Spring 生态系统通过集成多种大数据技术栈，为企业级应用提供了强大的支持

如何使用 Spring Data 访问 Cassandra 数据库

1. 添加 Maven 或 Gradle 依赖

为了在项目中使用 Spring Data 对 Cassandra 进行数据访问，首先需要添加相应的依赖项。对于 Maven 用户来说，在 pom.xml 文件中加入如下依赖：

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-cassandra</artifactId>
</dependency>

而对于采用 Gradle 构建工具的开发者，则应在 build.gradle 中声明类似的依赖关系。

2. 配置 Cassandra 数据源

接下来要做的就是设置好应用程序与 Cassandra 实例之间的连接参数。这通常是在 application.properties 或者 application.yml 文件里完成的。下面是一个简单的例子，展示了如何指定主机名、端口以及其他必要的属性。

spring:
  data:
    cassandra:
      contact-points: localhost
      port: 9042
      keyspace-name: testkeyspace
      schema-action: create_if_not_exists

3. 创建实体类

定义映射到表结构上的 Java 类型非常重要。这些 POJO (Plain Old Java Object) 将会用来表示存储于 Cassandra 表中的记录。这里给出一个名为 User 的简单示例实体类:

@Table("users")
public class User {
    
    @PrimaryKeyColumn(name="id", ordinal=0, type=PrimaryKeyType.PARTITIONED)
    private UUID id;
    
    @Column("name")
    private String name;

    // Getters and Setters...
}

请注意，@Table 和其他注解来自 org.springframework.data.cassandra.core.mapping 包下的 API。

4. 定义 Repository 接口

借助 Spring Data 提供的强大功能，只需编写少量代码就能轻松获取 CRUD 操作能力。具体做法是继承自 CrudRepository<T,ID> 接口来构建自己的仓库接口。例如，针对上面提到过的 User 实体对象，可以这样设计对应的 repository :

public interface UserRepository extends CrudRepository<User,UUID> {

    List<User> findByName(String name);
}

此时已经具备了基本增删改查的能力，并且还支持按名字查询特定用户的列表方法。

5. 编写 Service 层逻辑和服务调用方 Controller

最后一步就是在业务处理单元即 service layer 内部利用上述创建好的 repositories 来执行实际的任务；与此同时也要记得开发 RESTful web services endpoint(s)，以便外部客户端可以通过 HTTP 请求触发内部的服务流程。

@Service
public class UserServiceImpl implements UserService{
  
  final UserRepository userRepository;

  public UserServiceImpl(UserRepository userRepository){
     this.userRepository=userRepository; 
  }

  @Override
  public Iterable<User> findAll(){
       return userRepository.findAll();
  }
}

@RestController
@RequestMapping("/api/users")
public class UserController {

  final UserService userService;

  public UserController(UserService userService){
     this.userService=userService; 
  }

  @GetMapping("")
  public ResponseEntity<List<User>> getAllUsers() {
        List<User> users = StreamSupport.stream(
                Spliterators.spliteratorUnknownSize(userService.findAll().iterator(),Spliterator.NONNULL),
                false).collect(Collectors.toList());
        
         if(users.isEmpty()){
             return new ResponseEntity<>(HttpStatus.NO_CONTENT); //You many decide to return NOT_FOUND
          }else{   
              return new ResponseEntity<>(users, HttpStatus.OK);
           }
   }
}

通过这种方式就可以充分利用 Spring Framework 生态圈的优势，简化对 NoSQL 存储系统的编程工作量的同时提高生产效率。

Spring 在企业 Java 开发中的领导地位

BigData 支持的优势

Spring 生态系统通过集成多种大数据技术栈，为企业级应用提供了强大的支持。借助于 Spring Batch 和 Spring Cloud Data Flow 等项目，开发者能够轻松处理大规模数据集并实现高效的数据管道构建。

NoSQL 数据库兼容性

随着非关系型数据库（NoSQL）的发展，Spring Data 提供了对各种流行 NoSQL 解决方案的支持，包括 MongoDB、Cassandra 及 Redis 等。这使得应用程序可以灵活选择最适合其需求的数据模型和技术栈，而无需担心底层复杂度。值得注意的是，“NoSQL”一词最早由 Carlo Strozzi 用于描述一种轻量级开源的关系型数据库，在此之后逐渐演变为指代一系列非关系型数据库解决方案。

云计算迁移能力

为了适应现代 IT 架构向云端转移的趋势，Spring Boot 和 Spring Cloud 组件共同作用下实现了微服务架构的最佳实践。这些工具简化了分布式系统的部署过程，并增强了跨多个云平台的服务发现、配置管理以及负载均衡等功能。此外，Spring Cloud 提供了一系列针对特定公有云供应商优化过的模块，从而提高了应用程序在不同环境间无缝切换的可能性。

// 示例：使用 Spring Data 进行 MongoDB 操作
@Autowired
private MongoTemplate mongoTemplate;

public List<Document> findAllDocuments() {
    Query query = new Query();
    return mongoTemplate.find(query, Document.class);
}

It’s JavaOne time again and this year you’ll find sessions on how Spring works with Java SE to address Big Data, NoSQL, and enterprise integration challenges. We’ve always worked hard to ensure that Spring remains at the forefront of enterprise Java by providing timely support for emerging trends and technologies. The numbers suggest that our users appreciate this. A recent report from Evans Data (“Spring Source Usage Study,” Evans Data Corporation, September 2011) shows:

Spring is the framework of choice among expert Java developers. More than two thirds of Java developers are either using Spring today or planning to do so
Spring usage continues to grow. More than half of existing Spring users expect to grow or significantly grow their use of Spring.
Spring is delivering results. 70% of Spring users indicate at least a 50% productivity gain by using Spring and 73% indicate at least a 50% time reduction to deliver a completed project.
Spring users are at the forefront of enterprise Java. Spring users are more cloud ready, and Spring adopters are more likely to have already deployed applications to the cloud.

