Question

我想创建自己的地图减少工作。

地图类的输出是：文本（键），文本（值）

reduce类的输出是：Text，Intwritable

我尝试以下列方式实现它：

import java.io.IOException;
import java.util.*;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.util.*;

public class artistandTrack {

   public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text> {
     private final static IntWritable one = new IntWritable(1);
     private Text word = new Text();

     public void map(LongWritable key, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException {
       String line = value.toString();
           String[] names=line.split(" ");
           Text artist_name = new Text(names[2]);
           Text track_name = new Text(names[3]);               

 output.collect(artist_name,track_name);
     }
   }

   public static class Reduce extends MapReduceBase implements Reducer<Text, Text, Text, IntWritable> {
     public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
       int sum = 0;
       while (values.hasNext()) {
         sum += 1;
             Text x1=values.next();
                     }
       output.collect(key, new IntWritable(sum));
     }
   }

   public static void main(String[] args) throws Exception {
     JobConf conf = new JobConf(artistandTrack.class);
     conf.setJobName("artisttrack");

     conf.setOutputKeyClass(Text.class);
     conf.setOutputValueClass(IntWritable.class);

         conf.setMapOutputKeyClass(Text.class);
         conf.setMapOutputValueClass(Text.class);

     conf.setMapperClass(Map.class);
     conf.setCombinerClass(Reduce.class);
     conf.setReducerClass(Reduce.class);

     conf.setInputFormat(TextInputFormat.class);
     conf.setOutputFormat(TextOutputFormat.class);

     FileInputFormat.setInputPaths(conf, new Path(args[0]));
     FileOutputFormat.setOutputPath(conf, new Path(args[1]));

     JobClient.runJob(conf);
   }
}

当我尝试运行它时，它显示以下输出并终止

    WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/10/17 06:09:15 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
14/10/17 06:09:15 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
14/10/17 06:09:16 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized
14/10/17 06:09:18 WARN mapreduce.JobSubmitter: Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
14/10/17 06:09:19 INFO mapred.FileInputFormat: Total input paths to process : 1
14/10/17 06:09:19 INFO mapreduce.JobSubmitter: number of splits:1
14/10/17 06:09:19 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local803195645_0001
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/staging/userloki803195645/.staging/job_local803195645_0001/job.xml:an attempt to override final  parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/staging/userloki803195645/.staging/job_local803195645_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/local/localRunner/userloki/job_local803195645_0001/job_local803195645_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/local/localRunner/userloki/job_local803195645_0001/job_local803195645_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
14/10/17 06:09:20 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
14/10/17 06:09:20 INFO mapreduce.Job: Running job: job_local803195645_0001
14/10/17 06:09:20 INFO mapred.LocalJobRunner: OutputCommitter set in config null
14/10/17 06:09:20 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapred.FileOutputCommitter
14/10/17 06:09:20 INFO mapred.LocalJobRunner: Waiting for map tasks
14/10/17 06:09:20 INFO mapred.LocalJobRunner: Starting task: attempt_local803195645_0001_m_000000_0
14/10/17 06:09:20 INFO mapred.Task:  Using ResourceCalculatorProcessTree : [ ]
14/10/17 06:09:20 INFO mapred.MapTask: Processing split: hdfs://localhost:54310/project5/input/sad.txt:0+272
14/10/17 06:09:21 INFO mapred.MapTask: numReduceTasks: 1
14/10/17 06:09:21 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
14/10/17 06:09:21 INFO mapreduce.Job: Job job_local803195645_0001 running in uber mode : false
14/10/17 06:09:21 INFO mapreduce.Job:  map 0% reduce 0%
14/10/17 06:09:22 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
14/10/17 06:09:22 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
14/10/17 06:09:22 INFO mapred.MapTask: soft limit at 83886080
14/10/17 06:09:22 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600  
14/10/17 06:09:22 INFO mapred.MapTask: kvstart = 26214396; length = 6553600 
14/10/17 06:09:25 INFO mapred.LocalJobRunner: 
14/10/17 06:09:25 INFO mapred.MapTask: Starting flush of map output
14/10/17 06:09:25 INFO mapred.MapTask: Spilling map output
14/10/17 06:09:25 INFO mapred.MapTask: bufstart = 0; bufend = 120; bufvoid = 104857600
14/10/17 06:09:25 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214384(104857536); length = 13/6553600
14/10/17 06:09:25 INFO mapred.LocalJobRunner: map task executor complete.
14/10/17 06:09:25 WARN mapred.LocalJobRunner: job_local803195645_0001
***java.lang.Exception: java.io.IOException: wrong value class: class         org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text
at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:522)
Caused by: java.io.IOException: wrong value class: class  org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text
at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:199)
at org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:1307)
at artistandTrack$Reduce.reduce(artistandTrack.java:44)
at artistandTrack$Reduce.reduce(artistandTrack.java:37)
at org.apache.hadoop.mapred.Task$OldCombinerRunner.combine(Task.java:1572)
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.sortAndSpill(MapTask.java:1611)
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.flush(MapTask.java:1462)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:437)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:342)
at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:243)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)***


14/10/17 06:09:26 INFO mapreduce.Job: Job job_local803195645_0001 failed with state FAILED due to: NA
14/10/17 06:09:26 INFO mapreduce.Job: Counters: 11
Map-Reduce Framework
    Map input records=4
    Map output records=4
    Map output bytes=120
    Map output materialized bytes=0
    Input split bytes=97
    Combine input records=0
    Combine output records=0
    Spilled Records=0
    Failed Shuffles=0
    Merged Map outputs=0
File Input Format Counters 
    Bytes Read=272
Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:836)
at artistandTrack.main(artistandTrack.java:68)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at    sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)

来自哪个错误的班级

java.lang.Exception: java.io.IOException: wrong value class: class         org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text

和

为什么工作失败

Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:836)
at artistandTrack.main(artistandTrack.java:68)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at      sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)

我不明白哪里出错了。任何帮助

Answer 1

我认为问题在于：

conf.setCombinerClass(Reduce.class);

您的Map会产生一对Text和Text，然后您的combiner接受它并生成一对Text和IntWritable ，但是您的Reducer无法接受IntWritable作为值，因此会抛出异常。尝试使用Combiner设置删除行。

Answer 2

使用下面的Main：

 public static void main(String[] args) throws Exception {
 JobConf conf = new JobConf(artistandTrack.class);
 conf.setJobName("artisttrack");

 FileInputFormat.setInputPaths(conf, new Path(args[0]));
 FileOutputFormat.setOutputPath(conf, new Path(args[1]));

 conf.setMapperClass(Map.class);
 //conf.setCombinerClass(Reduce.class);
 conf.setReducerClass(Reduce.class);

 //conf.setOutputKeyClass(Text.class);
 //conf.setOutputValueClass(IntWritable.class);

 conf.setMapOutputKeyClass(Text.class);
 conf.setMapOutputValueClass(Text.class);

 conf.setInputFormat(TextInputFormat.class);
 conf.setOutputFormat(TextOutputFormat.class);

 JobClient.runJob(conf);
}

如何定义我们自己的地图并减少类

2 个答案: