Spring Data – by Mark Pollack et al
TLDR: If you are working with Spring Data on a daily basis and want a complete and thorough overview of the framework then this book is all you will need. It covers all aspects of Spring Data without being overly verbose, and even if you have used Spring Data quite a lot already (like me), then I still believe you’ll discover something useful from this book. You will also find bonus chapters in context with Spring Data on Spring Roo, the REST repo exporter (very cool!), ‘Big Data’ via Hadoop, Pig, Hive and Spring Batch/Integration, and also coverage of GemFire.
I’ve been working professionally with Spring Data for quite some time now, both for ‘old skool’ RDBMS and also a lot of NoSQL (primarily MongoDB and Redis). The company I was working for at the time the Spring Data projects were approaching release were somewhat early-adopters, and in combination with the fact that their applications were firmly rooted in Spring made the decision to use this framework an easy choice. After some initial problems, which should be expected with a new technology (such as config issues and incompatibly between libraries bundled in JARs etc), Spring Data has provided a massive boost to productivity, and it is now my de facto choice when implementing persistence within Spring.
About the book itself: The first few chapters provide a great introduction to Spring Data, and describe the key motivations and techniques behind the framework. If you are simply modifying an already configured Spring Data app then this is all you need (but please do keep reading to learn more!). The next few chapters cover integration with an RDBMS, and also the popular NoSQL implementations – MongoDB, Neo4j and Redis. If you are working in one specific technology then reading the corresponding chapter will get you up and running quickly. Although Spring Data provides a common abstraction layer, it allows datastore-specific functionality to bleed through the interfaces (which is a good thing in my opinion, as it allows you to leverage specific features and strengths of the underlying technology), and this book will provide an excellent grounding and explanation of key concepts within each underlying datastore technology so that you can become productive quickly. Of course, you can also head over to the Spring Source website to learn the really advanced stuff (if you want to).
Part 4 of the book covers several interesting advanced features of the framework, such as using Spring Roo to auto-generate repository code, and also a brief guide on how to use the REST Repository Exporter. Metaprogamming and RAD tools like Spring Roo (and web-frameworks such as Grails and Play) are becoming increasingly popular in the industry, and so this chapter is a nice addition to the book. The REST exporter is also a very cool feature, and essentially allows you to expose CRUD functionality on your repositories via a REST interface. For anyone building a SOA-based app (or using micro-services etc) then encapsulating datastores and exposing simply functionality via a well defined HTTP-based API is very cool.
The final two parts of the book provide detailed coverage of using Spring Data to work with ‘Big Data’ through the use of Apache Hadoop, Spring Batch, Spring Integration and GemFire. Although this content wasn’t relevant to my initial decision to buy the book the chapters are a complete bonus in my opinion, and upon reading them I was even more happy with my purchase. The content provided is obviously quite high-level (as Big Data is a huge topic, no pun intended :)), but has enough detail to get you up and running with some Hadoop Jobs and Hive and Pig etc, which is a great skill to add to your CV.
I chose this book over the only other real competition for Spring Data coverage, Petri Kainulainen’s Spring Data, purely because this book offered more content. Obviously the book under review has more pages, ~280 vs ~160, but more importantly it covers a greater amount of topics, and Petri’s book focuses primarily on Redis (for which I was already familiar with). My main motivation for buying a Spring Data book was to learn about the ‘tips and tricks’, and I think either book would have met this need, but the coverage of other NoSQL technologies in the book under review, and the bonus chapters on Big Data technologies swayed my final decision. Now that I’ve read the book I am very happy with the decision.
In summary: This book will be all you need to master Spring Data, from key concepts to advanced usage. You’ll learn all of the ‘tips and tricks’ along the way, and also become familiar with Spring Roo, the REST repo exporter and fundamental techniques within Spring Data’s ‘Big Data’ processing (Hadoop, Spring Batch/Integration etc). I would recommend the book to any Spring developer, even one like myself who is happy learning about Spring from the excellent Spring Source website This book is a little more ‘polished’ than the Spring Source docs, and also provides concepts in well-structured and bit-sized chunks of information.
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