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Spring Data : Modern Data Access for Enterprise Java - Mark Pollack

Spring Data

Modern Data Access for Enterprise Java

By: Mark Pollack, Oliver Gierke, Thomas Risberg, Jon Brisbin, Michael Hunger

eText | 12 October 2012 | Edition Number 1

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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 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
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Non-FictionComputing & I.T.DatabasesData WarehousingData Mining

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