在 Apache Hadoop 中仅使用 job.waitForCompletion(true) 方法和通过 ToolRunner.run(new MyClass(), args) 启动 map reduce 作业有什么区别?
我有一个 MapReduce 作业通过以下两种方式执行:
首先如下:
public class MaxTemperature extends Configured implements Tool {
public static void main(String[] args) throws Exception {
int exitCode = ToolRunner.run(new MaxTemperature(), args);
System.exit(exitCode);
}
@Override
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: MaxTemperature <input path> <output path>");
System.exit(-1);
}
System.out.println("Starting job");
Job job = new Job();
job.setJarByClass(MaxTemperature.class);
job.setJobName("Max temperature");
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.setMapperClass(MaxTemperatureMapper.class);
job.setReducerClass(MaxTemperatureReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
int returnValue = job.waitForCompletion(true) ? 0:1;
if(job.isSuccessful()) {
System.out.println("Job was successful");
} else if(!job.isSuccessful()) {
System.out.println("Job was not successful");
}
return returnValue;
}
}
第二个是:
public class MaxTemperature{
public static void main(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: MaxTemperature <input path> <output path>");
System.exit(-1);
}
System.out.println("Starting job");
Job job = new Job();
job.setJarByClass(MaxTemperature.class);
job.setJobName("Max temperature");
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.setMapperClass(MaxTemperatureMapper.class);
job.setReducerClass(MaxTemperatureReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
int returnValue = job.waitForCompletion(true) ? 0:1;
if(job.isSuccessful()) {
System.out.println("Job was successful");
} else if(!job.isSuccessful()) {
System.out.println("Job was not successful");
}
}
两种方式的输出是一样的。但是我不明白两者之间有什么区别? 哪个比另一个更受欢迎?
最佳答案
这篇文章很好地解释了 ToolRunner 的使用:ToolRunner
关于hadoop - 启动 MapReduce 作业的不同方式,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/41697229/