这个问题在这里已经有了答案：

使用自定义可写（1个答案）从hadoop map reduce作业输出列表
5年前关门了。
如何将arraylist作为值从Map器传递给reducer。
我的代码基本上有一些规则要处理，并且会根据这些规则创建新的值（字符串）。我在一个列表中维护所有的输出（在规则执行后生成），现在需要将这个输出（Map器值）发送到reducer，并且没有方法这样做。
有人能给我指个方向吗
添加代码

package develop;

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.MultipleOutputs;

import utility.RulesExtractionUtility;

public class CustomMap{

    public static class CustomerMapper extends Mapper<Object, Text, Text, Text> {
        private Map<String, String> rules;
        @Override
        public void setup(Context context)
        {

            try
            {
                URI[] cacheFiles = context.getCacheFiles();
                setupRulesMap(cacheFiles[0].toString());
            }
            catch (IOException ioe)
            {
                System.err.println("Error reading state file.");
                System.exit(1);
            }

        }

        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {

//          Map<String, String> rules = new LinkedHashMap<String, String>();
//          rules.put("targetcolumn[1]", "ASSIGN(source[0])");
//          rules.put("targetcolumn[2]", "INCOME(source[2]+source[3])");
//          rules.put("targetcolumn[3]", "ASSIGN(source[1]");

//          Above is the "rules", which would basically create some list values from source file

            String [] splitSource = value.toString().split(" ");

            List<String>lists=RulesExtractionUtility.rulesEngineExecutor(splitSource,rules);

//          lists would have values like (name, age) for each line from a huge text file, which is what i want to write in context and pass it to the reducer.
//          As of now i havent implemented the reducer code, as m stuck with passing the value from mapper.

//          context.write(new Text(), lists);---- I do not have a way of doing this

        }

        private void setupRulesMap(String filename) throws IOException
        {
            Map<String, String> rule = new LinkedHashMap<String, String>();
            BufferedReader reader = new BufferedReader(new FileReader(filename));
            String line = reader.readLine();
            while (line != null)
            {
                String[] split = line.split("=");
                rule.put(split[0], split[1]);
                line = reader.readLine();

                // rules logic
            }
            rules = rule;
        }
    }
    public static void main(String[] args) throws IllegalArgumentException, IOException, ClassNotFoundException, InterruptedException, URISyntaxException {

    Configuration conf = new Configuration();
    if (args.length != 2) {
        System.err.println("Usage: customerMapper <in> <out>");
        System.exit(2);
    }
    Job job = Job.getInstance(conf);
    job.setJarByClass(CustomMap.class);
    job.setMapperClass(CustomerMapper.class);
    job.addCacheFile(new URI("Some HDFS location"));

    URI[] cacheFiles= job.getCacheFiles();
    if(cacheFiles != null) {
        for (URI cacheFile : cacheFiles) {
            System.out.println("Cache file ->" + cacheFile);
        }
    }
    // job.setReducerClass(Reducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);

    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));

    System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}