Spring Data: Modern Data Access for Enterprise Java

by Mark Pollack, Oliver Gierke, Thomas Risberg, Jonathan Brisbin, Michael Hunger

Overview

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

Product Details

ISBN-13:	9781449323950
Publisher:	O'Reilly Media, Incorporated
Publication date:	11/02/2012
Pages:	312
Product dimensions:	7.00(w) x 9.10(h) x 0.80(d)

About the Author

Dr. Mark Pollack has worked on Big Data solutions in High Energy Physics at Brookhaven National Laboratory and then moved to the financial services industry as a technical lead or architect for front office trading systems.
Always interested in best practices and improving the software development process, Mark has been a core Spring (Java) developer since 2003 and founded its Microsoft counterpart, Spring.NET, in 2004.
Mark now leads the Spring Data project that aims to simplify application development with new data technologies around Big Data and NoSQL databases.

Oliver Gierke is engineer at SpringSource, a division of VMware, project lead of the Spring Data JPA, MongoDB and core module. He has been into developing enterprise applications and open source projects for over 6 years now. His working focus is centered around software architecture, Spring and persistence technologies. He is regularly speaking at German and international conferences as well as author of technology articles.

Thomas Risberg is currently a member of the Spring Data team focusing on the MongoDB and JDBC Extensions projects. He is also a committer on the Spring Framework project, primarily contributing to enhancements of the JDBC framework portion.



Thomas works on the VMware's Cloud Foundry team developing integration for the various frameworks and languages supported by the Cloud Foundry project.



Thomas is co-author of “Professional Java Development with the Spring Framework” together with Rod Johnson, Juergen Hoeller, Alef Arendsen, and Colin Sampaleanu, published by Wiley in 2005.

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.

Michael Hunger has been passionate about software development for a long time. He is particularly interested in the people who develop software, software craftsmanship, programming languages, and improving code.



For the last two years he has been working with Neo Technology on the Neo4j graph database. As the project lead of Spring Data Neo4j he helped developing the idea to become a convenient and complete solution for object graph mapping. He is also taking care of Neo4j cloud hosting efforts.



As a developer he loves to work with many aspects of programming languages, learning new things every day, participating in exciting and ambitious open source projects and contributing to different programming related books. Michael is also an active editor and interviewer at InfoQ.

Table of Contents

• Foreword
• Preface
• Background
  • Chapter 1: The Spring Data Project
  • Chapter 2: Repositories: Convenient Data Access Layers
  • Chapter 3: Type-Safe Querying Using Querydsl
• Relational Databases
  • Chapter 4: JPA Repositories
  • Chapter 5: Type-Safe JDBC Programming with Querydsl SQL
• NoSQL
  • Chapter 6: MongoDB: A Document Store
  • Chapter 7: Neo4j: A Graph Database
  • Chapter 8: Redis: A Key/Value Store
• Rapid Application Development
  • Chapter 9: Persistence Layers with Spring Roo
  • Chapter 10: REST Repository Exporter
• Big Data
  • Chapter 11: Spring for Apache Hadoop
  • Chapter 12: Analyzing Data with Hadoop
  • Chapter 13: Creating Big Data Pipelines with Spring Batch and Spring Integration
• Data Grids
  • Chapter 14: GemFire: A Distributed Data Grid
• Bibliography
• Colophon