spring cloud data flow demo

一．环境准备

a)Java1.8及以上
b)关系型数据库用来存储stream task和程序的状态（默认使用内嵌的H2）
c)Redis
d)Message broker （rabbitMq，kafka）
e)Maven
f)为了方便spring组件的使用建议使用（sts），以下操作基于sts

二．Data Flow Server

Spring Cloud Data Flow 支持多种运行环境（Cloud Foundry 、Apache YARN 、Kubernetes 、Apache Mesos、Local Server for development ）本例中使用spring 的 LocalServer.
    1.新建一个spring start project 
    2.输入项目信息
    3.选择spring版本及项目依赖
        Boot version : 1.4.4
        项目依赖选择 Local Data Flow server
        选下一步等待maven包及项目构建完成
    4.在 spring boot main class上添加@EnableDataFlowServer 注解

        @EnableDataFlowServer
        @SpringBootApplication
        public class DfServerApplication {

            public static void main(String[] args) {
                SpringApplication.run(DfServerApplication.class, args);
            }
        }

    5.现在Data Flow服务器就搭建好了 （需要redis的支持）
    6.然后到项目路径下边 执行 mvn spring-boot:run 服务器以端口9393启动

三．Data Flow shell

a)项目构建与Data Flow Server一致 
b)第三步选择依赖的时候选择 data flow shell
c) 修改代码添加@EnableDataFlowShell注解

    @EnableDataFlowShell
    @SpringBootApplication
    public class DfShellApplication {

        public static void main(String[] args) {
            SpringApplication.run(DfShellApplication.class, args);
        }
    }

d) 项目路径下执行 mvn spring-boot:run
dataflow config server http://localhost:9393
若server 在本地 且 已经启动则会直接连接。

四．创建streams

a)创建source

    i.项目创建与server一致
    ii.第三步选择依赖的时候选择 stream rabbit(若你使用的是kafka 择选择kafka)
    iii.修改代码

        @EnableBinding(Source.class)
        @SpringBootApplication
        public class LoggingSourceApplication {
            @Bean
            @InboundChannelAdapter(
              value = Source.OUTPUT, 
              poller = @Poller(fixedDelay = "10000", maxMessagesPerPoll =         "1")
            )
            public MessageSource timeMessageSource() {
                System.out.println(new Date() +"======================logging-source========================== execued");
                return () -> MessageBuilder.withPayload(new Date().getTime()).build();
            }

            public static void main(String[] args) {
                SpringApplication.run(LoggingSourceApplication.class, args);
            }
        }

    iv.到项目路径 执行mvn clean install

b). 创建processor

    i.所有步骤跟source一样
    ii.代码修改

            @EnableBinding(Processor.class)
            @SpringBootApplication
            public class LoggingProcessorApplication {

                @Transformer(inputChannel = Processor.INPUT, 
                          outputChannel = Processor.OUTPUT)
                        public Object transform(Long timestamp) {

                            DateFormat dateFormat = new                                             SimpleDateFormat("yyyy/MM/dd hh:mm:yy");
                            String date = dateFormat.format(timestamp);
                            System.out.println(date +                           "------------------------------logging-proccessor-------------------------------  executed");
                            return date;
                        }
                public static void main(String[] args) {
                    SpringApplication.run(LoggingProcessorApplication.class, args);
                }
            }

c). 创建sink

i.所有步骤跟source创建一样
ii.代码修改

        @EnableBinding(Sink.class)
        @SpringBootApplication
        public class LoggingSinkApplication {

            @MessageEndpoint
            public static class LoggingMessageEndpoint {
                @ServiceActivator(inputChannel = Sink.INPUT)
                public void logIncomingMessages(@Payload String msg,                    @Headers Map headers) {
                    System.out.println("logging-sink**************"+                        msg);
                    headers.entrySet().forEach(e ->                                 System.out.println(e.getKey() + '=' + e.getValue()));
                }
            }
            @StreamListener(Sink.INPUT)
            public void loggerSink(String date) {
                System.out.println("logging-sink Received: " + date);
            }
            public static void main(String[] args) {
                SpringApplication.run(LoggingSinkApplication.class, args);
            }
        }

五．注册Stream app

执行 app register --name “demo” --type type --uri maven://:[:[:]]:
注册完毕后 可执行 app list 查看注册列表

六．创建stream并部署

1.创建stream

执行stream create --name “name”  --definiation ‘a | b | c’
然后执行 stream list 就可以看到刚才定义的stream

2.部署stream

执行命令 stream deploy --name ‘name’

七．创建Task

a)项目创建步骤同source
b)第三步选择依赖时选择 Cloud Task
c).修改相关代码

@EnableTask
@EnableBatchProcessing
@SpringBootApplication
public class MyTaskApplication {

    public static void main(String[] args) {
        SpringApplication.run(MyTaskApplication.class, args);
    }
}
创建jobConfiguration
@Configuration
public class JobConfiguration {
    private static Log logger
    = LogFactory.getLog(JobConfiguration.class);

  @Autowired
  public JobBuilderFactory jobBuilderFactory;

  @Autowired
  public StepBuilderFactory stepBuilderFactory;

  @Bean
  public Job job() {
      return jobBuilderFactory.get("job")
        .start(stepBuilderFactory.get("jobStep1")
        .tasklet(new Tasklet() {

            @Override
            public RepeatStatus execute(StepContribution contribution, 
              ChunkContext chunkContext) throws Exception {

              logger.info("my Job was run");
              return RepeatStatus.FINISHED;
            }
      }).build()).build();
  }
}

d).到项目路径下执行 mvn spring-boot:run

八．部署task

a)注册app

    app register --name my-job --type task --uri maven://:[:[:]]:
    执行app list可以看到注册的task程序

b).创建task

    task create myjob --difination ‘appname’
    task list 可以看到刚刚创建的 task

c).运行task

    task launch ‘taskname’
    然后执行 task execution list 就可以看到执行过的task

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spring cloud data flow demo