单词计数-MapReduceJob

pom文件

<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.zuoyan</groupId>
	<artifactId>hadoop</artifactId>
	<version>0.0.1-SNAPSHOT</version>
	<packaging>jar</packaging>

	<name>hadoop</name>
	<url>http://maven.apache.org</url>

	<properties>
		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
	</properties>

	<dependencies>
		<dependency>
			<groupId>junit</groupId>
			<artifactId>junit</artifactId>
			<version>3.8.1</version>
		</dependency>
		<!-- https://mvnrepository.com/artifact/org.apache.hadoop/hadoop-client -->
		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-client</artifactId>
			<version>3.0.0</version>
		</dependency>
		<!-- https://mvnrepository.com/artifact/com.janeluo/ikanalyzer -->
		<dependency>
		    <groupId>com.janeluo</groupId>
		    <artifactId>ikanalyzer</artifactId>
		    <version>2012_u6</version>
		</dependency>
	</dependencies>
	<build>
		<plugins>
			<plugin>
				<artifactId>maven-assembly-plugin</artifactId>
				<configuration>
					<appendAssemblyId>false</appendAssemblyId>
					<descriptorRefs>
						<descriptorRef>jar-with-dependencies</descriptorRef>
					</descriptorRefs>
					<archive>
						<manifest>
							<!-- 此处指定main方法入口的class -->
							<mainClass>com.zuoyan.hadoop.FirstMapReduceJob</mainClass>
<!-- 							<mainClass>com.geotmt.hadoop.hdfs.FirstMapReduceJob</mainClass> -->
						</manifest>
					</archive>
				</configuration>
				<executions>
					<execution>
						<id>make-assembly</id>
						<phase>package</phase>
						<goals>
							<goal>assembly</goal>
						</goals>
					</execution>
				</executions>
			</plugin>
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-compiler-plugin</artifactId>
				<version>3.6.2</version>
				<configuration>
					<source>1.8</source>
					<target>1.8</target>
					<encoding>UTF-8</encoding>
				</configuration>
			</plugin>
		</plugins>
	</build>
</project>

　　

单词计数-实现

package com.zuoyan.hadoop;
import java.io.ByteArrayInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.Reader;

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;
import org.apache.hadoop.util.GenericOptionsParser;
import org.wltea.analyzer.core.IKSegmenter;
import org.wltea.analyzer.core.Lexeme;

/**
 * 单词计数
 *
 */
public class FirstMapReduceJob {

    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 {
            /*
             * 默认英文分词
             *
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                context.write(word, one);
            }
            */
        	/*
        	 * 中文分词-使用IK分词器分词
        	 */
            byte[] bytes = value.getBytes();
            InputStream inputStream = new ByteArrayInputStream(bytes);
            Reader reader = new InputStreamReader(inputStream);
            IKSegmenter iKSegmenter = new IKSegmenter(reader,true);
            Lexeme t;
            while((t=iKSegmenter.next()) != null){
            	context.write(new Text(t.getLexemeText()), new IntWritable(1));
            }

            //方案二，获取文件信息
//            context.getInputSplit().getLocationInfo();

        }
    }

    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 {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length != 2) {
            System.err.println("Usage: wordcount <in> <out>");
            System.exit(2);
        }
        Job job = new Job(conf, "word count");
        job.setJarByClass(FirstMapReduceJob.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}