使用JobControl管理mapreduce多job依赖

当我们在处理mr问题的时候，有时候需求过于复杂，通过一个简单的mr无法达到目的，我们该怎么办呢？

答案是采取JobControl，直接上代码。

/**
	 * job2 依赖于 job1
	 * @param job1
	 * @param job2
	 * @param chainName
	 * @return
	 * @throws IOException
	 */
	public static int handleJobChain(Job job1 ,Job job2, String chainName) throws IOException{
		ControlledJob controlledJob1 = new ControlledJob(job1.getConfiguration());
		controlledJob1.setJob(job1);
		
		ControlledJob controlledJob2 = new ControlledJob(job2.getConfiguration());
		controlledJob2.setJob(job2);
		controlledJob2.addDependingJob(controlledJob1);
		
		JobControl jc = new JobControl(chainName);
		jc.addJob(controlledJob1);
		jc.addJob(controlledJob2);
		Thread jcThread = new Thread(jc);
		jcThread.start();
		while(true){
			if(jc.allFinished()){
				System.out.println(jc.getSuccessfulJobList());
				jc.stop();
				return 0;
			}
			if(jc.getFailedJobList().size() > 0){
				System.out.println(jc.getFailedJobList());
				jc.stop();
				return 1;
			}
		}
	}

 

要注意的地方就是hadoop的JobControl类实现了线程Runnable接口。我们需要实例化一个线程来让它启动。直接调用JobControl的run()方法，线程将无法结束。