Description:
You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop.
Through several sample projects, you'll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You'll also discover the features Spring Data adds to Spring's existing JPA and JDBC support for writing RDBMS-based data access layers.
- Learn about Spring's template helper classes to simplify the use of database-specific functionality
- Explore Spring Data's repository abstraction and advanced query functionality
- Use Spring Data with Redis (key/value store), HBase (column-family), MongoDB (document database), and Neo4j (graph database)
- Discover the GemFire distributed data grid solution
- Export Spring Data JPA-managed entities to the Web as RESTful web services
- Simplify the development of HBase applications, using a lightweight object-mapping framework
- Build example big-data pipelines with Spring Batch and Spring Integration
Brief description: Jon Brisbin is a member of the SpringSource Spring Data team and focuses on providing developers useful libraries to facilitate next-generation data manipulation. He's helped bring elements of the Grails GORM object mapper to Java-based MongoDB applications, he's provided key integration components between the Riak datastore and the RabbitMQ message broker, he blogs and speaks on evented application models, and is working diligently to bridge the gap between the bleeding-edge non-blocking and traditional JVM-based applications.