Spring Data: Modern Data Access for Enterprise Java

This book is the authoritative introductory guide to the Spring Data project. In the Java enterprise world of the time, relational databases reigned supreme, but with the rise of NoSQL and new data technologies such as Hadoop, RDBMS was no longer a one-size-fits-all solution. Written jointly by the Spring Data project lead and the leads of its core modules, the book explains how Spring Data offers a unified programming model that lets developers efficiently connect to Redis, HBase, MongoDB, Neo4j, GemFire, and other data stores. The book is divided into several parts: background, relational databases, NoSQL, rapid application development, and big data. Part I introduces the origins of the Spring Data project, the classification of NoSQL stores, and how to import the sample projects, and focuses on the Repository abstraction: deriving queries from method names, defining query methods, pagination and sorting, manually implementing repository methods, and type-safe queries with Querydsl. Part II discusses the differences between Spring Data JPA repositories and traditional JPA approaches, as well as type-safe JDBC programming with Querydsl SQL. Part III goes deep into MongoDB document stores and Neo4j graph databases, covering the mapping subsystem, MongoTemplate, graph repository operations, collaborative filtering recommendations, and other advanced use cases, and introduces Redis key-value storage, atomic counters, publish-subscribe, and the caching abstraction. Part IV introduces rapid persistence-layer development with Spring Roo and exporting JPA entities as RESTful services with the REST Repository Exporter. Part V covers Spring for Apache Hadoop, demonstrating HDFS scripting, MapReduce job scheduling, analyzing Apache logs with Hive and Pig, and building data pipelines with Spring Batch and Spring Integration, finally exporting data to JDBC, MongoDB, and Splunk. The book is threaded with multiple runnable sample projects whose code can be imported into an IDE and debugged directly. One caveat: the book was written in 2012 and covers the Spring Data versions and APIs of that time; some class names and configuration approaches (such as XML namespace configuration) now differ from current versions. It is suitable as a reference for understanding Spring Data’s design philosophy rather than as an API manual for the latest version.