First install hadoop (if not installed yet) by,
1. Study and Configure Hadoop for Big Data
# Download sample.txt file (attached with this post)
# Paste sample.txt in your home folder
# Open terminal
# It will display your user name, we will use it later.
# Open eclipse->new java project->project name exp5b->new class-> WordCount
# Add following code in that class
package exp5b;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;
import org.apache.hadoop.util.GenericOptionsParser;
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()) {
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();
context.write(key, result);
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf,
if (otherArgs.length < 2) {
System.err.println(“Usage: wordcount <in> [<in>…] <out>”);
Job job = Job.getInstance(conf, “word count”);
for (int i = 0; i < otherArgs.length – 1; ++i) {
FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
new Path(otherArgs[otherArgs.length – 1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
# Save the file
# It will display some errors, so we are going to import three jar files in our project.
# Copy hadoop-mapreduce-client-core-2.7.1.jar from ~/hadoop/share/hadoop/mapreduce directory
# In eclipse-> right click on exp5b project- >paste
# Right click on pasted hadoop-mapreduce-client-core-2.7.1.jar-> Buid path-> add to buid path
# Copy hadoop-common-2.7.1.jar from ~/hadoop/share/hadoop/common directory
# In eclipse-> right click on exp5b project- >paste
# Right click on pasted hadoop-common-2.7.1.jar-> Buid path-> add to buid path
# Copy commons-cli-1.2.jar from ~/hadoop/share/hadoop/common/lib directory
# In eclipse-> right click on exp5b project- >paste
# Right click on pasted commons-cli-1.2.jar-> Buid path-> add to buid path
# In eclipse->Right click on project exp5b-> export->java->jar file->next-> select the export
destination -> /home/your_user_name/exp5b.jar -> next -> next -> select main class ->browse ->
WordCount -> finish
# exp5b.jar file will be created in your home folder
# Open terminal
# Now Start NameNode daemon and DataNode daemon:
# Make the HDFS directories required to execute MapReduce jobs
~/hadoop/bin/hdfs dfs -mkdir /user
~/hadoop/bin/hdfs dfs -mkdir /user/your_user_name
# Put sample.txt file in hdfs
~/hadoop/bin/hdfs dfs -put ~/sample.txt input_data
# Perform MapReduce job
~/hadoop/bin/hadoop jar ~/exp5b.jar input_data output_data
# Output
~/hadoop/bin/hdfs dfs -cat output_data/*
# Our task is done, so delete the distributed files (input_data & output_data)
~/hadoop/bin/hdfs dfs -rm -r input_data output_data
# Stop haddop