We'll look at the problems and tasks of Hadoop exploitation and explain how we've adapted Hadoop for the Yandex infrastructure.
We’ll go into the details of Side Effect Injection approach, look at the Java code compilation variants, dig into one bytecode modification case in JVM, dissect Java formal grammar, and then play with it all using a real application as an example.
In this talk we’ll share how we look for functional problems in the compiler of Zing Java machine, using automatic generator of test programs on Java.
We'll focus on loading data into Hadoop for later analysis.
This talk is about how to come into/start your own Spark + Machine Learning and get away with it. It will be useful for those with no experience in ML in distributed systems.
We'll look at Reactive approaches with Spring 5 and Reactor 3 and learn how to migrate from Spring 4 to the new Reactive Spring 5, using a crypto trading platform as an example.
We’ll touch on both theoretical aspects and some practical approaches for high-performance algorithms development.
Making an internal ML hackathon without any experience and longtime preparation and getting a real benefit from it.
We'll cover the main architecture of Spark ML library, as well as a row of limitations which can make it harder to use the library and how to avoid them. We'll use the problem of news feed ranging in Odnoklassniki social network as an example to demonstrate the work of standard library and its extensions.
We'll dwell on what's included in JDK 9, the proposed changes to the release cadence of the JDK, the numbering scheme and GPL released binaries. We’ll also look at the introduction of a long-term support (LTS) model and what that means for developers and administrators, along with the future of the Java platform.
What is necessary to effectively test Java EE applications, as well as how to keep fast feedback, sufficient coverage, and constant development velocity. All of the time will be spent live-coding test cases with different scopes using different technologies. We will especially focus on how to develop maintainable test code with high quality that embraces principles of software craftsmanship.
We'll use Vert.x to write an app and learn how to add functions to this app really fast, how to avoid the old code redesign, how to easily scale, along with the features you get in so doing. We'll explain where Vert.x is most efficient. The talk will be useful for those who want to start using Vert.x.
A few words about the general stack, in more detail about Ignite in tow with various services.
We'll look into a standard solution of the problem in Live Demo mode on the base of Spring Cloud project. During this demo, we'll dwell on inside realization of client load balancing with examples from different libraries.