Eclipse 在Mapreduce中进行作业链接时，如何解决chainmapper不适用于参数错误？

我正在使用Hadoop1.2.1，EclipseJuno。我试图在一个Mapreduce作业中链接三个map任务。在eclipse中编写Mapreduce代码时，我遇到了一个错误，比如chainmapper不适用于参数，并且我无法设置inputpath。下面是我的mapreduce代码

 package org.myorg;

import java.io.IOException;
import java.net.URI;
import java.nio.file.FileSystem;
import java.util.StringTokenizer;

import javax.security.auth.login.Configuration;

import org.apache.hadoop.classification.InterfaceAudience.Private;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.MapRunnable;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.apache.hadoop.mapred.lib.ChainMapper;
import org.apache.hadoop.mapred.lib.ChainReducer;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.net.StaticMapping;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;


public class Recommand extends Configured implements Tool {



    public static class IdIndexMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text>{

        public void map(LongWritable key, Text val, OutputCollector<Text, Text> output,Reporter reporter)throws IOException{
            String[] ids;
            String ln=val.toString();
            ids=ln.split("\t");
            output.collect(new Text(ids[0]),new Text(ids[1]));

    }
}
    public static class FtrMapper extends MapReduceBase implements Mapper<Text, Text, Text, Text>{
        public void map(Text key, Text val, OutputCollector<Text, Text>output, Reporter reporter) throws IOException{
            String[] str;

            String lne=val.toString();
        while(lne.contains("M1024")){
                str=lne.split(",");
            String[] str1=new String[str.length];
                for(int i=0;i<str.length;i++){
                                if(str[i]=="M1024"){   //hre need to give id which we need to split;
                                    continue;
                                        }
                                str1[i]=str[i];
                                output.collect(key,new Text(str1[i]));                  
//                          System.out.println("str1 out:"+str[i]); 
                                    }
                            }


        }
    }

public static class CntMapper extends MapReduceBase implements Mapper<Text, Text, Text, IntWritable>{

    private final static IntWritable one=new IntWritable(1);
    private  Text word=new Text();
    public void map(Text key, Text val, OutputCollector<Text, IntWritable>output, Reporter reporter)throws IOException{
        String line = val.toString();
    StringTokenizer tokenizer = new StringTokenizer(line);
        while (tokenizer.hasMoreTokens()) {
            word.set(tokenizer.nextToken());
            output.collect(word, one);
                    }
                }
            }


public static class Reduce extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable>{
    public void reduce(Text key, Iterable<IntWritable>values, OutputCollector<Text, IntWritable>output, Reporter reporter)throws IOException{
        int sum=0;
        for(IntWritable val:values){
            sum+=val.get();
                    }
        output.collect(key,new IntWritable(sum));
                    }
                }   

static int printUsage() {
    System.out.println("recommand  ");
    ToolRunner.printGenericCommandUsage(System.out);
    return -1;
}

public int run(String[] args) throws Exception {
    JobConf conf = new JobConf(getConf(), Recommand.class);
    conf.setJobName("wordcount");

    if (args.length != 2) {
        System.out.println("ERROR: Wrong number of parameters: " +
                args.length + " instead of 2.");
        return printUsage();
    }
    FileInputFormat.setInputPaths(conf, args[0]);
    FileOutputFormat.setOutputPath(conf, new Path(args[1]));

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

    JobConf mapAConf = new JobConf(false);
    ChainMapper.addMapper(conf, IdIndexMapper.class, LongWritable.class, Text.class, Text.class, Text.class, true, mapAConf);

    JobConf mapBConf = new JobConf(false);
    ChainMapper.addMapper(conf, FtrMapper.class, Text.class, Text.class, Text.class, Text.class, true, mapBConf);

    JobConf mapCConf = new JobConf(false);
    ChainMapper.addMapper(conf, CntMapper.class, Text.class, Text.class, Text.class, IntWritable.class, true, mapBConf);

    JobConf reduceConf = new JobConf(false);
    ChainReducer.setReducer(conf, Reduce.class, Text.class, IntWritable.class, Text.class, IntWritable.class, true, reduceConf);

    JobClient.runJob(conf);
    return 0;
}

public static void main(String[] args) throws Exception {
    int res = ToolRunner.run(new org.apache.hadoop.conf.Configuration(), Recommand(), args);
    System.exit(res);
}
}

package org.myorg；
导入java.io.IOException；
导入java.net.URI；
导入java.nio.file.FileSystem；
导入java.util.StringTokenizer；
导入javax.security.auth.login.Configuration；
导入org.apache.hadoop.classification.InterfaceAudience.Private；
导入org.apache.hadoop.conf.Configured；
导入org.apache.hadoop.fs.Path；
导入org.apache.hadoop.io.*；
导入org.apache.hadoop.mapred.FileOutputFormat；
导入org.apache.hadoop.mapred.JobClient；
导入org.apache.hadoop.mapred.JobConf；
导入org.apache.hadoop.mapred.MapReduceBase；
导入org.apache.hadoop.mapred.MapRunnable；
导入org.apache.hadoop.mapred.OutputCollector；
导入org.apache.hadoop.mapred.Reducer；
导入org.apache.hadoop.mapred.Reporter；
导入org.apache.hadoop.mapred.TextInputFormat；
导入org.apache.hadoop.mapred.TextOutputFormat；
导入org.apache.hadoop.mapred.lib.ChainMapper；
导入org.apache.hadoop.mapred.lib.ChainReducer；
导入org.apache.hadoop.mapreduce.Job；
导入org.apache.hadoop.mapreduce.Mapper；
导入org.apache.hadoop.mapreduce.lib.input.FileInputFormat；
导入org.apache.hadoop.net.StaticMapping；
导入org.apache.hadoop.util.Tool；
导入org.apache.hadoop.util.ToolRunner；
公共类建议扩展配置的实现工具{
公共静态类IdIndexMapper扩展MapReduceBase实现Mapper{
公共void映射（LongWritable键、文本val、OutputCollector输出、Reporter报告器）引发IOException{
字符串[]id；
字符串ln=val.toString（）；
ids=ln.split（“\t”）；
collect（新文本（ids[0]）、新文本（ids[1]）；
}
}
公共静态类FtrMapper扩展MapReduceBase实现映射器{
公共无效映射（文本键、文本值、OutputCollectoroutput、Reporter）引发IOException{
字符串[]str；
字符串lne=val.toString（）；
而（lne.包含（“M1024”））{
str=lne.split（“，”）；
字符串[]str1=新字符串[str.length]；
对于（int i=0；i确保以下内容以避免此错误

这两个类都扩展了
Mapper
类
使用的
ChainMapper
类来自正确的API，以适用于代码的API为准
org.apache.hadoop.mapreduce.lib.chain.ChainMapper
或import
org.apache.hadoop.mapred.lib.ChainMapper
您能发布错误消息吗？第一条错误消息出现在“addmapper”上，即“addmapper方法（JobConf，ClassTry）尝试这篇文章的答案（可能重复）：是的，我尝试了与你给出的相同的内容。当我在eclipse中尝试该代码时，它显示了我所说的错误，在ChainMapper.addMapper的行上。我不知道如何解决它们。我不这么认为……上面提到的帖子的答案是imports
org.apache.hadoop.mapred.Mapper；
而不是
org.apache.hadoop.mapreduce.Mapper；
，就像你一样。你是吗那是什么？