Hadoop示例程序WordCount详解及实例

来源:互联网 发布:sql设置取值默认 编辑:程序博客网 时间:2024/05/11 05:07

1.图解MapReduce

 

 

 

2.简历过程:

Input:

Hello World Bye World

Hello Hadoop Bye Hadoop

Bye Hadoop Hello Hadoop

Map:

<Hello,1>

<World,1>

<Bye,1>

<World,1>

<Hello,1>

<Hadoop,1>

<Bye,1>

<Hadoop,1>

<Bye,1>

<Hadoop,1>

<Hello,1>

<Hadoop,1>

Sort:

<Bye,1>

<Bye,1>

<Bye,1>

<Hadoop,1>

<Hadoop,1>

<Hadoop,1>

<Hadoop,1>

<Hello,1>

<Hello,1>

<Hello,1>

<World,1>

<World,1>

Combine:

<Bye,1,1,1>

<Hadoop,1,1,1,1>

<Hello,1,1,1>

<World,1,1>

Reduce:

<Bye,3>

<Hadoop,4>

<Hello,3>

<World,2>

3.代码实例:

package com.felix;import java.io.IOException;import java.util.Iterator;import java.util.StringTokenizer;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.mapred.FileInputFormat;import org.apache.hadoop.mapred.FileOutputFormat;import org.apache.hadoop.mapred.JobClient;import org.apache.hadoop.mapred.JobConf;import org.apache.hadoop.mapred.MapReduceBase;import org.apache.hadoop.mapred.Mapper;import org.apache.hadoop.mapred.OutputCollector;import org.apache.hadoop.mapred.Reducer;import org.apache.hadoop.mapred.Reporter;import org.apache.hadoop.mapred.TextInputFormat;import org.apache.hadoop.mapred.TextOutputFormat;/** *  * 描述:WordCount explains by Felix * @author Hadoop Dev Group */public class WordCount{    /**     * MapReduceBase类:实现了Mapper和Reducer接口的基类(其中的方法只是实现接口,而未作任何事情)     * Mapper接口:     * WritableComparable接口:实现WritableComparable的类可以相互比较。所有被用作key的类应该实现此接口。     * Reporter 则可用于报告整个应用的运行进度,本例中未使用。      *      */    public static class Map extends MapReduceBase implements            Mapper<LongWritable, Text, Text, IntWritable>    {        /**         * LongWritable, IntWritable, Text 均是 Hadoop 中实现的用于封装 Java 数据类型的类,这些类实现了WritableComparable接口,         * 都能够被串行化从而便于在分布式环境中进行数据交换,你可以将它们分别视为long,int,String 的替代品。         */        private final static IntWritable one = new IntWritable(1);        private Text word = new Text();                /**         * Mapper接口中的map方法:         * void map(K1 key, V1 value, OutputCollector<K2,V2> output, Reporter reporter)         * 映射一个单个的输入k/v对到一个中间的k/v对         * 输出对不需要和输入对是相同的类型,输入对可以映射到0个或多个输出对。         * OutputCollector接口:收集Mapper和Reducer输出的<k,v>对。         * OutputCollector接口的collect(k, v)方法:增加一个(k,v)对到output         */        public void map(LongWritable key, Text value,                OutputCollector<Text, IntWritable> output, Reporter reporter)                throws IOException        {            String line = value.toString();            StringTokenizer tokenizer = new StringTokenizer(line);            while (tokenizer.hasMoreTokens())            {                word.set(tokenizer.nextToken());                output.collect(word, one);            }        }    }    public static class Reduce extends MapReduceBase implements            Reducer<Text, IntWritable, Text, IntWritable>    {        public void reduce(Text key, Iterator<IntWritable> values,                OutputCollector<Text, IntWritable> output, Reporter reporter)                throws IOException        {            int sum = 0;            while (values.hasNext())            {                sum += values.next().get();            }            output.collect(key, new IntWritable(sum));        }    }    public static void main(String[] args) throws Exception    {        /**         * JobConf:map/reduce的job配置类,向hadoop框架描述map-reduce执行的工作         * 构造方法:JobConf()、JobConf(Class exampleClass)、JobConf(Configuration conf)等         */        JobConf conf = new JobConf(WordCount.class);        conf.setJobName("wordcount");           //设置一个用户定义的job名称        conf.setOutputKeyClass(Text.class);    //为job的输出数据设置Key类        conf.setOutputValueClass(IntWritable.class);   //为job输出设置value类        conf.setMapperClass(Map.class);         //为job设置Mapper类        conf.setCombinerClass(Reduce.class);      //为job设置Combiner类        conf.setReducerClass(Reduce.class);        //为job设置Reduce类        conf.setInputFormat(TextInputFormat.class);    //为map-reduce任务设置InputFormat实现类        conf.setOutputFormat(TextOutputFormat.class);  //为map-reduce任务设置OutputFormat实现类        /**         * InputFormat描述map-reduce中对job的输入定义         * setInputPaths():为map-reduce job设置路径数组作为输入列表         * setInputPath():为map-reduce job设置路径数组作为输出列表         */        FileInputFormat.setInputPaths(conf, new Path(args[0]));        FileOutputFormat.setOutputPath(conf, new Path(args[1]));        JobClient.runJob(conf);         //运行一个job    }}


原文地址:http://blog.csdn.net/xw13106209/article/details/6116323
0 0
原创粉丝点击