多个输入文件并将每个文件输出1个文件输出1个文件（Hadoop：MapReduce）

Question

我被困在单独的每个文件wordcount结果中1行。 我希望输出所有文件结果为1个文件，每个文件结果代表1行。

预期的output.txt格式

file1 1, 2, 3, 4, …, 100
file2 5, 2, 9, 6, …, 30

目前输出结果 每个文件的wordcount结果总结在一起

file1 123,22,31,...,100
file2 123,22,31,...,100

run（）的

MultipleInputs.addInputPath(job,in_path1,TextInputFormat.class,Map.class);
MultipleInputs.addInputPath(job,in_path2,TextInputFormat.class,Map.class);

地图

context.write(new Text("file1"),output);
context.write(new Text("file2"),output);

减少

context.write(new Text("file1"),new Text(sp.toString()));
context.write(new Text("file2"),new Text(sp.toString()));

地图

public static class Map extends Mapper<LongWritable, Text, Text, Text> {
        private static final HashMap<String, Object> counter = new HashMap<>();
        private Text output = new Text();

        private String mapToString(HashMap<String, Object> map) {
            StringBuilder sb = new StringBuilder();
            Iterator<Entry<String, Object>> iter = map.entrySet().iterator();
            while (iter.hasNext()) {
                Entry<String, Object> entry = iter.next();
                sb.append(entry.getKey());
                sb.append('=');
                sb.append(entry.getValue().toString());

                if (iter.hasNext()) {
                    sb.append(';').append(' ');
                }
            }
            return sb.toString();
        }

        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            // TODO: Get filename
            String line = value.toString();
            StringTokenizer tokenizer = new StringTokenizer(line);
            while (tokenizer.hasMoreTokens()) {
                String token = tokenizer.nextToken();
                if (!counter.containsKey(token)) {
                    counter.put(token, 1);
                } else {
                    counter.put(token, (Integer) counter.get(token) + 1);
                }
            }
            output.set(mapToString(counter));
            context.write(new Text("filename1"), output);
        }
    }

减少

public static class Reduce extends Reducer<Text, Text, Text, Text> {

        public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {

            int number = 0;
            System.out.println(key);
            for (Text val : values) { // val line record
                String[] input = val.toString().split(";\\s");
                for (int i = 0; i < input.length; i++) {
                    String[] temp = input[i].split("=");
                    String topValue = temp[0];
                    topValue = temp[0].replaceAll("[^a-zA-Z0-9]", "");
                    topValue = topValue.toLowerCase();

                    if (resultMap.containsKey(topValue)) {
                        int original = resultMap.get(topValue);
                        int sum = original + Integer.parseInt(temp[1]);
                        resultMap.put(topValue, sum);
                    }

                }

            }


        }

         @Override
            protected void cleanup(Context context) throws IOException,
                    InterruptedException {
             StringBuilder sp = new StringBuilder();

                System.out.println("MapSize: " + resultMap);
                int i = 0;
                Iterator iterator = resultMap.entrySet().iterator();




                while (iterator.hasNext()) {


                    Entry me2 = (Entry) iterator.next();
                    //System.out.println("key : " + me2.getKey());
                    sp.append(me2.getKey());
                    sp.append(":");
                    sp.append(me2.getValue());
                    System.out.println(me2.getValue());
                    sp.append(",");
                }

                context.write(new Text("file1"), new Text(sp.toString()));
                context.write(new Text("file2"), new Text(sp.toString()));


            }
    }

我卡在两个文件字数组合在一起。我希望在1行中打印每个文件字数。