Apache Beam intro and use-cases


18:30 Welcome
19:00 Start Sessions
20:30 Networking

In cooperation with the Kettle community we're proud to bring the first Apache Beam Belgium meetup. This session is an introduction to Beam and some interesting use-cases. Later in the year and starting next year we will come back with some deep dives, but let's start with the introduction.

*** Apache Beam introduction, use-cases and demo * talk by Matthias Baetens ***

Matthias will give an introduction to what Beam is and how it is used in the industry. We'll take a look at some code and an interactive demo.

*** BeamSQL * talk by Robin Qiu (Google) ***

Robin will talk about the ongoing development on BeamSQL, and have a live demo on running a SQL transform embedded in a Beam Python pipeline on Apache Flink runner.

*** Video Analytics for Football games @ SportTotal.tv * talk by
Victor Sonck (ML6) ***

This use case is about how we used Apache Beam to analyze and process, in near-real time, football game stream feeds. The goal was to determine events (start of game, team detection, player tracking, ball tracking) and performing analytics on these videos (duration, ball possession, score, ..). The client for which we implemented this use case is https://www.sporttotal.tv/.

In particular, Apache Beam Dataflow runner was used with Python SDK to create streaming pipelines. In this pipeline we used sliding windows to chunk the video frames into sets of sequence of frames, which could be used as input for different machine learning models.

*** Visual Beam Pipeline Development with Kettle
* talk by Matt Casters ***

Kettle is an open source data integration tool under an Apache license. This session will demonstrate how we integrated with Apache Beam to allow you to visually build pipelines that can be executed on the various Beam runners without the need to write any code.
After an introduction on the Kettle project you will get an overview of the supported functionalities and best practices with a number of demos on DataFlow, Spark and Flink.