Building a recommender system using Spark and Akka + Java 9 Performance

General Details

• How could one combine Machine Learning and Performance ?

• Holding a cold beer and watching Willem Meints and Jeroen Borgers giving presentations about them.

• Both sessions seem to be very interesting, but on the other hand, difficult to attend.

• Thanks to our friends from Infi, we can have some food and drinks to keep us going on the sessions (and to have some fun!).

Agenda

18:00: Walk in - drinks and food are served
18:30: Introduction Utrecht JUG and Infi
18:45: First talk
19:30: Break
19:45: Second talk
20:30: Drinks

Interesting update: a lucky winner will receive a JetBrains licence!

Presentation Details

What Willem says about this presentation

Machine Learning to some is still very magical. The truth however is that this magic is actually much easier to use than you'd expect. Come and learn how you can use Apache Spark and Akka together to build a service that recommends items to users. In this session, I'm going to show you some of the bits that go into building a recommender system, how to actually implement one in Spark and finally how to integrate the recommender system into your application using Akka HTTP.

Who is Willem

Willem is a technical evangelist for Info Support, he writes and speaks about new technology and helps developers get started with new frameworks and tools on projects. When not at work he likes to photograph the varying dutch landscapes.

What Jeroen says about the presentation

After the introduction of the substantial change: lambdas and streams in Java 8, Java 9 introduces modular JDK (Jigsaw) and a large number of less drastic improvements. We can already see them, because Java 9 is Feature Complete since 26th of May. In production, though, it will take longer: General Availability in March 2017. In terms of performance in Java 9 there are some interesting improvements including Jigsaw, the compiler, locking, diagnostics, unsafe replacements, garbage collection and Strings. I will describe these improvements and put them in context, with code examples and demo.

Who is Jeroen

Jeroen is the principal consultant at jPinpoint and director at Profactive. He has extensive experience in the field of application performance and Enterprise Java. He has worked many years as a senior consultant for numerous organisations in various industries, as developer, architect, team leader, quality officer, mentor, auditor, performance tester, tuner, troubleshooter and trainer. He provides the Accelerating Java Applications training.