131 lines
3.5 KiB
Markdown
131 lines
3.5 KiB
Markdown
# B1 - Hadoop Word Count
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> [!NOTE]
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> These are generic instructions, need to refine them.
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---
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1. Copy and paste the following code in `WordCount.java` file:
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```java
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import java.io.IOException;
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import java.util.StringTokenizer;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.Path;
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import org.apache.hadoop.io.IntWritable;
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import org.apache.hadoop.io.Text;
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import org.apache.hadoop.mapreduce.Job;
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import org.apache.hadoop.mapreduce.Mapper;
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import org.apache.hadoop.mapreduce.Reducer;
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import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
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import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
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public class WordCount {
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// Mapper Class
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public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
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private final static IntWritable one = new IntWritable(1);
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private Text word = new Text();
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public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
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StringTokenizer itr = new StringTokenizer(value.toString());
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while (itr.hasMoreTokens()) {
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word.set(itr.nextToken().toLowerCase().replaceAll("[^a-zA-Z0-9]", ""));
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if (!word.toString().isEmpty()) {
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context.write(word, one);
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}
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}
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}
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}
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// Reducer Class
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public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
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private IntWritable result = new IntWritable();
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public void reduce(Text key, Iterable<IntWritable> values, Context context)
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throws IOException, InterruptedException {
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int sum = 0;
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for (IntWritable val : values) {
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sum += val.get();
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}
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result.set(sum);
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context.write(key, result);
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}
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}
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public static void main(String[] args) throws Exception {
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if (args.length != 2) {
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System.err.println("Usage: WordCount <input path> <output path>");
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System.exit(-1);
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}
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Configuration conf = new Configuration();
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Job job = Job.getInstance(conf, "word count");
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job.setJarByClass(WordCount.class);
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job.setMapperClass(TokenizerMapper.class);
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job.setCombinerClass(IntSumReducer.class); // optional
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job.setReducerClass(IntSumReducer.class);
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job.setOutputKeyClass(Text.class);
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job.setOutputValueClass(IntWritable.class);
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FileInputFormat.addInputPath(job, new Path(args[0]));
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FileOutputFormat.setOutputPath(job, new Path(args[1]));
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System.exit(job.waitForCompletion(true) ? 0 : 1);
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}
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}
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```
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2. Create an `input.txt` file in the same directory as the above code:
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```text
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This is a sample code.
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All the way from KSKA Git.
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Hello world
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Meow meow meow meow
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```
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3. In the same directory, open a `Terminal` window and compile the Java code:
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```shell
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javac -classpath `hadoop classpath` -d . WordCount.java
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jar cvf WordCount.jar *.class
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jar tf WordCount.jar
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```
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> [!NOTE]
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> Compiled code will be saved in the current working directory.
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4. Create an input and output directory in Hadoop FS:
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```shell
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hadoop fs -mkdir /user/hadoop/input
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hadoop fs -mkdir /user/hadoop/output
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```
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5. Upload the `input.txt` file to Hadoop FS:
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```shell
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hadoop fs -put input.txt /user/hadoop/input/
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```
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6. Run the WordCount job:
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```shell
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hadoop jar WordCount.jar WordCount /user/hadoop/input/input.txt /user/hadoop/output
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```
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7. View the output:
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```shell
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hadoop fs -cat /user/hadoop/output/part-r-00000
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```
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---
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