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. Learn about Spring’s template helper classes to simplify the use ofdatabase-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
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.
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Publisher: O'Reilly Media
Page Count (est.): 288
Pub Date: 10/26/2012