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Spring Data [Kindle Edition]

Mark Pollack , Oliver Gierke , Thomas Risberg , Jon Brisbin , Michael Hunger
4.5 von 5 Sternen  Alle Rezensionen anzeigen (2 Kundenrezensionen)

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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

Über den Autor und weitere Mitwirkende

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. 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. 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. 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.


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The book is written by the core developers of the Spring Data Framework. In my eyes it served me very well getting started with Spring Data as well as in diving into more advanced topics such as the integration of QueryDSL for different technologies such as JPA or plain JDBC. In addition to that nearly two thirds of the book cover the support for NoSQL and Big Data Stores such as MongoDB, Neo4j, Redis or Hadoop.

Two smaller aspects are to criticize about the book: I would have liked to have an example for a Gradle based integration of QueryDSL and the chapter about Rapid Application Development is between the NoSQL and the Big Data chapters. It should have been put at the end of the book instead.

Overall you get a great introduction into the framework and some other new frameworks surrounding it.
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4.0 von 5 Sternen Data access the Spring way 4. November 2012
Von Alex
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.
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Die hilfreichsten Kundenrezensionen auf (beta) 4.8 von 5 Sternen  5 Rezensionen
5 von 6 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Get this book! 6. November 2012
Von Tobias Trelle - Veröffentlicht auf
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 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Excellent introduction to Spring Data 6. September 2013
Von Konrad Garus - Veröffentlicht auf
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.
5.0 von 5 Sternen Must read book on Spring Data 10. Mai 2013
Von David Witherspoon - Veröffentlicht auf
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.
1 von 5 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A must for Java developers dealing with persistence 2. April 2013
Von Tirthankar Bhowmick - Veröffentlicht auf
Using it for Neo4j. I like the fast pace at which various concepts are explained with examples. Do check code examples at [...]
0 von 5 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen excellent overview 14. Dezember 2012
Von Amazon Customer - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
Combining this with available documentation gives one a good in depth knowledge of the subject. Though i have still to try with big-data.
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