Distributed Computing with Apache Spark by Martin Tapp

How would you apply an algorithm over hundreds of million data points?

How would you scale your existing code to run over 1,000 nodes?

Please join us for today’s meetup on “Distributed Computing with Apache Spark” to find out how modern cluster computing frameworks can fundamentally change the performance and scalability characteristics of cloud software. In this talk, we’ll see how these frameworks work and how you can harness their power to solve business problems involving large amounts of data or drastic reduction in algorithm completion time.

Martin Tapp:

Martin is a Senior Research Engineer at Kronos Inc. He currently works within the Data Science Team where he is responsible for the Big Data platform and architecture as well as for the scalability of data science models. He also applies machine learning and other techniques to workforce management problems. He received a Ph.D. in Software Engineering from Ecole Polytechnique of Montreal in 2013 focusing on automating the data-interchange software used by distributed real-time systems. His other research interests include distributed computing, web and network technologies, compilers, and code generation.

Nous vous proposons pour notre prochain meetup soirée DevOps / Robot Framework.