mapreduce设置setMapOutputKeyClass与setMapOutputValueClass原因

一般的mapreduce的wordcount程序如下：

public class WcMapper extends Mapper<LongWritable, Text, Text, LongWritable> {

    @Override
    protected void map(LongWritable key, Text value, Context ctx) throws IOException, InterruptedException {

        String[] words = value.toString().split(" ");
        for (int i = 0; i < words.length; i++) {
            ctx.write(new Text(words[i]), new LongWritable(1L));
        }
    }
}

public class WcReduer extends Reducer<Text, LongWritable, Text, LongWritable> {

    LongWritable count = new LongWritable();
    @Override
    protected void reduce(Text key, Iterable<LongWritable> values, Context ctx) throws IOException, InterruptedException {
        Iterator<LongWritable> itr = values.iterator();
        long sum = 0L;
        while (itr.hasNext()) {
            sum = sum + itr.next().get();
        }
        count.set(sum);
        ctx.write(key, count);
    }
}

驱动作业代码：

public class JobClient {

    public static void main(String[] args) throws Exception {

        Job job = Job.getInstance();
        job.setJarByClass(JobClient.class);
        job.setMapperClass(WcMapper.class);
        job.setReducerClass(WcReduer.class);

        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);

        job.setJobName("wordcount");
        FileInputFormat.addInputPath(job, new Path("/daxin/hadoop-mapreduce/words"));
        FileOutputFormat.setOutputPath(job, new Path("/daxin/hadoop-mapreduce/wordcount-result"));
        job.waitForCompletion(true);
    }
}

提交作业会报错：

Error: java.io.IOException: Type mismatch in key from map: expected org.apache.hadoop.io.LongWritable, received org.apache.hadoop.io.Text
	at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.collect(MapTask.java:1072)
	at org.apache.hadoop.mapred.MapTask$NewOutputCollector.write(MapTask.java:715)
	at org.apache.hadoop.mapreduce.task.TaskInputOutputContextImpl.write(TaskInputOutputContextImpl.java:89)
	at org.apache.hadoop.mapreduce.lib.map.WrappedMapper$Context.write(WrappedMapper.java:112)
	at com.daxin.blog.WcMapper.map(WcMapper.java:20)
	at com.daxin.blog.WcMapper.map(WcMapper.java:13)
	at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:146)
	at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:787)
	at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
	at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)
	at java.security.AccessController.doPrivileged(Native Method)
	at javax.security.auth.Subject.doAs(Subject.java:422)
	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657)
	at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)　

通过异常信息我们可以定位错误在源码中的位置：org.apache.hadoop.mapred.MapTask.MapOutputBuffer#collect，具体关键源码如下:

 public synchronized void collect(K key, V value, final int partition
                                     ) throws IOException {
      reporter.progress();
      if (key.getClass() != keyClass) {
        throw new IOException("Type mismatch in key from map: expected "
                              + keyClass.getName() + ", received "
                              + key.getClass().getName());
      }
      if (value.getClass() != valClass) {
        throw new IOException("Type mismatch in value from map: expected "
                              + valClass.getName() + ", received "
                              + value.getClass().getName());
      }
   .....
}

此处key.getClass可以确定是Text，需要确定keyClass是什么类型。下面就将确定一下keyClass类型，可以发现keyClass赋值源码：

 keyClass = (Class<K>)job.getMapOutputKeyClass();

　getMapOutputKeyClass源码：

  public Class<?> getMapOutputKeyClass() {
    Class<?> retv = getClass(JobContext.MAP_OUTPUT_KEY_CLASS, null, Object.class);
    if (retv == null) {
      retv = getOutputKeyClass();
    }
    return retv;
  }　

其中MAP_OUTPUT_KEY_CLASS则是获取map输出的key的类型，由于我们驱动代码没有设置因此此处得到的值为默认值null，接下在调用getOutputKeyClass方法：

  public Class<?> getOutputKeyClass() {
    return getClass(JobContext.OUTPUT_KEY_CLASS,
                    LongWritable.class, Object.class);
  }

 public static final String OUTPUT_KEY_CLASS = "mapreduce.job.output.key.class";

通过获取OUTPUT_KEY_CLASS的类型，OUTPUT_KEY_CLASS表示的是作业的key的输出类型，但是由于我们没有设置因此获取默认值为LongWritable。但是实际上我们的MapTask输出的key为Text，因而报如上类型不匹配错误。同理Map的value也有类似问题。为了解决此问题就需要显式的设置MapTask的Key、Value输出类型。代码如下：

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);

原文地址：https://www.cnblogs.com/leodaxin/p/8831092.html