Question

我目前正在尝试弄清楚当你运行MapReduce作业时，通过在代码的某些位置制作一些system.out.println（）会发生什么，但是当作业运行时，知道那些print语句会在我的终端上打印。有人可以帮我弄清楚我到底做错了什么。

import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.OutputCommitter;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.StatusReporter;
import org.apache.hadoop.mapreduce.TaskAttemptID;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class WordCountJob {
    public static int iterations;
  public static class TokenizerMapper 
     extends Mapper<Object, Text, Text, IntWritable>{

 private final static IntWritable one = new IntWritable(1);
 private Text word = new Text();
@Override
 public void map(Object key, Text value, Context context
                ) throws IOException, InterruptedException {
    System.out.println("blalblbfbbfbbbgghghghghghgh");
  StringTokenizer itr = new StringTokenizer(value.toString());
  while (itr.hasMoreTokens()) {
    word.set(itr.nextToken());
    String myWord = itr.nextToken();
    int n = 0;
    while(n< 5){
        myWord = myWord+ "Test my appending words";
        n++;
    }
    System.out.println("Print my word:  "+myWord);
    word.set(myWord);
    context.write(word, one);
   }
 }
}

public static class IntSumReducer 
   extends Reducer<Text,IntWritable,Text,IntWritable> {
private IntWritable result = new IntWritable();

public void reduce(Text key, Iterable<IntWritable> values, 
                   Context context
                   ) throws IOException, InterruptedException {
  int sum = 0;
  for (IntWritable val : values) {
    sum += val.get();
  }
  result.set(sum);
  context.write(key, result);
  }
}

public static void main(String[] args) throws Exception {
 Configuration conf = new Configuration();
 TaskAttemptID taskid = new TaskAttemptID();
 TokenizerMapper my = new TokenizerMapper();

if (args.length != 3) {
  System.err.println("Usage: WordCountJob <in> <out> <iterations>");
  System.exit(2);
}
iterations = new Integer(args[2]);
Path inPath = new Path(args[0]);
Path outPath =  null;
for (int i = 0; i<iterations; ++i){
    System.out.println("Iteration number: "+i);
    outPath = new Path(args[1]+i);
    Job job = new Job(conf, "WordCountJob");
    job.setJarByClass(WordCountJob.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    FileInputFormat.addInputPath(job, inPath);
    FileOutputFormat.setOutputPath(job, outPath);
    job.waitForCompletion(true);
    inPath = outPath;
   }
 }
}

Answer 1

这取决于您提交工作的方式，我认为您是使用bin/hadoop jar yourJar.jar提交的吗？

您的System.out.println()仅在您的main方法中可用，这是因为mapper / reducer在不同JVM中的hadoop内执行，所有输出都被重定向到特殊日志文件（out / log-files）。我建议使用你自己的Apache-commons日志：

Log log = LogFactory.getLog(YOUR_MAPPER_CLASS.class)

因此请做一些信息记录：

log.info("Your message");

如果您处于“本地”模式，那么您可以在shell中看到此日志，否则此日志将存储在执行任务的计算机上的某个位置。请使用jobtracker的web UI查看这些日志文件，非常方便。默认情况下，作业跟踪器在端口50030上运行。

Answer 2

或者，您可以使用MultipleOutputs类并将所有日志数据重定向到一个输出文件（日志）。

MultipleOutputs<Text, Text> mos = new MultipleOutputs<Text, Text>(context);
Text tKey = new Text("key");
Text tVal = new Text("log message");
mos.write(tKey, tVal, <lOG_FILE>);

MapReduce Job未在终端上显示我的打印语句

2 个答案: