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I'm still seeing some people struggling to run their own mapreduce applications using a command line. For those who are not java developers, here is some quick guidance.

Let's create a new directory and put our new java extension within it.

import org.apache.hadoop.conf.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.fs.Path;
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, args).getRemainingArgs();
    if (otherArgs.length != 2) {
      System.err.println("Usage: wordcount <in> <out>");
    Job job = new Job(conf, "word count");
    FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
    FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);

From the client-side, we need to be able to resolve external resources classes / libraries ( import lines ). Let's find out our hadoop classpath to resolve any dependency.:

-sh-4.1$ hadoop classpath
/usr/jdk64/jdk1.8.0_112/bin/javac -classpath $(/usr/hdp/current/hadoop-client/bin/hadoop classpath) -d job/ job/

Now, all the classes were turned into a .class, let's group them all into a single jar.

-sh-4.1$ /usr/jdk64/jdk1.8.0_112/bin/jar -cvf Test.jar -C job/ .

Execute the mapreduce program.

-sh-4.1$ hadoop jar Test.jar WordCount /tmp/sample_07.csv /tmp/output_mapred
17/11/05 23:41:50 INFO client.RMProxy: Connecting to ResourceManager at
17/11/05 23:41:51 INFO client.AHSProxy: Connecting to Application History server at
17/11/05 23:41:51 INFO hdfs.DFSClient: Created HDFS_DELEGATION_TOKEN token 12603 for bob1 on ha-hdfs:cluster2
17/11/05 23:41:51 INFO security.TokenCache: Got dt for hdfs://cluster2; Kind: HDFS_DELEGATION_TOKEN, Service: ha-hdfs:cluster2, Ident: (HDFS_DELEGATION_TOKEN token 12603 for bob1)
File Input Format Counters 
Bytes Read=46055
File Output Format Counters 
Bytes Written=36214
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Revision #:
2 of 2
Last update:
‎02-12-2020 02:43 AM
Updated by:
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