MapReduce作业在HADOOP-2.6.0中不起作用
我正在尝试运行wordcount示例 这是密码MapReduce作业在HADOOP-2.6.0中不起作用,hadoop,mapreduce,Hadoop,Mapreduce,我正在尝试运行wordcount示例 这是密码 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
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.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 WordCount {
public static class TokenizerMapper
extends Mapper<Object, Text, Text, IntWritable>{
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(Object key, Text value, Context context
) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
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();
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
我偶然发现了这个帖子
但解决方案对我不起作用您使用的是Hadoop 2.6和mapred软件包。我认为新的包名包括mapreduce。请按照示例运行正确的版本。您还可以使用和来理解两者之间的差异。最后,我解决了这个问题。我需要在warn-site.xml中添加以下属性
<property>
<name>yarn.resourcemanager.hostname</name>
<value>Hostname-of-your-RM</value>
<description>The hostname of the RM.</description>
</property>
warn.resourcemanager.hostname
您的RM的主机名
RM的主机名。
这将解决您的问题。请添加作业类、地图类和减速器类,以帮助您better@Ramzy我更新了我的问题我把它列为树。同样的问题你们是在集群还是在本地工作区运行。如果是本地的,您可以添加任何调试语句并查看,如果您得到任何异常,哪里可以得到调试语句?我的意思是在java代码中,以及您参考的文章中提到的日志中。即使我不确定,由于没有异常,它在哪里失败了。我观察到的一件事是,它建议使用ToolRunner接口。这是写作业的另一种方式。你能试试看它是否管用吗。此外,如果您的映射器被选中,那么它应该显示如下“mapreduce.Job:map 0%reduce 0%mapreduce.Job:map 100%reduce 0%
<property>
<name>yarn.resourcemanager.hostname</name>
<value>Hostname-of-your-RM</value>
<description>The hostname of the RM.</description>
</property>