idea下mapreduce的wordcount
pom.xml
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.henu</groupId>
<artifactId>henu</artifactId>
<version>1.0-SNAPSHOT</version>
<name>henu</name>
<!-- FIXME change it to the project's website -->
<url>http://www.example.com</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>RELEASE</version>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.7.2</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>1.8</source>
<target>1.8</target>
<encoding>utf-8</encoding>
</configuration>
</plugin>
</plugins>
</build>
</project>
WordCount
package com.henu;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
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;
import java.io.IOException;
/**
* @author George
* @description
**/
public class WC {
public static class WCMapper extends Mapper<LongWritable, Text,Text, IntWritable>{
Text k1 = new Text();
IntWritable v1 = new IntWritable(1);
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] strings = line.split("\\s+");
for (String s : strings) {
k1.set(s);
context.write(k1,v1);
}
}
}
public static class WCReducer extends Reducer<Text, IntWritable,Text, IntWritable> {
int count;
IntWritable v2 = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
count = 0;
for (IntWritable value : values) {
count += value.get();
}
v2.set(count);
context.write(key,v2);
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(WC.class);
job.setMapperClass(WCMapper.class);
job.setReducerClass(WCReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.setInputPaths(job,new Path(args[0]));
FileOutputFormat.setOutputPath(job,new Path(args[1]));
job.waitForCompletion(true);
}
}
进行分区：
package com.henu;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
/**
* @author George
* @description
**/
public class WC {
public static class WCMapper extends Mapper<LongWritable, Text,Text, IntWritable>{
Text k1 = new Text();
IntWritable v1 = new IntWritable(1);
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] strings = line.split("\\s+");
for (String s : strings) {
k1.set(s);
context.write(k1,v1);
}
}
}
public static class WCReducer extends Reducer<Text, IntWritable,Text, IntWritable> {
int count;
IntWritable v2 = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
count = 0;
for (IntWritable value : values) {
count += value.get();
}
v2.set(count);
context.write(key,v2);
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(WC.class);
job.setMapperClass(WCMapper.class);
job.setReducerClass(WCReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
//map阶段设置分区
job.setPartitionerClass(MyPartitoner.class);
job.setNumReduceTasks(2);
FileInputFormat.setInputPaths(job,new Path(args[0]));
FileOutputFormat.setOutputPath(job,new Path(args[1]));
job.waitForCompletion(true);
}
private static class MyPartitoner extends Partitioner<Text,IntWritable> {
@Override
public int getPartition(Text text, IntWritable intWritable, int i) {
String kStr = text.toString();
return kStr.equalsIgnoreCase("hello")?0:1;
}
}
}
发送到linux上运行：
yarn jar henu-1.0-SNAPSHOT.jar com.henu.WC /hello /abc