Spring has always offered deployment flexibility. In the early days this meant a choice of application servers, but now this extends to choice of cloud platforms including our own Cloud Foundry. Spring has always provided strong data access support. In the early days this meant a choice of approaches for accessing a relational database, today this extends to a range of Big Data and NoSQL stores, data processing, and in-memory data grid capabilities. Spring has always valued developer productivity and provided first class support for writing server-side web applications. Today this extends to meet the modern requirements of HATEOAS-based REST APIs.

These are real and pressing concerns within the enterprise today. Cloud is everywhere, and now Big Data is firmly on the enterprise project radar too, creating a range of new requirements:

Big Data: the need to store and get analytics from gigabytes, terabytes or petabytes of unstructured or semi-structured data
Fast Data: the increasing need for low latency interactions with large sets of data, often driven by today’s mobile and social apps
Flexible Data: the need to adapt data access to the most appropriate model for each application
Cloud Delivery: the growing demand to access data as a service, provisioned on the cloud of your choice.

The latest Harvard Business Review survey indicates that 85% of organizations have Big Data initiatives planned or in progress. Application developers need to deliver capable, high quality solutions that integrate with this new world and can be deployed anywhere, on or off premise. NoSQL and NewSQL are also being used to address a wide range of use cases including:

Managing large data streams of non-transactional data (logs, clickstreams)
Fraud detection
Timelines (a la Twitter)
Synching offline and online data
Online gaming
Document, catalog and content management
Archiving - storing a large continual stream of data that is still accessible on-line
Embedded systems (small footprint databases in devices)

See this High Scalability blog entry for more details.

451 Research’s recent survey data highlights the changing shape of the data landscape. One size no longer fits all.

Enterprise developers can start taking advantage of these new technologies today with Spring and the familiar Spring programming model. Spring offers:

Big Data processing via Spring Data’s support for Apache Hadoop and HBase, as well as Spring Batch and Spring Integration
In-Memory data grid support via Spring Data GemFire
Support for NoSQL key-value stores with Spring Data Redis
Support for NoSQL document stores with Spring Data MongoDB
Support for NoSQL graph databases with Spring Data Neo4j
Support for NewSQL databases with SQLFire
And of course traditional relational databases, such as MySQL, Postgres, Oracle, and DB2, still have their place and can be accessed via Spring JPA and Spring JDBC Extensions, and made accessible via Spring Data REST

The thriving open source community around NoSQL, together with Spring, makes developing for the next generation of data stores and data processing more productive today. We don’t provide a single Java API for all persistence stores; this is not realistic given the fundamental differences between them. But we do provide a common and familiar programming model based on the concepts of templates and, where available, repositories. See Tobias Trelle’s recent InfoQ article for more details.

All in all, JavaOne 2012 is sure to be an action packed week, full of great Java tech talks, keynotes, and sessions including coverage of our own Big Data, NoSQL, and integration initiatives. Developers who want to get hands on with these technologies now also won’t want to miss SpringOne 2GX in Washington DC October 15-18, 2012. We have a packed technical agenda covering all aspects of modern enterprise application development.

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这又是一次JavaOne，今年您将看到关于Spring如何与Java SE一起工作以解决大数据、NoSQL和企业集成挑战的会话。我们一直在努力确保Spring始终处于企业Java的前沿，为新兴趋势和技术提供及时的支持。数字表明我们的用户对此表示赞赏。埃文斯数据公司（Evans Data，2011年9月，埃文斯数据公司，Spring Source Usage Study）最近的一份报告显示：
Spring是专家级Java开发人员选择的框架。超过三分之二的Java开发人员要么现在使用Spring，要么计划这样做
春季使用量继续增长。超过一半的现有Spring用户希望增加或显著增加对Spring的使用。
春天带来了成果。70%的Spring用户表示使用Spring至少可以提高50%的生产率，73%的用户表示交付完成的项目至少可以减少50%的时间。
Spring用户是企业Java的前沿。Spring用户更愿意使用云，Spring采用者更有可能已经在云上部署了应用程序。
Spring始终提供部署灵活性。在早期，这意味着可以选择应用服务器，但现在这扩展到云平台的选择，包括我们自己的云铸造厂。Spring一直提供强大的数据访问支持。在早期，这意味着可以选择访问关系数据库的方法，今天，这扩展到一系列大数据和NoSQL存储、数据处理和内存中的数据网格功能。Spring一直重视开发人员的生产力，并为编写服务器端web应用程序提供一流的支持。今天，它扩展到满足基于HATEOAS的restapi的现代需求。