Conductor 3.2.0 客户端开发记录

不使用Conductor Spring

和之前版本差不多，但使用TaskRunnerConfigurer 替代WorkflowTaskCoordinator

import java.util.ArrayList;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;

import com.netflix.conductor.client.automator.TaskRunnerConfigurer;
import com.netflix.conductor.client.http.TaskClient;
import com.netflix.conductor.client.worker.Worker;
import com.netflix.conductor.common.metadata.tasks.Task;
import com.netflix.conductor.common.metadata.tasks.TaskResult;

/**
 * The Class Application.
 * 
 * Class to configure the WorkFlow example.
 * 
 * @author Carlos Salas
 * @since 1.0
 * @version 1.0
 */

@SpringBootApplication
public class Application implements CommandLineRunner { 

    public static void main(String[] args) {

        SpringApplication.run(Application.class, args);
    }

    @Override
	public void run(String... args) throws Exception {

        TaskClient taskClient = new TaskClient();
        taskClient.setRootURI("http://192.168.157.140:8080/api/");        //Point this to the server API

        int threadCount = 2;            //number of threads used to execute workers.  To avoid starvation, should be same or more than number of workers

        Worker worker1 = new LeaderRatifyWorker("leaderRatify");
        Worker worker2 = new ManagerRatifyWorker("managerRatify");
        
        ArrayList<Worker> works=new ArrayList<Worker>();
        works.add(worker2);
        works.add(worker1);
        
        // Create TaskRunnerConfigurer
        TaskRunnerConfigurer configurer = new TaskRunnerConfigurer.Builder(taskClient, works)
            .withThreadCount(threadCount)
            .build();

        // Start the polling and execution of tasks
        configurer.init();
    }
    
  
}
           

使用conductor-client-spring

POM.XML内容如下：

<dependency>
			<groupId>com.netflix.conductor</groupId>
			<artifactId>conductor-common</artifactId>
			<version>3.2.0</version>
		</dependency>
		<dependency>
			<groupId>com.netflix.conductor</groupId>
			<artifactId>conductor-client</artifactId>
			<version>3.2.0</version>
		</dependency>



		<!-- https://mvnrepository.com/artifact/com.netflix.conductor/conductor-client-spring -->
		<dependency>
			<groupId>com.netflix.conductor</groupId>
			<artifactId>conductor-client-spring</artifactId>
			<version>3.2.0</version>
		</dependency>
           

spring主函数不用写如何代码，需要修改worker，增加annotation

public class ManagerRatifyWorker implements Worker {
    private String taskDefName="managerRatify";
    
    
    
	 public ManagerRatifyWorker() { 
	    }
	 
           

配置application.properties，注意api后面一定要加"/"

conductor.worker.pollingInterval=2
conductor.client.rootURI=http://192.168.157.140:8080/api/
conductor.client.threadCount=3
           

最后增加启动测试一个工作流的主代码如下：

@SpringBootApplication
public class SpringApplicationMain implements CommandLineRunner {

 
	public static void main(String[] args) {

		SpringApplication.run(SpringApplicationMain.class, args);
	}

    @Autowired
    TaskRunnerConfigurer taskRunnerConfigurer; 
	@Override
	public void run(String... args) throws Exception {
		// TODO Auto-generated method stub
		// ClientConfig config=new ClientConfig();

		// 没有找到伪同步模式获取返回
		WorkflowClient workflowClient = new WorkflowClient();
		workflowClient.setRootURI("http://192.168.157.140:8080/api/");
		StartWorkflowRequest request = new StartWorkflowRequest().withName("Leave").withVersion(3);
		String workflowId = workflowClient.startWorkflow(request);
		Thread.sleep(1000);
 
		System.err.println(workflowId);
		Workflow workflow_json = workflowClient.getWorkflow(workflowId, false);
		while (workflow_json != null) {
			if (workflow_json.getStatus().equals(WorkflowStatus.RUNNING)) {
				Thread.sleep(10);
				workflow_json = workflowClient.getWorkflow(workflowId, false);
			} else {
				break;
			}
		}
		System.err.println("workflow_json:" + workflow_json.getStatus().name() + workflow_json.getOutput().toString());

		System.exit(0);
	}