# B1 - Hadoop Word Count

> [!NOTE]
> These are generic instructions, need to refine them.

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1. Copy and paste the following code in `WordCount.java` file:

```java
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 {

    // Mapper Class
    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().toLowerCase().replaceAll("[^a-zA-Z0-9]", ""));
                if (!word.toString().isEmpty()) {
                    context.write(word, one);
                }
            }
        }
    }

    // Reducer Class
    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 {
        if (args.length != 2) {
            System.err.println("Usage: WordCount <input path> <output path>");
            System.exit(-1);
        }

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

        job.setJarByClass(WordCount.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class); // optional
        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);
    }
}
```

2. Create an `input.txt` file in the same directory as the above code:

```text
This is a sample code.
All the way from KSKA Git.
Hello world
Meow meow meow meow
```

3. In the same directory, open a `Terminal` window and compile the Java code:

```shell
javac -classpath `hadoop classpath` -d . WordCount.java
jar cvf WordCount.jar *.class
jar tf WordCount.jar
```

> [!NOTE]
> Compiled code will be saved in the current working directory.

4. Create an input and output directory in Hadoop FS:

```shell
hadoop fs -mkdir /user/hadoop/input
hadoop fs -mkdir /user/hadoop/output
```

5. Upload the `input.txt` file to Hadoop FS:

```shell
hadoop fs -put input.txt /user/hadoop/input/
```

6. Run the WordCount job:

```shell
hadoop jar WordCount.jar WordCount /user/hadoop/input/input.txt /user/hadoop/output
```

7. View the output:

```shell
hadoop fs -cat /user/hadoop/output/part-r-00000
```

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