Spring Data : 企业级Java的现代数据访问技术

Foreword

Preface

Part I. Background

1. The Spring Data Project

NoSQL Data Access for Spring Developers

General Themes

The Domain

The Sample Code

Importing the Source Code into Your IDE

2. Repositories： Convenient Data Access Layers

Quick Start

Defining Query Methods

Query Lookup Strategies

Query Derivation

Pagination and Sorting

Defining Repositories

Fine-Tuning Repository Interfaces

Manually Implementing Repository Methods

IDE Integration

IntelliJ IDEA

3. Type-Safe Querying Using Querydsl

Introduction to Querydsl

Generating the Query Metamodel

Build System Integration

Supported Annotation Processors

Querying Stores Using Querydsl

Integration with Spring Data Repositories

Executing Predicates

Manually Implementing Repositories

Part II. Relational Databases

4. JPA Repositories

The Sample Project

The Traditional Approach

Bootstrapping the Sample Code

Using Spring Data Repositories

Transactionality

Repository Querydsl Integration

S. Type-SafeJDBC Programming with Querydsl SQL

The Sample Project and Setup

The HyperSQL Database

The SQL Module of Querydsl

Build System Integration

The Database Schema

The Domain Implementation of the Sample Project

The QueryDslJdbcTemplate

Executing Queries

The Beginning of the Repository Implementation

Querying for a Single Object

The OneToManyResultSetExtractor Abstract Class

The CustomerListExtractor Implementation

The Implementations for the RowMappers

Querying for a List of Objects

Insert， Update， and Delete Operations

Inserting with the SQLInsertClause

Updating with the SQLUpdateClause

Deleting Rows with the SQLDeleteClause

Part III. NoSQL

6. MongoDB：A Document Store

MongoDB in a Nutshell

Setting Up MongoDB

Using the MongoDB Shell

The MongoDB Java Driver

Setting Up the Infrastructure Using the Spring Namespace

The Mapping Subsystem

The Domain Model

Setting Up the Mapping Infrastructure

Indexing

Customizing Conversion

MongoTemplate

Mongo Repositories

Infrastructure Setup

Repositories in Detail

Mongo Querydsl Integration

7. Neo4j： A Graph Database

Graph Databases

Neo4j

Spring Data Neo4j Overview

Modeling the Domain as a Graph

Persisting Domain Objects with Spring Data Neo4j

Neo4jTemplate

Combining Graph and Repository Power

Basic Graph Repository Operations

Derived and Annotated Finder Methods

Advanced Graph Use Cases in the Example Domain

Multiple Roles for a Single Node

Product Categories and Tags as Examples for In-Graph Indexes

Leverage Similar Interests （Collaborative Filtering）

Recommendations

Transactions， Entity Life Cycle， and Fetch Strategies

Advanced Mapping Mode

Working with Neo4j Server

Continuing From Here

8. Redis： A Key/Value Store

Redis in a Nutshell

Setting Up Redis

Using the Redis Shell

Connecting to Redis

Object Conversion

Object Mapping

Atomic Counters

Pub/Sub Functionality

Listening and Responding to Messages

Using Spring's Cache Abstraction with Redis

PartIV. Rapid Application Development

9. Persistence Layers with Spring Roo

A Brief Introduction to Roo

Roo's Persistence Layers

Quick Start

Using Roo from the Command Line

Using Roo with Spring Tool Suite

A Spring Roo JPA Repository Example

Creating the Project

Setting Up JPA Persistence

Creating the Entities

Defining the Repositories

Creating the Web Layer

Running the Example

A Spring Roo MongoDB Repository Example

Creating the Project

Setting Up MongoDB Persistence

Creating the Entities

Defining the Repositories

Creating the Web Layer

Running the Example

10. REST Repository Exporter

The Sample Project

Interacting with the REST Exporter

Accessing Products

Accessing Customers

Accessing Orders

Part V. Big Data

11. Spring forApache Hadoop

Challenges Developing with Hadoop

Hello World

Hello World Revealed

Hello World Using Spring for Apache Hadoop

Scripting HDFS on the JVM

Combining HDFS Scripting and Job Submission

Job Scheduling

Scheduling MapReduce Jobs with a TaskScheduler

Scheduling MapReduce Jobs with Quartz

12. Analyzing Datawith Hadoop

Using Hive

Hello World

Running a Hive Server

Using the Hive Thrift Client

Using the Hive JDBC Client

Apache Logfile Analysis Using Hive

Using Pig

Hello World

Running a PigServer

Controlling Runtime Script Execution

Calling Pig Scripts Inside Spring Integration Data Pipelines

Apache Logfile Analysis Using Pig

Using HBase

Hello World

Using the HBase Java Client

13. Creating Big Data Pipelines with Spring Batch and Spring Integration

Collecting and Loading Data into HDFS

An Introduction to Spring Integration

Copying Logfiles

Event Streams

Event Forwarding

Management

An Introduction to Spring Batch

Processing and Loading Data from a Database

Hadoop Workflows

Spring Batch Support for Hadoop

Wordcount as a Spring Batch Application

Hive and Pig Steps

Exporting Data from HDFS

From HDFS to JDBC

From HDFS to MongoDB

Collecting and Loading Data into Splunk

Part VI. Data Grids

14. GemFire： A Distributed Data Grid

GemFire in a Nutshell

Caches and Regions

How to Get GemFire

Configuring GemFire with the Spring XML Namespace

Cache Configuration

Region Configuration

Cache Client Configuration

Cache Server Configuration

WAN Configuration

Disk Store Configuration

Data Access with GemfireTemplate

Repository Usage

POJO Mapping

Creating a Repository

PDX Serialization

Continuous Query Support

Bibliography

Index

在使用关系型数据库搭建Java企业应用时，你可以选择多种数据访问框架。但是在处理大数据的时候呢？《企业级Java的现代数据访问技术：Spring Data（影印版）》这本包含丰富实践的指南将为你展示SpringData如何使得搭建基于诸如NoSQL和Hadoop这样一些新型数据访问技术的应用变得更加简单。
　　《企业级Java的现代数据访问技术：Spring Data（影印版）》通过多个示例项目，你将了解到SpringData如何提供了一个兼容NoSQL特有特性和功能的编程模型，以及它如何帮助你开发基于诸如数据分析、事件流处理和工作流之类用例的Hadoop应用。你也将找到那些SpringData添加到Spring现有JPA和JDBC中的特性，它们用来实现基于RDBMS的数据访问层。