import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Iterator;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
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.mapreduce.Job;

/**
 * Counts the number of occurrences of words.
 */
public class WordCount
{
    /**
     * Mapper class     
     */
    public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable>
    {
        private final static IntWritable one  = new IntWritable(1);
        private Text                     word = new Text();

        /**
         * Mapper output is word (Text) and count of number of occurrences.
         */        
        public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException
        {
            String line = value.toString();
            StringTokenizer tokenizer = new StringTokenizer(line, "| \t");
            while (tokenizer.hasMoreTokens())
            {
                this.word.set(tokenizer.nextToken());
                output.collect(this.word, one);
            }
        }
    }

    /**
     * Reducer class     
     */
    public static class Reduce extends MapReduceBase
            implements Reducer<Text, IntWritable, Text, IntWritable>
    {
        public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter)
                throws IOException
        {
            int sum = 0;
            while (values.hasNext())
            {
                sum += values.next().get();
            }
            output.collect(key, new IntWritable(sum));
        }
    }

    /**
     * Main method to submit the job to Hadoop cluster after configurating job parameters.
     * @param args 
     *      args[0] - input path, args[1] - output path
     * @throws Exception 
     *      if an error occurs
     */ 
    public static void main(String[] args) throws Exception
    {
        JobConf conf = new JobConf(WordCount.class);                // Name of class
        conf.setJobName("wordcount");                               // Name of job when executing with Hadoop

        conf.setOutputKeyClass(Text.class);                         // Type of output key
        conf.setOutputValueClass(IntWritable.class);                // Type of output value
        
        conf.setMapperClass(Map.class);                             // Class that implements mapper
        conf.setCombinerClass(Reduce.class);                        // Performs local reducing after map stage        
        conf.setReducerClass(Reduce.class);                         // Class that implements reducer

        conf.setInputFormat(TextInputFormat.class);                 // Indicate input files are in text format
        conf.setOutputFormat(TextOutputFormat.class);               // Indicate output files are in text format

        // This following line is required when executing remotely
        conf.set("mapred.jar","wordcount.jar");                     // Configure the JAR that stores the class.  
        
        Configuration conf2 = new Configuration();
        
        // Setup default input and output directories if not provided as arguments
        String outputPath = "/user/rlawrenc/outputwc/";
        String inputPath = "/user/hduser/data/nation.tbl";

        if ( args.length > 0 ) 
            inputPath = args[0];
        if ( args.length > 1 ) 
            outputPath = args[1];
                
        // Delete output path if it already exists as otherwise get an error if try to overwrite
        Path pt = new Path(outputPath);
        FileSystem fs = FileSystem.get(conf2);
        fs.delete(pt, true);        // Remove previous output directory       
        
        FileInputFormat.setInputPaths(conf, new Path(inputPath));
        FileOutputFormat.setOutputPath(conf, pt);
        
        Job job = new Job(conf, "wordcount");
        
        // Execute job
        job.waitForCompletion(true); 

        // Show output by iterating through all file parts (one part per reducer) and output lines
        FileStatus[] files = fs.listStatus(pt);
        int recordCount = 0;
        
        for (FileStatus file : files)
        {
            System.out.println("File: " + file.getPath());
            if ( file.isDir() || !file.getPath().toString().contains("part") ) continue;
            FSDataInputStream is = fs.open(file.getPath());
            BufferedReader br = new BufferedReader(new InputStreamReader(is));

            String s;
            while ((s = br.readLine()) != null)
            {
                System.out.println(s);
                recordCount++;
            }

            br.close();
        }
        fs.close();
        System.out.println("Total records printed: "+recordCount);
    }
}