Tal Weiss explores five crucial Java techniques for distributed debugging and some of the pitfalls that make bug resolution much harder, and can even lead to downtime.
The panelists discuss the Scala compiler fork (typelevel.org): Is this a positive and natural outgrowth of a growing language or will this development cause irreparable rifts in the Scala community?
Peter Pilgrim presents the experience of adopting Scala in the digital enterprise. He provides technical and development advice to agile teams new to implementing Scala.
Chris Richardson discusses an event-driven microservice architecture, it’s benefits and drawbacks and how Spring Boot can help, implementing business logic using domain models written in Scala.
Sean Owen introduces Spark, Scala and random decision forests, and demonstrates the process of analyzing a real-world data set with them.
Elasticity is a key component in reactive systems and James Ward navigates the different characteristics of different implementations of this concept: Akka, Scala, RxJava, and more.
Jonathan Bell & Gail Kaiser introduce Phosphor, a dynamic taint tracking system for the JVM, describing the approach used to achieve portable taint tracking.
Marius Eriksen explains Twitter's experiences with functional programming (with Scala) @ Twitter: where functional techniques worked and where not. Also: how the Scala language has scaled with Twitter
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
Jan Machacek demos creating and using reactive APIs in Scala with Spray and Akka.
Glen Peterson uses the Expression Problem to compare refactoring in Java, Scala and Clojure, showing how traits minimize changes in Scala when an interface changes and how Clojure avoids some issues.
Sponsored by Goldman Sachs. Java 8 has Streams, Scala has parallel collections, and GS Collections has ParallelIterables. How well do they perform?