问题
I need to chain two MapReduce jobs. I used JobControl to set job2 as dependent of job1. It works, output files are created!! But it doesn't stop! In the shell it remains in this state:
12/09/11 19:06:24 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
12/09/11 19:06:25 INFO input.FileInputFormat: Total input paths to process : 1
12/09/11 19:06:25 INFO util.NativeCodeLoader: Loaded the native-hadoop library
12/09/11 19:06:25 WARN snappy.LoadSnappy: Snappy native library not loaded
12/09/11 19:07:00 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
12/09/11 19:07:00 INFO input.FileInputFormat: Total input paths to process : 1
How can I stop it? This is my main.
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Configuration conf2 = new Configuration();
Job job1 = new Job(conf, "canzoni");
job1.setJarByClass(CanzoniOrdinate.class);
job1.setMapperClass(CanzoniMapper.class);
job1.setReducerClass(CanzoniReducer.class);
job1.setOutputKeyClass(Text.class);
job1.setOutputValueClass(IntWritable.class);
ControlledJob cJob1 = new ControlledJob(conf);
cJob1.setJob(job1);
FileInputFormat.addInputPath(job1, new Path(args[0]));
FileOutputFormat.setOutputPath(job1, new Path("/user/hduser/tmp"));
Job job2 = new Job(conf2, "songsort");
job2.setJarByClass(CanzoniOrdinate.class);
job2.setMapperClass(CanzoniSorterMapper.class);
job2.setSortComparatorClass(ReverseOrder.class);
job2.setInputFormatClass(KeyValueTextInputFormat.class);
job2.setReducerClass(CanzoniSorterReducer.class);
job2.setMapOutputKeyClass(IntWritable.class);
job2.setMapOutputValueClass(Text.class);
job2.setOutputKeyClass(Text.class);
job2.setOutputValueClass(IntWritable.class);
ControlledJob cJob2 = new ControlledJob(conf2);
cJob2.setJob(job2);
FileInputFormat.addInputPath(job2, new Path("/user/hduser/tmp/part*"));
FileOutputFormat.setOutputPath(job2, new Path(args[1]));
JobControl jobctrl = new JobControl("jobctrl");
jobctrl.addJob(cJob1);
jobctrl.addJob(cJob2);
cJob2.addDependingJob(cJob1);
jobctrl.run();
////////////////
// NEW CODE ///
//////////////
// delete jobctrl.run();
Thread t = new Thread(jobctrl);
t.start();
String oldStatusJ1 = null;
String oldStatusJ2 = null;
while (!jobctrl.allFinished()) {
String status =cJob1.toString();
String status2 =cJob2.toString();
if (!status.equals(oldStatusJ1)) {
System.out.println(status);
oldStatusJ1 = status;
}
if (!status2.equals(oldStatusJ2)) {
System.out.println(status2);
oldStatusJ2 = status2;
}
}
System.exit(0);
} }
回答1:
I essentially did what Pietro alluded to above.
public class JobRunner implements Runnable {
private JobControl control;
public JobRunner(JobControl _control) {
this.control = _control;
}
public void run() {
this.control.run();
}
}
and in my map/reduce class I have:
public void handleRun(JobControl control) throws InterruptedException {
JobRunner runner = new JobRunner(control);
Thread t = new Thread(runner);
t.start();
while (!control.allFinished()) {
System.out.println("Still running...");
Thread.sleep(5000);
}
}
in which I just pass the jobControl object.
回答2:
The JobControl object itself is Runnable, so you can just use it like this:
new Thread(myJobControlInstance).start()
回答3:
Just a tweak to the code snippet what sinemetu1 had shared..
You can drop call to the JobRunner as JobControl by itself implements Runnable
Thread thread = new Thread(jobControl);
thread.start();
while (!jobControl.allFinished()) {
System.out.println("Still running...");
Thread.sleep(5000);
}
I also stumbled upon this link where the user confirms that JobControl can be run ONLY with new thread. https://www.mail-archive.com/common-user@hadoop.apache.org/msg00556.html
回答4:
try this:
Thread jcThread = new Thread(jobControl);
jcThread.start();
System.out.println("循环判断jobControl运行状态 >>>>>>>>>>>>>>>>");
while (true) {
if (jobControl.allFinished()) {
System.out.println("====>> jobControl.allFinished=" + jobControl.getSuccessfulJobList());
jobControl.stop();
// 如果不加 break 或者 return,程序会一直循环
break;
}
if (jobControl.getFailedJobList().size() > 0) {
succ = 0;
System.out.println("====>> jobControl.getFailedJobList=" + jobControl.getFailedJobList());
jobControl.stop();
// 如果不加 break 或者 return,程序会一直循环
break;
}
}
来源:https://stackoverflow.com/questions/12374928/hadoop-mapreduce-chain-jobs-jobcontrol-doesnt-stop