Stateful stream processing made easy with Apache Flink.


Apache Flink's powerful and elegant stream oriented API is the natural tool to meet the needs of real-time, or almost real-time, analysis of the huge data volumes arising, for instance, in IoT, analytics and machine learning. Starting from a very introductory definition of what streams are in Flink, we will follow code examples and short theoretical digressions that we will let us discover how to approach concrete problems with the DataStream API and to see Flink at work with tools like Kafka, Zookeeper, HBase and Cassandra.

Language: English

Level: Beginner

Alberto Mancini

Developer - K-Teq

I got a PhD in Applied Math and I indulged to my feeling for Software Development since the begin of the century when I started my adventure as freelance developer and consultant. #ML #DataScience #web #java #flink #streams

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Francesca Tosi

Numerical Analyst - K-Teq

Numerical Analyst and developer at K-Teq I got a PhD in Applied Math in 2006. I did research for some years in the field of computational fluid dynamics, working for research centers and international companies: ETH Zentrum (Zurich, CH); Exa Corporation (Burlington, MA/Usa); Ferrari (Italy); Ansys (Hannover, Germany). After the CFD and HPC experience, back in Italy, I started to work as a freelance developer, mostly with java and in the area of compute and data intensive applications, Machine Learning and high volume data processing.

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