ML models like vectors or sparse vectors. Creating a pivot table in MapReduce can create a sparse vector.

output

A	(countryA = 1)(countryE = 1)(countryD = 1)(countryC = 1)(countryB = 2)
B	(countryF = 1)(countryA = 1)(countryE = 1)(countryD = 4)(countryC = 1)(countryB = 1)
C	(countryG = 1)(countryA = 1)(countryE = 1)(countryD = 4)(countryC = 3)(countryB = 1)

pivotdata.txt

A countryA
A countryB
A countryB
A countryC
A countryD
A countryE
B countryA
B countryB
B countryC
B countryD
B countryD
B countryD
B countryD
B countryE
B countryF
C countryA
C countryB
C countryC
C countryC
C countryC
C countryD
C countryD
C countryD
C countryD
C countryE
C countryG

PivotTable.java

/**
 * gradle clean
 * gradle build
 *
 * hadoop jar build/libs/pivot-table-1.0-SNAPSHOT.jar com.dvidr.PivotTable src/main/resources/pivotdata.txt src/main/resources/output
 *
 */

package com.dvidr;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import java.io.IOException;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;


public class PivotTableV2 extends Configured implements Tool {
    public static class AMap extends Mapper<LongWritable, Text, Text, Text> {
        private Text word = new Text();
        private Text word2 = new Text();

        @Override
        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            // file schema: hostname country
            String[] parts = value.toString().split("\\s");
            word.set(parts[0]);
            word2.set(parts[1]);
            context.write(word, word2);
        }
    }

    public static class AReduce extends Reducer<Text, Text, Text, Text> {
        private Text word = new Text();
        private Map<String, Integer> map = new HashMap<String, Integer>();


        private static String stringMap(Map mp) {
            Iterator it = mp.entrySet().iterator();
            StringBuilder sb = new StringBuilder();
            while (it.hasNext()) {
                Map.Entry pair = (Map.Entry) it.next();
                sb.append("(" + pair.getKey() + " = " + pair.getValue().toString() + ")");
                it.remove();
            }
            return sb.toString();
        }

        @Override
        public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
            for (Text value : values) {

                String factor = value.toString();
                Integer i = map.get(factor);
                if (i == null) {
                    i = 0;
                }
                map.put(factor, i + 1);
            }
            word.set(stringMap(map));
            context.write(key, word);
        }
    }


    public int run(String[] args) throws Exception {

        Configuration conf = getConf();
        Job job = Job.getInstance(conf);

        job.setJarByClass(PivotTable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        job.setMapperClass(AMap.class);
        job.setReducerClass(AReduce.class);
        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
        job.setNumReduceTasks(1);

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

        return (job.waitForCompletion(true) ? 0 : 1);

    }

    public static void main(String[] args) throws Exception {
        int exitCode = ToolRunner.run(new Configuration(), new PivotTableV2(), args);
        System.exit(exitCode);
    }
}