Hadoop (Proof of Concept) by Bhavesh

# Ways to write Traditional WORD Count Program in Map Reduce, Apache PIG and HIVE in Hadoop Eco System

•  WordCount Program in Map Reduce

import java.io.IOException;

import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IntWritable;

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.output.FileOutputFormat;

public class WordCount {

  public static class TokenizerMapper

       extends Mapper<Object, Text, Text, IntWritable>{

    private final static IntWritable one = new IntWritable(1);

    private Text word = new Text();

    public void map(Object key, Text value, Context context

                    ) throws IOException, InterruptedException {

      StringTokenizer itr = new StringTokenizer(value.toString());

      while (itr.hasMoreTokens()) {

        word.set(itr.nextToken());

        context.write(word, one);

      }

    }

  }

  public static class IntSumReducer

       extends Reducer<Text,IntWritable,Text,IntWritable> {

    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values,

                       Context context

                       ) throws IOException, InterruptedException {

      int sum = 0;

      for (IntWritable val : values) {

        sum += val.get();

      }

      result.set(sum);

      context.write(key, result);

    }

  }

  public static void main(String[] args) throws Exception {

    Configuration conf = new Configuration();

    Job job = Job.getInstance(conf, "word count");

    job.setJarByClass(WordCount.class);

    job.setMapperClass(TokenizerMapper.class);

    job.setCombinerClass(IntSumReducer.class);

    job.setReducerClass(IntSumReducer.class);

    job.setOutputKeyClass(Text.class);

    job.setOutputValueClass(IntWritable.class);

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

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

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

  }

}

• Creating Jar file and execute Map Reduce Program

Output of Map Reduce.

•        WordCount Program in PIG

PIG Output

•           WordCount Program in HIVE

CREATE TABLE FILES (line STRING);

LOAD DATA INPATH 'docs' OVERWRITE INTO TABLE FILES;

CREATE TABLE word_counts AS

SELECT word, count(1) AS count FROM

(SELECT explode(split(line, ' ')) AS word FROM FILES) w

GROUP BY word

ORDER BY word;

HIVE Output