Word Count Map Reduce
Word Count in Map Reduce . No more counting Dollars will be counting Stars !!
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.6.0-cdh5.9.0<version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.6.0-cdh5.9.0<version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.6.0-cdh5.9.0<version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.6.0-cdh5.9.0</version>
</dependency>
</dependencies>
<repositories>
<repository>
<id>cloudera</id>
<url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
</repository>
</repositories>
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Mapper :
package com.big.data.mapreduce.wordcount;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
import java.util.StringTokenizer;
public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
// As TextInput Format has been used ,
//the key is the offset of line in the file , The actual line goes in the value
// Reuse the writables, to avoid GC.
private final IntWritable one = new IntWritable(1);
private Text word = new Text();
@Override
public void map(LongWritable key, Text value,
Mapper.Context context) throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
//Writable.Set() replaces the previous
//content of the writable Object with the new content
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
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Reducer
package com.big.data.mapreduce.wordcount;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
@Override
public void reduce(Text key, Iterable values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
context.write(key, new IntWritable(sum));
}
}
Key Take aways :
1. Map reads Key, Values And emit Key, Values .
2. Because the Input format is TextInputFormat the Map KEYIN = long and VALUEIN = line read
3. For counting the words, a given word across all the mapper need to be collected at a given reducer
to perform the counting
4. Writables have been reused , both in Mapper and Reducer. By creating less object we are avoiding GC
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Driver
package com.big.data.mapreduce.wordcount;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import java.io.IOException;
public class WordCountDriver extends Configured implements Tool {
//extends Configured implements Tool helps in argument parsing .
//Arguments need to passed as -Dkey=Value
public static final String INPUT_PATH = "input.path";
public static final String OUTPUT_PATH = "output.path";
public static void main(String[] args) throws Exception {
if(ToolRunner.run(new WordCountDriver(), args)!=0){
throw new IOException("Job has failed");
}
}
@Override
public int run(String[] args) throws Exception {
//The arguments passed has been split into Key value by ToolRunner
Configuration conf = getConf();
Path inputPath = new Path(conf.get(INPUT_PATH));
Path outputPath = new Path(conf.get(OUTPUT_PATH));
Job job = new Job(conf, this.getClass().toString());
FileInputFormat.setInputPaths(job, inputPath);
FileOutputFormat.setOutputPath(job, outputPath);
job.setJobName("WordCount");
job.setJarByClass(WordCountDriver.class);
//Set InputFormatClass
job.setInputFormatClass(TextInputFormat.class);
//Set OutPutFormat class
job.setOutputFormatClass(TextOutputFormat.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(WordCountMapper.class);
job.setCombinerClass(WordCountReducer.class);
job.setReducerClass(WordCountReducer.class);
// Driver polls to find out if the job has completed or not.
return job.waitForCompletion(true) ? 0 : 1;
}
}
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Working code can be found at Github
package com.big.data.mapreduce.wordcount;
import com.cloudera.org.joda.time.DateTime;
import org.apache.commons.io.FileUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.junit.AfterClass;
import org.junit.Assert;
import org.junit.BeforeClass;
import org.junit.Test;
import java.io.File;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import java.util.UUID;
public class WordCountDriverTest {
private final Configuration conf = new Configuration();
private static FileSystem fs;
private static final DateTime NOW = DateTime.now();
private static String baseDir;
private static String outputDir;
private static final String NEW_LINE_DELIMETER = "\n";
@BeforeClass
public static void startup() throws Exception {
Configuration conf = new Configuration();
//set the fs to file:/// which means the local fileSystem
conf.set("fs.default.name", "file:///");
conf.set("mapred.job.tracker", "local");
fs = FileSystem.getLocal(conf);
baseDir = "/tmp/mapreduce/wordcount/" + UUID.randomUUID().toString();
outputDir = baseDir + "/output";
File tempFile = new File(baseDir + "/input.txt");
String content = "My name is Maverick";
//Write the data into the local filesystem
FileUtils.writeStringToFile(tempFile, content, "UTF-8");
FileUtils.writeStringToFile(tempFile, NEW_LINE_DELIMETER, "UTF-8", true);
FileUtils.writeStringToFile(tempFile, content, "UTF-8", true);
}
@AfterClass
public static void cleanup() throws Exception {
//Delete the local filesystem folder after the Job is done
fs.delete(new Path(baseDir), true);
}
@Test
public void WordCount() throws Exception {
// Any argument passed with -DKey=Value will be parsed by ToolRunner
String[] args = new String[]{
"-D" + WordCountDriver.INPUT_PATH + "=" + baseDir,
"-D" + WordCountDriver.OUTPUT_PATH + "=" + outputDir };
WordCountDriver.main(args);
//Read the data from the outputfile
File outputFile = new File(outputDir + "/part-r-00000");
String fileToString = FileUtils.readFileToString(outputFile, "UTF-8");
Map<String, Integer> wordToCount = new HashMap<>();
//4 lines in output file, with one word per line
Arrays.stream(fileToString.split(NEW_LINE_DELIMETER)).forEach(e -> {
String[] wordCount = e.split("\t");
wordToCount.put(wordCount[0], Integer.parseInt(wordCount[1]));
});
//4 words .
Assert.assertEquals(4L, wordToCount.size());
Assert.assertEquals(2L, wordToCount.get("Maverick").longValue());
}
}