Name: Spring Data
Price: 234.54 RON
Availability: OnlineOnly
Author: Mark Pollack
ISBN: 9781449323950

Spring Data

Mark Pollack

Oliver Gierke

Thomas Risberg

Jon Brisbin

Michael Hunger

en Limba Engleză Paperback – 27 noi 2012

Relational database technologies continue to be predominant in Java enterprise applications, but with newer technologies such as NoSQL databases and Hadoop available, RDBMS is no longer considered a "one size fits all" solution. This book shows you how to increase your options with Spring's data access framework.

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Cuprins

Foreword; Preface; Overview of the New Data Access Landscape; How to Read This Book; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Background; Chapter 1: The Spring Data Project; 1.1 NoSQL Data Access for Spring Developers; 1.2 General Themes; 1.3 The Domain; 1.4 The Sample Code; Chapter 2: Repositories: Convenient Data Access Layers; 2.1 Quick Start; 2.2 Defining Query Methods; 2.3 Defining Repositories; 2.4 IDE Integration; Chapter 3: Type-Safe Querying Using Querydsl; 3.1 Introduction to Querydsl; 3.2 Generating the Query Metamodel; 3.3 Integration with Spring Data Repositories; Relational Databases; Chapter 4: JPA Repositories; 4.1 The Sample Project; 4.2 The Traditional Approach; 4.3 Bootstrapping the Sample Code; 4.4 Using Spring Data Repositories; Chapter 5: Type-Safe JDBC Programming with Querydsl SQL; 5.1 The Sample Project and Setup; 5.2 The QueryDslJdbcTemplate; 5.3 Executing Queries; 5.4 Insert, Update, and Delete Operations; NoSQL; Chapter 6: MongoDB: A Document Store; 6.1 MongoDB in a Nutshell; 6.2 Setting Up the Infrastructure Using the Spring Namespace; 6.3 The Mapping Subsystem; 6.4 MongoTemplate; 6.5 Mongo Repositories; Chapter 7: Neo4j: A Graph Database; 7.1 Graph Databases; 7.2 Neo4j; 7.3 Spring Data Neo4j Overview; 7.4 Modeling the Domain as a Graph; 7.5 Persisting Domain Objects with Spring Data Neo4j; 7.6 Combining Graph and Repository Power; 7.7 Advanced Graph Use Cases in the Example Domain; 7.8 Transactions, Entity Life Cycle, and Fetch Strategies; 7.9 Advanced Mapping Mode; 7.10 Working with Neo4j Server; 7.11 Continuing From Here; Chapter 8: Redis: A Key/Value Store; 8.1 Redis in a Nutshell; 8.2 Connecting to Redis; 8.3 Object Conversion; 8.4 Object Mapping; 8.5 Atomic Counters; 8.6 Pub/Sub Functionality; 8.7 Using Spring's Cache Abstraction with Redis; Rapid Application Development; Chapter 9: Persistence Layers with Spring Roo; 9.1 A Brief Introduction to Roo; 9.2 Roo's Persistence Layers; 9.3 Quick Start; 9.4 A Spring Roo JPA Repository Example; 9.5 A Spring Roo MongoDB Repository Example; Chapter 10: REST Repository Exporter; 10.1 The Sample Project; Big Data; Chapter 11: Spring for Apache Hadoop; 11.1 Challenges Developing with Hadoop; 11.2 Hello World; 11.3 Hello World Revealed; 11.4 Hello World Using Spring for Apache Hadoop; 11.5 Scripting HDFS on the JVM; 11.6 Combining HDFS Scripting and Job Submission; 11.7 Job Scheduling; Chapter 12: Analyzing Data with Hadoop; 12.1 Using Hive; 12.2 Using Pig; 12.3 Using HBase; Chapter 13: Creating Big Data Pipelines with Spring Batch and Spring Integration; 13.1 Collecting and Loading Data into HDFS; 13.2 Hadoop Workflows; 13.3 Exporting Data from HDFS; 13.4 Collecting and Loading Data into Splunk; Data Grids; Chapter 14: GemFire: A Distributed Data Grid; 14.1 GemFire in a Nutshell; 14.2 Caches and Regions; 14.3 How to Get GemFire; 14.4 Configuring GemFire with the Spring XML Namespace; 14.5 Data Access with GemfireTemplate; 14.6 Repository Usage; 14.7 Continuous Query Support; Bibliography; Colophon;