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 functionalityExplore Spring Data's repository abstraction and advanced query functionalityUse Spring Data with Redis (key/value store), HBase(column-family), MongoDB (document database), and Neo4j (graph database)Discover the GemFire distributed data grid solutionExport Spring Data JPA-managed entities to the Web as RESTful web servicesSimplify the development of HBase applications, using a lightweight object-mapping frameworkBuild example big-data pipelines with Spring Batch and Spring Integration
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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 functionalityExplore Spring Data's repository abstraction and advanced query functionalityUse Spring Data with Redis (key/value store), HBase(column-family), MongoDB (document database), and Neo4j (graph database)Discover the GemFire distributed data grid solutionExport Spring Data JPA-managed entities to the Web as RESTful web servicesSimplify the development of HBase applications, using a lightweight object-mapping frameworkBuild example big-data pipelines with Spring Batch and Spring Integration
Imprint | O'Reilly Media |
Country of origin | United States |
Release date | November 2012 |
Availability | Expected to ship within 12 - 17 working days |
First published | November 2012 |
Authors | Jon Brisbin |
Contributors | Mark Pollack, Oliver Gierke, Thomas Risberg, Michael Hunger |
Dimensions | 233 x 179 x 28mm (L x W x T) |
Format | Paperback |
Pages | 150 |
ISBN-13 | 978-1-4493-2395-0 |
Barcode | 9781449323950 |
Categories | |
LSN | 1-4493-2395-2 |