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Reactor 1.1.0.RELEASE now available

The Reactor team is pleased to announce that some significant updates to the Reactor framework are now available in the 1.1.0.RELEASE version of Reactor’s flexible, asynchronous, fast data framework. This version includes numerous bug fixes and rewrites of key components to make them faster and, maybe more importantly, more efficient in terms of memory usage. Reactor 1.1 now includes the fantastic gs-collections library from Goldman Sachs [1] which provides a very fluent API for dealing with maps and collections of all kinds.

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Spring for Apache Hadoop 2.0 RC3 released

We are happy to announce that Spring for Apache Hadoop version 2.0 RC3 has just been released.

Now includes support for the latest Hadoop distributions - Pivotal HD 2.0, Cloudera CDH5 and Hortonworks HDP 2.1


Other than version upgrades, the changes in this version revolve around partitioning support for writing datasets SHDP-327.

The main focus for Spring for Apache Hadoop 2.0 is to add YARN application development support in addition to continue to provide
improvements in the HDFS and MapReduce support. You can see many of these new YARN features in use in
the YARN samples and in the
new Spring IO Guides.

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Spring Data release train Dijkstra RC1 released

I am happy to announce the first release candidate of the next Spring Data release train named Dijkstra. The full list of participating modules looks as follows:

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Spring Framework 4.0.4 released

Dear Spring community,

It’s my pleasure to announce that Spring Framework 4.0.4 is now available. This is a straightforward maintenance release after 4.0.3, primarily fixing regressions and other recent bugs. It also comes with a range of minor dependency updates (including ASM 5.0.2).

http://projects.spring.io/spring-framework/

Aside from working towards our 4.1 release in July, we intend to do a 4.0.5 & 3.2.9 pair of releases in late May. Both of the latter are the last planned releases in the respective line. So if you have any critical bug reports to consider for those branches still, please let us know - through creating new JIRA issues or through escalating existing JIRA issues…

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Spring Social 1.1.0 Released

Dear Spring Community,

I’m very happy to announce the general availability of Spring Social 1.1.0. Along with the release of the core Spring Social project, Spring Social Facebook 1.1.0, Spring Social Twitter 1.1.0, and Spring Social LinkedIn 1.0.0 are also now available.

These releases include several new features, including:

  • Simplified Java and XML configuration support
  • A new ReconnectFilter to automatically reestablish a connection when a token has expired or been revoked
  • Updated API bindings for Facebook, Twitter, and LinkedIn
  • A generic connection factory for APIs where there is not (yet) connection framework support
  • Tighter Spring Security integration, including SocialAuthenticationFilter for provider-based sign-in
  • Thymeleaf template support
  • Updated documentation
  • …and much more…
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Spring Boot 1.0.2.RELEASE Available Now

Spring Boot 1.0.2.RELEASE is available now in the Spring and Maven Central repositories. This is mostly a bug-fix release (nothing major, but please upgrade if you are using an older version). There are also a couple of nice new features.

My favourite additions are the new @IntegrationTest features. Here’s an example:

@RunWith(SpringJUnit4ClassRunner.class)
@SpringApplicationConfiguration(classes = SampleActuatorApplication.class)
@WebAppConfiguration
@IntegrationTest("server.port=0")
public class SampleActuatorApplicationTests {

	@Value("${local.server.port}")
	private int port;

        ...

}
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Spring Security OAuth 2.0.0.RC1 Available

Spring Security OAuth 2.0.0.RC1 is available now from the Spring Repo. This is a huge step in the direction of modernisation and ease of use for OAuth server and client apps on Spring.

