Spring Social Facebook 2.0.0.RELEASE Released

Dear Spring Community,

I’m happy to announce the release of Spring Social Facebook 2.0.0.RELEASE. This release completes the overhaul of Spring Social Facebook to target version 2.3 of Facebook’s Graph API.Facebook will be turning off version 1.0 of their Graph API on April 30th, so it is highly recommended that you upgrade to Spring Social Facebook 2.0.0.RELEASE as soon as possible.

As has been mentioned in last week’s release candidate and in milestone releases prior to that, Facebook’s Graph API introduced several breaking changes which resulted in many breaking changes between Spring Social Facebook 1.1.x and Spring Social Facebook 2.0.0. Also, even some operations that still work do not work as they did previously. For example, it is no longer possible to fetch a list of all of a users’s Facebook friends; you can only fetch a list of their friends who have also authorized your application with Facebook.

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Spring integration Java DSL 1.1 M1 is available

Dear Spring community,

We are pleased to announce that the Spring Integration Java DSL 1.1 Milestone 1 is now available. Use the Milestone Repository with Maven or Gradle to try it in early access.

compile "org.springframework.integration:spring-integration-java-dsl:1.1.0.M1"

To be honest, many of the planned features for 1.1 are not implemented yet, but thanks to encouragement from our pal Josh Long and the recent announcement about the Apache Kafka support (Spring Integration Kafka Support 1.1 Release, Spring XD 1.1.1 Release), we’ve released this Milestone 1 mainly to showcase the Apache Kafka support in the Java Configuration DSL.

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Using Apache Kafka for Integration and Data Processing Pipelines with Spring

Applications generated more and more data than ever before and a huge part of the challenge - before it can even be analyzed - is accommodating the load in the first place. Apache’s Kafka meets this challenge. It was originally designed by LinkedIn and subsequently open-sourced in 2011. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. The design is heavily influenced by transaction logs. It is a messaging system, similar to traditional messaging systems like RabbitMQ, ActiveMQ, MQSeries, but it’s ideal for log aggregation, persistent messaging, fast (_hundreds_ of megabytes per second!) reads and writes, and can accommodate numerous clients. Naturally, this makes it perfect for cloud-scale architectures!

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