Speakers: Oliver Gierke and Thomas Darimont

Slides: https://speakerdeck.com/olivergierke/spring-data-repositories-best-practices

The repository abstraction layer is one of the core pieces of the Spring Data projects. It provides a consistent, interface-based programming model to allow implementing data access layers easily for relational and NoSQL databases. We will have a look at the lessons learned from the application of it in various customer projects and summarize best practices for you to apply in your projects. The session will also discuss advanced features like the Querydsl integration, the integration of custom implementation code as well as hooks into Spring MVC and Spring HATEOAS.

Learn more about Spring Data at: http://projects.spring.io/spring-data

Learn more about Spring HATEOAS at: http://projects.spring.io/spring-hateoas

Learn more about Spring MVC at: http://projects.spring.io/spring-framework

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Spring Data Redis 1.2.0 has been released and is now available from Maven Central. This release sums up the fixes and enhancements from 1.1.1 and RC1 plus an updated documentation. The release has been tested against Redis 2.4.6, 2.6.17, 2.8.6 as well as the recent 3.0-beta1 using the latest Spring framework 3.2 and 4.0 versions.

Reference Documentation | Changes | JavaDoc

Up next SD Redis will join the Spring Data release train Dijkstra. We are looking forward to your feedback on Twitter or in the issue tracker.

For more information about Spring Data Redis please see the home page.

Spring Boot 1.0.0 (RC4) has been released and is available in the repo.spring.io repository. There are some bug fixes from RC3 and a load of updated third-party dependencies. New features include

• Support for Spring Loaded reloading of classes during development in Maven and Gradle builds.
• A starter pom for spring-data-rest (and a sample).
• Lots of new documentation (all in the source code but published as usual at http://projects.spring.io/spring-boot.
• Automatic main class detection for "gradle run".
• Support for relaunching and incrementing Spring Batch jobs on startup.

If there are no more…

Recorded at SpringOne2GX 2013 in Santa Clara, CA.

Speakers: Alvaro Videla, Jan Machacek

Jan will show how to use RabbitMQ to connect components on different platforms. After a few introductory slides explaining the main concepts, the rest of the talk will be live code. The coding will begin by showing Spring Integration code to connect to RabbitMQ to send and receive messages--think byte[] values back and forth to start with. Jan will then show the real power of RabbitMQ by replacing the RPC server component by native code in C++: we will write image processing component. To make matters even better--faster--we will then use CUDA to perform the image processing. Come to Jan's talk and demo if you want to find out how to use RabbitMQ in the core of your application, especially if your application needs to tie together code on completely different platforms and if it performs heavy number crunching or image processing. You do not need to have deep knowledge of Spring Integration, AMQP or OpenCV, ...; all that you will need is your inner geek.

Learn more about RabbitMQ at

http://www.gopivotal.com/products/pivotal-rabbitmq

and

http://www.rabbitmq.com

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Recorded SpringOne2GX 2013 in Santa Clara, CA

Speaker: Gary Russell A comprehensive review of message routing within a flow - including

• exactly how and when replyChannel and errorChannel headers are used
• how and when these headers apply in an error flow
• differences between synchronous and asynchronous processing (with task executors and pollers)
• Use of SpEL (for messagemethod mapping as well as certain "dynamic" config attributes)
• Type conversion (via SpEL, datatype channels, etc) Implicitly created channels
• How chains work How messages are mapped to methods when a message arrives at a component
• How gateway methods are mapped to messages (and a first look at some enhancements we are considering)
• Options for…

This post is intended to introduce the Groovy Bean Builder to Java developers as a powerful alternative or supplement to Java @Configuration and XML configuration. The Spring Framework release 4.0 includes a port of the Grails Bean Builder to the core Spring Framework, providing a Groovy DSL for configuring Spring applications. Groovy and Grails developers are no doubt familiar with configuring Spring applications this way and I expect the rest of you are already thinking "How cool is that?"

Don't worry if you're not a Groovy expert. Just as many Java programmers use another popular Groovy DSL, Gradle, to build applications, you only need to know some basic syntax to get started. Sample code is available on github…

Hot on the heels of Spring Data's Codd GA release, there is a new Getting Started guide for Spring Data REST, Accessing Data with REST. It shows you how to create up an application with a JPA backend and a RESTful, hypermedia-driven front end.

Spring Data REST does all the heavy lifting of building a powerful RESTful front end as well as writing the JPA queries for the back end. To top it off, the guide leverages Spring Boot so you are using the latest-and-greatest from the Spring team.

Cheers!

Recorded at SpringOne2GX 2013 in Santa Clara, CA

Speakers: Smitha Gudur, Manoj Joshi, Redbasin Networks

Cancer/life science drug research models are very rich in relationships, relationship heterogeneity and entity inter-dependencies. Most entity metadata is dynamic and unpredictable making it difficult to fit such models in traditional relational landscape. Redbasin Networks uses a hybrid Nosql strategy that supports composite and rich document metadata that is interconnected pervasively. Cancer and life science data is excessively nested. You will find this useful if you are building complex engineering and/or scientific applications, and need insights on how to merge data from many diverse data-sets and map it to an intuitive and effective graph database model. We will show using code examples how complex metadata can be engineered using Spring, Neo4J and Mongo, to create useful drug insights for the drug researcher, and also provide a platform for technologists to build sophisticated life science applications.

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Recorded at SpringOne2GX 2013 in Santa Clara, CA

Speakers: Peter Bell (MongoDB Master), Costin Leau (Elasticsearch), Christoph Strobl (Solr) and Michael Nitschinger (Couchbase)

Spring Data has started as an umbrella project consisting of many individual modules - per supported data store. While some of these data store modules - like the JPA and MongoDB ones - are maintained by Pivotal engineers a lot of community implementations have popped up lately. They build on the foundations of the Spring Data Core module and expose the Spring Data programming model for others stores. The session will feature maintainers and contributors of the community modules for Solr (Christoph Strobl), Elasticsearch (Costin Leau), Couchbase (Michael Nitschinger) and MongoDB (Peter Bell), who will talk about the latest and greatest features of the upcoming releases and give an impression of how they used the APIs of Spring Data Core to build the module. Spring Data has stared as an umbrella project consisting of many individual modules - per supported data store. While some of these data store modules - like the JPA and MongoDB ones - are maintained by Pivotal engineers a lot of community implementations have popped up lately. They build on the foundations of the Spring Data Core module and expose the Spring Data programming model for others stores. The session will feature maintainers and contributors of the community modules for Solr (Christoph Strobl), Elasticsearch (Costin Leau), Couchbase (Michael Nitschinger) and MongoDB (Peter Bell), who will talk about the latest and greatest features of the upcoming releases and give an impression of how they used the APIs of Spring Data Core to build the module.

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