The headline feature is support for @Configuration(for OAuth2 only) and if you use Spring Boot to write your app you can serve tokens and protect the API resources in about 25 lines of code:

@Configuration
@EnableAutoConfiguration
@EnableResourceServer
@RestController
public class Application {

	public static void main(String[] args) {
		SpringApplication.run(Application.class, args);
	}

	@RequestMapping("/")
	public String home() {
		return "Hello World";
	}

	@Configuration
	@EnableAuthorizationServer
	protected static class OAuth2Config extends AuthorizationServerConfigurerAdapter {

		@Autowired
		private AuthenticationManager authenticationManager;
		
		@Override
		public void configure(AuthorizationServerEndpointsConfigurer endpoints) throws Exception {
			endpoints.authenticationManager(authenticationManager);
		}
		
		@Override
		public void configure(ClientDetailsServiceConfigurer clients) throws Exception {
		 	clients.inMemory()
		        .withClient("my-trusted-client")
		            .authorizedGrantTypes("password", "authorization_code", "refresh_token")
		            .authorities("ROLE_CLIENT", "ROLE_TRUSTED_CLIENT")
		            .scopes("read", "write", "trust")
		            .resourceIds("oauth2-resource")
		            .secret("secret");
		}

	}

}
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Spring XD 1.0.0.M6 Released

The Spring XD team is pleased to announce that Spring XD Milestone 6 is now available for download.

This is our biggest release yet! The team has been hard at work, and Milestone 6 contains a wealth of new features that meet enterprise requirements in terms of reliability, performance, and user experience. Below is a quick Top Ten (in no particular order), but if you checkout the release notes you will realize how difficult it is to pick out 10 from the list of 299.

  • Distributed and Fault Tolerant Runtime: Leader election among multiple xd-admin servers and automatic redeployment of modules to other xd-containers in the case of failure. ZooKeeper is introduced to manage the cluster and its deployment state.

  • Support for running XD on YARN: Run admin and container nodes on a Hadoop YARN cluster rather than on VMs or physical servers that you need to manage. There are simple configuration and shell scripts that make this process very easy.

  • Deployment Manifests: When deploying a stream you can provide a deployment manifest that describes how to transform the logical stream definition (e.g. http | hdfs) to a physical deployment on the cluster. You can specify the number of instances of each module to deploy and also a criteria expression (using SpEL) that evaluates each of the available containers in the cluster to determine the best matches for those module instances. This will be an area of active development for the next release as we extend the manifest to include support for data partitioning strategies.

  • Real-Time Evaluation of Machine Learning Scoring Algorithms: Integration with the JPMML-Evaluator library that provides support for a wide range of model types and is interoperable with models exported from popular data analysis packages such as R. Integration with other libraries is supported by providing an implementation of XD’s Analytic and MappedAnalytic abstractions. Give it a try with the sample application based on the classic iris data set.

  • Updated UI: A redesign and rewrite of the UI that has a modern look and feel.

  • Enhanced DSL Auto-completion: Tab completion now works within the value of the –definition option when creating streams and jobs. Creating streams and jobs has never been easier. Try it out via xd-shell!

  • Default stream for the Batch Job lifecycle: Batch jobs are a source of event data. Add a tap to a Batch Job to receive events upon upon job success/failure, individual step actions or even item level actions. This functionality along with the support for launching jobs by sending messages to a named channel, enables your applications to have a complex event-driven flow between the batch and streaming domains.

  • Improved server and module configuration options: Server and module configuration have been separated to help with the life-cycle of upgrading them independently. Module configuration has been made more modular while allowing for shared configuration between related modules.

  • High performance TCP/UDP source: Based on the Reactor project - the Reactor IP source on commodity hardware can consume ~1 Million msgs/second.

  • FTP to HDFS job: Out of the box support for jobs to transfer files from FTP to HDFS. Those jobs take advantage of another new feature: partitioning of steps across multiple XD Containers.

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Second Service Release For Spring Data Release Train Codd Released

I am happy to announce the second service release of the Spring Data release train named Codd. The full list of participating modules looks as follows:

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Spring Integration 4.0 Release Candidate Available

We are pleased to announce that the Spring Integration 4.0 release candidate (4.0.0.RC1) is now available.
Please use the Milestone Repository with maven or gradle,
download a distribution archive,
or see the project home page for links to the updated documentation, and Maven/Gradle configuration details.

The release includes several bug fixes, some new features and further improvements with the GA release due near the end of April.

Here is a summary of major changes since the last milestone

[email protected] and @InboundChannelAdapter__

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