是否有可能执行独立的 map reduce 作业(不在 reducer 输出的链接中
- 成为映射器的输入。
- 可以一个接一个地执行。
最佳答案
在你的驱动代码中调用两个方法runfirstjob,runsecondjob.就像这样。这只是一个提示,根据你的需要做修改
public class ExerciseDriver {
static Configuration conf;
public static void main(String[] args) throws Exception {
ExerciseDriver ED = new ExerciseDriver();
conf = new Configuration();
FileSystem fs = FileSystem.get(conf);
if(args.length < 4) {
System.out.println("Too few arguments. Arguments should be: <hdfs input folder> <hdfs output folder> <N configurable Integer Value>");
System.exit(0);
}
String pathin1stmr = args[0];
String pathout1stmr = args[1];
String pathin2ndmr = args[2];
String pathout2ndmr = args[3];
ED.runFirstJob(pathin1stmr, pathout1stmr);
ED.runSecondJob(pathin2ndmr, pathout2ndmr);
}
public int runFirstJob(String pathin, String pathout)
throws Exception {
Job job = new Job(conf);
job.setJarByClass(ExerciseDriver.class);
job.setMapperClass(ExerciseMapper1.class);
job.setCombinerClass(ExerciseCombiner.class);
job.setReducerClass(ExerciseReducer1.class);
job.setInputFormatClass(ParagrapghInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(pathin));
FileOutputFormat.setOutputPath(job, new Path(pathout));
job.submit();
job.getMaxMapAttempts();
/*
JobContextImpl jc = new JobContextImpl();
TaskReport[] maps = jobclient.getMapTaskReports(job.getJobID());
*/
boolean success = job.waitForCompletion(true);
return success ? 0 : -1;
}
public int runSecondJob(String pathin, String pathout) throws Exception {
Job job = new Job(conf);
job.setJarByClass(ExerciseDriver.class);
job.setMapperClass(ExerciseMapper2.class);
job.setReducerClass(ExerciseReducer2.class);
job.setInputFormatClass(KeyValueTextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
FileInputFormat.addInputPath(job,new Path(pathin));
FileOutputFormat.setOutputPath(job, new Path(pathout));
boolean success = job.waitForCompletion(true);
return success ? 0 : -1;
}
}
关于hadoop - 独立的 map reduce 作业一个接一个地执行,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/29507243/