Mac下报错'WARN security.UserGroupInformation: PriviledgedActionException as：用户名...No such file or directory'的一种解决方法

 1 package com.kaikeba.mapreduce;
 2 
 3 import org.apache.hadoop.io.IntWritable;
 4 import org.apache.hadoop.io.LongWritable;
 5 import org.apache.hadoop.io.Text;
 6 import org.apache.hadoop.mapreduce.Mapper;
 7 
 8 import java.io.IOException;
 9 
10 /**
11  * mapreduce‘s map
12  */
13 public class WordCountMap extends Mapper<LongWritable, Text,Text, IntWritable> {
14     //most application should override map method
15     @Override
16     protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
17         //split
18         String readLine = value.toString();
19         String[] words = readLine.split(" ");
20         //words output to disk
21         for(String word:words){
22             context.write(new Text(word),new IntWritable(1));
23         }
24     }
25 }

 1 package com.kaikeba.mapreduce;
 2 
 3 import org.apache.hadoop.io.IntWritable;
 4 import org.apache.hadoop.io.Text;
 5 import org.apache.hadoop.mapreduce.Reducer;
 6 
 7 import java.io.IOException;
 8 
 9 /**
10  * mapreduce‘s reduce
11  */
12 public class WordCountReduce extends Reducer<Text, IntWritable,Text,IntWritable> {
13     //should override reduce method
14     @Override
15     protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
16         //count words count
17         int count=0;
18         for(IntWritable i:values){
19             count+=i.get();
20         }
21         //output key value to hdfs
22         context.write(key,new IntWritable(count));
23     }
24 }

 1 package com.kaikeba.mapreduce;
 2 
 3 import org.apache.hadoop.conf.Configuration;
 4 import org.apache.hadoop.fs.Path;
 5 import org.apache.hadoop.io.IntWritable;
 6 import org.apache.hadoop.io.Text;
 7 import org.apache.hadoop.mapreduce.Job;
 8 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 9 import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
10 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
11 import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
12 
13 import java.io.IOException;
14 
15 /**
16  * mapreduce‘s main method, ‘WordCountMain‘ is mapreduce‘s job name
17  */
18 public class WordCountMain {
19     public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
20         //check args,args is input path and output path
21         if(args==null||args.length!=2){
22             System.out.println("please input path");
23             System.exit(0);//exit main method
24         }
25         //create mapreduce job
26         Configuration conf=new Configuration();
27         //if run mapreduce in cluster,set conf and mapred-site should set yarn
28         //conf.set("mapreduce.job.jar","/home/hadoop/IdeaProject/hadoop/target/hadoop-1.0-SNAPSHOT.jar");
29         //conf.set("mapreduce.app-submission.cross-platform","true");
30         //conf.set("mapreduce.framework.name","yarn");
31 
32         /**
33          * Creates a new Job with no particular Cluster and a given jobName.
34          * A Cluster will be created from the conf parameter only when it‘s needed
35          */
36         Job job=Job.getInstance(conf,WordCountMain.class.getSimpleName());//get class simplename
37         //set mapreduce job
38         job.setJarByClass(WordCountMain.class);//Set the Jar by finding where a given class came from
39         //set input/output format
40         job.setInputFormatClass(TextInputFormat.class);
41         job.setOutputFormatClass(TextOutputFormat.class);
42         //set input/output path
43         FileInputFormat.setInputPaths(job,new Path(args[0]));
44         FileOutputFormat.setOutputPath(job,new Path(args[1]));
45         //set map/reduce class
46         job.setMapperClass(WordCountMap.class);
47         job.setReducerClass(WordCountReduce.class);
48         //add combine class
49         job.setCombinerClass(WordCountReduce.class);
50         //set map/reduce output key-value type
51         //map
52         job.setMapOutputKeyClass(Text.class);
53         job.setMapOutputValueClass(IntWritable.class);
54         //reduce
55         job.setOutputKeyClass(Text.class);
56         job.setOutputValueClass(IntWritable.class);
57         //set job number ---> 4 reduce task
58         job.setNumReduceTasks(4);
59         //job commit
60         try{
61             job.waitForCompletion(true);
62         }catch(Exception e){
63             e.printStackTrace();
64         }
65     }
66 }