Recorded at SpringOne2GX Presenters: Phil Berman, Michael Minella & Derrick Shields Big Data Track Slides: http://www.slideshare.net/SpringCentral/iot-realized-the-connected-car-53122510

For this session we will explore the power of Spring XD in the context of the Internet of Things (IoT). We will look at a solution developed with Spring XD to stream real time analytics from a moving car using open standards. Ingestion of the real time data (location, speed, engine diagnostics, etc) into HDFS, analyzing it to provide highly accurate MPG and vehicle range prediction, as well as providing…

Recorded at SpringOne2GX 2015 Presenters: Stephane Maldini & Rossen Stoyanchev Web / Javascript Track Slides: http://www.slideshare.net/SpringCentral/introduction-to-reactive-programming

This is your one stop shop introduction to get oriented to the world of reactive programming. There are lots of such intros out there even manifestos. We hope this is the one where you don't get lost and it makes sense. Get a definition of what "reactive" means and why it matters. Learn about Reactive Streams and Reactive Extensions and the emerging ecosystem around them. Get a sense for what going reactive…

Recorded at SpringOne2GX 2015. Speakers: John Blum & Luke Shannon Data/Integration Track Slides: http://www.slideshare.net/SpringCentral/building-highly-scalable-spring-applications-using-inmemory-data-grids-53086251

Building highly scalable, low latency applications while simultaneously preserving consistency, high availability and resiliency requires a new breed of technology. In this presentation we introduce Pivotal GemFire along with the open source offering, Apache Geode. Apache Geode is a proven, distributed, in-memory database with ACID properties that can handle large volumes of…

Recorded at SpringOne2GX 2015. Presenters: Fred Melo & William Markito Oliveira Big Data Track Slides: http://www.slideshare.net/SpringCentral/implementing-a-highly-scalable-stock-prediction-system-with-r-apache-geode-and-spring-xd

Finance market prediction has always been one of the hottest topics in Data Science and Machine Learning. However, the prediction algorithm is just a small piece of the puzzle. Building a data stream pipeline that is constantly combining the latest price info with high volume historical data is extremely challenging using traditional platforms, requiring a lot of…

Recorded at SpringOne2GX 2015. Presenters:Yann Cébron - JetBrains, Stéphane Nicoll, Pivotal Core Spring Track Slides: no slides all demo

For many years, IntelliJ IDEA has been widely used in projects employing the Spring Framework. The latest version of the IDE (14.1) now ships with dedicated Spring Boot support. In this practical presentation we're going to look at some features from IntelliJ IDEA that will help you not only get started with Spring Boot but also guide you along the way, helping with coding and configuration management for your application. As a bonus, we'll also discover…

Recorded at SpringOne2GX 2015 Presenter: Mark Pollack Big Data Track Slides: http://www.slideshare.net/SpringCentral/spring-xd-today-and-tomorrow In this talk we will cover the major new features added to Spring XD since last year as well as upcoming changes for the next major version. Key integrations driven by the Big Data ecosystem at large such as Kafka, Spark, functional programming, integration with Python, and designer/monitoring UIs will be introduced and demonstrated. The next major version of XD will shift to a foundation based on Cloud-Native architectural principles, where each…

Recorded at SpringOne2GX 2015 Presenters: Sam Brannen & Nicolas Fränkel Core Spring Track Slides: http://www.slideshare.net/SpringCentral/get-the-most-out-of-testing-with-spring-42-53128369

Join Sam Brannen and Nicolas Fränkel to discover what's new in Spring Framework 4.2's testing support and learn tips and best practices for testing modern, Spring-based applications. Sam Brannen is the Spring Test component lead and author of the Spring TestContext Framework, and Nicolas Fränkel is the author of the book "Integration Testing from the Trenches".

In this session, Sam and Nicolas will cover…

講者：Oliver Gierke

A year has passed and the Spring Data shipped two release train iterations packed with interesting features. This talk will give a broad overview of the most important introduced in the Fowler and Gosling release trains. We will cover recent additions and improvements in Spring Data Commons - the module that's shared amongst the store specific ones. We'll then delve into the latest and greatest features of individual store modules, like JPA, MongoDB and the community ones as well.

Tuesday, Jan 26th, 2016 10:00AM PST (San Francisco GMT-08:00) Register

講者：Kenny Bastani

This webinar introduces you to a sample application that combines multiple microservices with a graph processing platform to rank communities of users on Twitter. The problem we’re going to solve is how to discover communities of influencers on Twitter using a set of seed profiles as inputs.

To solve this problem without a background in machine learning or social network analytics might be a bit of a stretch, but we’re going to take a stab at it using a little bit of computer science history. We’re going to use a collection of popular tools as a part of this article’s sample application. The tools we’ll use, in the order of importance, will be: Spring Boot Neo4j Apache Spark Docker RabbitMQ While there are some missing pieces, such as securing REST API access, and mapping device volumes to the containers, these kinds of important topics will be covered in future webinars.