO of data Artisans. Before founding data Artisans, Kostas was a postdoctoral researcher at TU Berlin and received a PhD in Computer Science from Aalborg University.

Robert Metzger is Committer & PMC member member at the Apache Flink project and a co-founder and software engineer at dataArtisans.

2. A look at Apache Flink 1.2

By Stefan Richter, data Artisans

As we are quickly moving towards the end of the year, version 1.2 of Apache Flink is already just around the corner. In this talk we give a full overview of the new release, which brings us
dynamic job rescaling, integration with Apache Mesos, query able state, secure data access, and Kafka 0.10 support.

We also take a closer technical look at some of the most anticipated features. In particular, we will present details on dynamic job rescaling and query able state that were driven by our team at data Artisans.

With dynamic job rescaling, Flink 1.2 can now easily adjust operator parallelism to react to workload changes, while maintaining the fault tolerance guarantees and performance of previous versions.

Queryable state is our first step to blur the boundaries between stream processors and databases with the potential to revolutionize the current state-of-the-art in big data. We present how to blend database functionality with Flink by providing live read-access to operator states in a running streaming pipeline.

This talk concludes with a glimpse on the future roadmap beyond Flink 1.2 and how data Artisans plans to continue pushing the boundaries of stream processing.

Stefan Richter is an Apache Flink® contributor and works as a software engineer at data Artisans. He has a PhD in Computer Science from Saarland University where he worked as researcher in the field of information systems. His research focus was on indexing, big data, and main memory databases.

3. Real-time analytics as a service at King

By Gyula Fóra, King

This talk introduces RBea, our scalable real-time analytics platform at King built on top of Apache Flink. The design goal of RBea is to make stream analytics easily accessible to game teams across King. RBea is powered by Apache Flink and uses the framework’s capabilities to it’s full potential in order to provide highly scalable stateful and windowed processing logic for the analytics applications. RBea provides a high-level scripting DSL that is more approachable to developers without stream-processing experience and uses code-generation to execute user-scripts efficiently at scale.

In this talk I will cover the technical details of the RBea architecture and will also look at what real-time analytics brings to the table from the business perspective. If time permits I will also give some outlook on our future plans to generalise and further grow the platform.

Gyula Fóra is a Data Warehouse Engineer in the Streaming Platform team at King, working hard on shaping the future of real-time data processing. This includes researching, developing and sharing awesome streaming technologies. Gyula grew up in Budapest where he first started working on distributed stream processing and later became a core contributor to the Apache Flink project.