Apache Flink Meetup @idealo

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We’re very excited to announce our second Apache Flink Meetup in 2017. Among others we will have talks presented by data Artisans. Join us for an evening of bagels, beer, and the latest and greatest on Apache Flink® at our host idealo (https://www.idealo.de/unternehmen/jobs/).

Agenda:

7:00 pm Bagels, Beer, Networking

7:30 pm Introduction by idealo (https://www.idealo.de/unternehmen/jobs/)

7:40 pm Stateful Stream Processing with Apache Flink

By Tzu-Li (Gordon) Tai, data Artisans (http://data-artisans.com)

As Apache Flink continues to push the boundaries of stateful stream processing as an integral part of its past releases, increasing numbers of users are starting to realize the potential of stateful stream processing as a promising paradigm for robust and reactive data analytics as well as event-driven applications.

This talk aims at covering the general idea and motivations of stateful stream processing, and how Flink enables it with its powerful set of state management features and programming APIs. In addition to that, we will also take a look at the recent advancements related to Flink's state management and large state handling that were driven by our team at data Artisans team in the latest version 1.3 (expected release by end of May / early June).

8:30 pm An introduction to Apache Beam via Nexmark, a benchmark suite
for batch and streaming systems

By Ismaël Mejía, Talend (https://www.talend.com/)

Apache Beam is a unified programming model to express both batch and streaming use cases. By neatly separating properties of the data from run-time characteristics, Beam enables users to easily tune requirements around completeness and latency and run the same data processing job (pipeline) across multiple runtime environments including Apache Flink.

In this talk we will detail some of the Apache Beam concepts by introducing Nexmark, a benchmarking suite implemented on Beam. We will discuss the properties that make Apache Beam the perfect tool to develop a benchmarking suite and how Nexmark bridges an existing gap in the Big Data benchmarking world. Also we’ll see how Nexmark serves as a rich integration test of the correct implementation of both the Beam runners (for systems like Apache Spark, Apache Flink and Apache Apex) and the new features on Beam.