Spring Data
Modern Data Access for Enterprise Java
Publisher: O'Reilly Media
Released: October 2012
Pages: 316

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
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oreillySpring Data
 
4.5

(based on 4 reviews)

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Pros

  • Helpful examples (4)
  • Easy to understand (3)
  • Well-written (3)

Cons

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    • Intermediate (4)
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    5.0

    Excellent intro

    By Konrad Garus

    from Krakow, PL

    About Me Developer

    Verified Reviewer

    Pros

    • Accurate
    • Concise
    • Easy to understand
    • Helpful examples
    • Well-written

    Cons

      Best Uses

      • Expert
      • Intermediate

      Comments about oreilly Spring Data:

      The book is really well written. It quickly explains the basic ideas behind the data access API. It starts on familiar ground and shows a new way to solve old annoying problems, demonstrating new, streamlined ways to deal with JPA and JDBC repositories. It also offers a new way to write typesafe queries with all the benefits of IDE support: Querydsl.

      Then it shows how you can use most of the same API for NoSQL stores, including MongoDB, Neo4j and Redis. Each of those chapters starts with an introduction to the store itself (what it is, what it's good for). Then it shows how you can use the Spring Data API for, pardon me, Object-NoSQL mapping and writing repositories and queries. As it progresses it gradually dives deeper in the technical details.

      Next section is devoted to rapid application development. It features Spring Roo (which I'm not much interested in, not being a fan of codegen) and the REST repository explorer. The latter is a true gem and worth attention on its own. This chapter is also a very good demonstration of (introduction to?) a complete REST API with hyperlinks, CRUD, search, relationships between resources etc.

      Towards the end of the book there are also 3 chapters on Hadoop. The final chapter is devoted to GemFire, a distributed data grid.

      Spring Data is definitely worth a close look, and this book is a perfect resource to get started. Authors had a very good plan on what they wanted to say and executed it perfectly. The language is fairly light, clear and easy to follow. The examples are interesting, simple and concise at the same time. Very easy to understand, but not simplistic - they demonstrate the underlying power and do a good job of exposing all the gory details. You get to see a fairly wide and reasonably deep view of the framework.

      I received a copy of this book from one of the authors.

       
      5.0

      Excellent book about Spring Data

      By D Witherspoon

      from Colorado

      About Me Developer

      Pros

      • Accurate
      • Concise
      • Easy to understand
      • Helpful examples
      • Well-written

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        • Expert
        • Intermediate
        • Novice

        Comments about oreilly Spring Data:

        Spring Data by Michael Hunger, Jonathan L. Brisbin, Oliver Gierke, Mark Pollack, and Thomas Risberg is an excellent book to learn about how to use the Spring Data framework and be able to apply it to the project that you are working on. I am a big fan of the Spring framework and each time I get exposed to a new component of the framework like Spring Data I get more excited about the work that is being done there. This book is a must read for anyone developing software applications that needs to interact with a data source. Applying the techniques that are explained in this book will simplify the integration that it takes to work with different data sources. Throughout the book the authors explain how to use Spring Data framework to interact with different data sources like JDBC, Hibernate, Neo4j, and MongoDB to mention of few of the data source types.

        One of the sections in this book the I liked the most was the ones dealing with using Spring Data with Apache Hadoop. The latest challenges that we have today is dealing with large amounts of data and typically people look at the Apache Hadoop framework. The Authors do a great job showing how to use Spring to analyze data with Hadoop and create a Big data pipeline using Spring Batch and Spring Integration.

         
        4.0

        Get this book!

        By Tobias Trelle

        from Düsseldorf, Germany

        About Me Senior It Consultant

        Verified Reviewer

        Pros

        • Helpful examples
        • Well-written

        Cons

          Best Uses

          • Intermediate

          Comments about oreilly Spring Data:

          This book is a must-read for every Spring developer who is dealing with persistence, both relational and NoSQL. If you are using JPA, Spring Data helps you writing much cleaner code for repositories, pagination and sorting. If you are using one of the popular NoSQL datastores like MongoDB, Neo4j or Redis, you learn how to access them the Spring way: the well-know template pattern plus object mapping and repository support. Never heard of these strange names before? Don't mind - each of the NoSQL chapters comes with an introduction. Further on, you can learn how Spring Data can be used wtith Spring Roo - Spring's rapid application framework. The next big thing is Big Data: see how Spring interacts with Apache Hadoop. Last but not least you learn about Spring Data support for GemFire, VMware's commercial distributed in-memory database.

          The authors really know what they are talking about - all of them are working on some of the Spring Data projects. If these guys don't know it who else will? The book is packed with examples that can be easily downloaded from a github repository. A good starting point for implementing your own data access layer. It's really a hands-on book, but its rich index helps you using it a as reference as well.

          (2 of 2 customers found this review helpful)

           
          4.0

          Data access the Spring way

          By Alex

          from Berlin, Germany

          About Me Developer

          Verified Reviewer

          Pros

          • Easy to understand
          • Helpful examples

          Cons

            Best Uses

            • Intermediate

            Comments about oreilly Spring Data:

            The book provides a comprehensive overview of the Spring Data project with lots of helpful examples. Starting with a brief chapter on JDBC and relational databases, the reader is quickly introduced to the world of NoSQL data stores, including MongoDB, Neo4J and Redis. Focal to Spring's philosophy of data access are templates and repositories. While templates are used to manage the underlying resources and to map vendor-specific exceptions into Spring's own DataAccessException hierarchy, repositories are used to provide CRUD functionality and more sophisticated queries for data access. The introduced data stores structure data in different ways, either as a graph, as keys and values or document-based. Since each store has its own specifics, the framework does not try to hide access to different stores behind a single API (similar to JPA), but rather provides a consistent programming model to rely upon. Building upon the repository abstraction, the framework is also able to infer queries from method names following certain conventions, freeing the client from writing code, which can be largely considered boilerplate. In addition, Spring Data integrates nicely with Querydsl enabling the use of type safe queries, thereby reducing the risk of typos sneaking into your queries.

            Having introduced the mere data access, the remainder of the book deals with several applications of the capabilities provided by Spring Data, such as the integration into Spring's rapid application development tool Roo, or the facility of exporting repositories via a RESTful API which comes in handy for many data-driven backends. A topic which has gained more and more attention recently, and which is also tightly related to NoSQL is Big Data. Several examples show, how large volumes of data can be processed and stored using Hadoop and adjacent Spring modules, including Spring Integration and Spring Batch, before the book concludes with a brief introduction to GemFire, VMware's platform for distributed data management.

            Although prior knowledge of the framework is beneficial in order to put Spring Data in larger context and appreciate how the framework remains true to its philosophy of being non-intrusive, the examples make it easy even for beginners to follow the narrative.

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