我遇到了Hadoop Map / Reduce工作的奇怪问题。作业正确提交,运行,但产生错误/奇怪的结果。似乎映射器和减速器根本不运行。输入文件从以下转换:
12
16
132
654
132
12
到
0 12
4 16
8 132
13 654
18 132
23 12
我假设第一列是映射器之前对的生成键,但mapper和reducer似乎都没有运行。当我使用旧的API时,工作运行正常。
下面提供了该工作的来源。我使用Hortonworks作为平台。
public class HadoopAnalyzer
{
public static class Map extends Mapper<LongWritable, Text, Text, IntWritable>
{
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
@Override
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException
{
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens())
{
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable>
{
@Override
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException
{
int sum = 0;
for (IntWritable val : values)
{
sum += val.get();
}
context.write(key, new IntWritable(sum));
}
}
public static void main(String[] args) throws Exception
{
JobConf conf = new JobConf(HadoopAnalyzer.class);
conf.setJobName("wordcount");
conf.set("mapred.job.tracker", "192.168.229.128:50300");
conf.set("fs.default.name", "hdfs://192.168.229.128:8020");
conf.set("fs.defaultFS", "hdfs://192.168.229.128:8020");
conf.set("hbase.master", "192.168.229.128:60000");
conf.set("hbase.zookeeper.quorum", "192.168.229.128");
conf.set("hbase.zookeeper.property.clientPort", "2181");
System.out.println("Executing job.");
Job job = new Job(conf, "job");
job.setInputFormatClass(InputFormat.class);
job.setOutputFormatClass(OutputFormat.class);
job.setJarByClass(HadoopAnalyzer.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
TextInputFormat.addInputPath(job, new Path("/user/usr/in"));
TextOutputFormat.setOutputPath(job, new Path("/user/usr/out"));
job.setMapperClass(Mapper.class);
job.setReducerClass(Reducer.class);
job.waitForCompletion(true);
System.out.println("Done.");
}
}
也许我错过了一些显而易见的事情,但是有人能说清楚这里可能出现的问题吗?
答案 0 :(得分:3)
输出符合预期,因为您使用了以下内容,
job.setMapperClass(Mapper.class);
job.setReducerClass(Reducer.class);
应该是 -
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
您使用Map和Reduce扩展了Mapper和Reducer类,但没有在您的工作中使用它们。