Mapreduce(MR)设置多个job的任务运行

          MapReduce多个job任务其本质原理就是job2任务依赖job1任务的返回结果即job1的输出路径是job2的输入路径。

job2任务的启动依赖job1任务结束所返回的状态。

        依据自己的实际经验：多个job的串行或并行触发，我认为还是分开写几个程序，用脚本控制其执行顺序，这样便于程序的调试，管理。

           当然，选择使用那种情况也是依赖项目的需求而定。

           多个job依赖代码如下：

package more_job;

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class moreJob {
	private static final LongWritable num = new LongWritable(1);
	static int pv = 0;

	public static class MMap extends Mapper<LongWritable, Text, Text, LongWritable> {
		@Override
		protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, LongWritable>.Context context)
				throws IOException, InterruptedException {
			String line[] = value.toString().split("\t");
			String url = line[3];
			if(url.contains("baidu.com")){
				context.write(new Text(url), num);
			}
		}
	}
	
	public static class MRed extends Reducer<Text, LongWritable, Text, Text>{
		@Override
		protected void reduce(Text key, Iterable<LongWritable> value,
				Reducer<Text, LongWritable, Text, Text>.Context context) throws IOException, InterruptedException {
			for(LongWritable i :value){
				pv++;
			}
			context.write(new Text(key), new Text(Integer.toString(pv)));
		}
	}
	
	public static class MMap2 extends Mapper<LongWritable, Text, Text, LongWritable> {
		@Override
		protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, LongWritable>.Context context)
				throws IOException, InterruptedException {
			String line[] = value.toString().split("\t");
			String url = line[0].split("baidu.com")[0];
			context.write(new Text(url), num);
		}
	}
	
	public static class MRed2 extends Reducer<Text, LongWritable, Text, LongWritable>{
		@Override
		protected void reduce(Text key, Iterable<LongWritable> value,
				Reducer<Text, LongWritable, Text, LongWritable>.Context context) throws IOException, InterruptedException {
			for(LongWritable i :value){
				pv++;
			}
			context.write(new Text(key), new LongWritable(pv));
		}
	}
	
	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		Configuration conf = new Configuration();
                //job1的配置
		Job job1 = Job.getInstance(conf, "Job1");
		job1.setJarByClass(moreJob.class);
		job1.setMapperClass(MMap.class);
		job1.setReducerClass(MRed.class);
		job1.setMapOutputKeyClass(Text.class);
		job1.setMapOutputValueClass(LongWritable.class);
		FileInputFormat.addInputPath(job1, new Path(args[0]));   
                FileOutputFormat.setOutputPath(job1, new Path(args[1])); 
                FileSystem fs =new Path(args[1]).getFileSystem(conf);
                if(fs.exists(new Path(args[1]))){  
                      fs.delete(new Path(args[1]), true); 
                }  
		job1.setMaxMapAttempts(4);
		job1.setNumReduceTasks(50);
        
		/*	
		 * job1的输出路径是job2的输入路径
		 * 判断job1结束的返回状态，成功结束就执行job2
		 * job2只是依赖job1的结果路径，并不是依赖job1的输出结果的键值对类型。
		*/
			
		if(job1.waitForCompletion(true)){
                        //job2的配置
	                Job job2 = Job.getInstance(conf, "Job2");
			job2.setJarByClass(moreJob.class);
			job2.setMapperClass(MMap2.class);
			job2.setReducerClass(MRed2.class);
			job2.setMapOutputKeyClass(Text.class);
			job2.setMapOutputValueClass(LongWritable.class);
			job2.setOutputValueClass(LongWritable.class);
			FileInputFormat.addInputPath(job2, new Path(args[1]));   
	                FileOutputFormat.setOutputPath(job2, new Path(args[2]));
	                if(fs.exists(new Path(args[2]))){  
	                   fs.delete(new Path(args[2]), true); 
	                }  
			job2.setMaxMapAttempts(4);
			job2.setNumReduceTasks(50);
			System.exit(job2.waitForCompletion(true) ? 0 : 1); 
		}
	}
}