Hadoop入门经典:WordCount

转：http://blog.csdn.net/jediael_lu/article/details/38705371

以下程序在hadoop1.2.1上测试成功。

本例先将源代码呈现，然后详细说明执行步骤，最后对源代码及执行过程进行分析。

一、源代码

 package org.jediael.hadoopdemo.wordcount;  

 import java.io.IOException;

 import java.util.StringTokenizer;  

 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.input.TextInputFormat;

 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

 import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;  

 public class WordCount {  

     public static class WordCountMap extends

             Mapper<LongWritable, Text, Text, IntWritable> {  

         private final IntWritable one = new IntWritable(1);

         private Text word = new Text();  

         public void map(LongWritable key, Text value, Context context)

                 throws IOException, InterruptedException {

             String line = value.toString();

             StringTokenizer token = new StringTokenizer(line);

             while (token.hasMoreTokens()) {

                 word.set(token.nextToken());

                 context.write(word, one);

             }

         }

     }  

     public static class WordCountReduce extends

             Reducer<Text, IntWritable, Text, IntWritable> {  

         public void reduce(Text key, Iterable<IntWritable> values,

                 Context context) throws IOException, InterruptedException {

             int sum = 0;

             for (IntWritable val : values) {

                 sum += val.get();

             }

             context.write(key, new IntWritable(sum));

         }

     }  

     public static void main(String[] args) throws Exception {

         Configuration conf = new Configuration();

         Job job = new Job(conf);

         job.setJarByClass(WordCount.class);

         job.setJobName("wordcount");  

         job.setOutputKeyClass(Text.class);

         job.setOutputValueClass(IntWritable.class);  

         job.setMapperClass(WordCountMap.class);

         job.setReducerClass(WordCountReduce.class);  

         job.setInputFormatClass(TextInputFormat.class);

         job.setOutputFormatClass(TextOutputFormat.class);  

         FileInputFormat.addInputPath(job, new Path(args[0]));

         FileOutputFormat.setOutputPath(job, new Path(args[1]));  

         job.waitForCompletion(true);

     }

 }

二、执行程序

1、从eclipse从导出至wordcount.jar，并上传至hadoop服务器，本例中，将程序上传至/home/jediael/project。

2、安装hadoop伪分布模式，可参考Hadoop1.2.1伪分布模式安装指南，本实例将运行在hadoop的伪公布环境中。

3、在HDFS中创建目录wcinput，用作输入目录，并将需要分析的文件复制到目录下。

[root@jediael conf]# hadoop fs -mkdir wcinput

[root@jediael conf]# hadoop fs -copyFromLocal * wcinput

[root@jediael conf]# hadoop fs -ls wcinput

Found 26 items

-rw-r--r-- 1 root supergroup 1524 2014-08-20 12:29 /user/root/wcinput/automaton-urlfilter.txt

-rw-r--r-- 1 root supergroup 1311 2014-08-20 12:29 /user/root/wcinput/configuration.xsl

-rw-r--r-- 1 root supergroup 131090 2014-08-20 12:29 /user/root/wcinput/domain-suffixes.xml

-rw-r--r-- 1 root supergroup 4649 2014-08-20 12:29 /user/root/wcinput/domain-suffixes.xsd

-rw-r--r-- 1 root supergroup 824 2014-08-20 12:29 /user/root/wcinput/domain-urlfilter.txt

-rw-r--r-- 1 root supergroup 3368 2014-08-20 12:29 /user/root/wcinput/gora-accumulo-mapping.xml

-rw-r--r-- 1 root supergroup 3279 2014-08-20 12:29 /user/root/wcinput/gora-cassandra-mapping.xml

-rw-r--r-- 1 root supergroup 3447 2014-08-20 12:29 /user/root/wcinput/gora-hbase-mapping.xml

-rw-r--r-- 1 root supergroup 2677 2014-08-20 12:29 /user/root/wcinput/gora-sql-mapping.xml

-rw-r--r-- 1 root supergroup 2993 2014-08-20 12:29 /user/root/wcinput/gora.properties

-rw-r--r-- 1 root supergroup 983 2014-08-20 12:29 /user/root/wcinput/hbase-site.xml

-rw-r--r-- 1 root supergroup 3096 2014-08-20 12:29 /user/root/wcinput/httpclient-auth.xml

-rw-r--r-- 1 root supergroup 3948 2014-08-20 12:29 /user/root/wcinput/log4j.properties

-rw-r--r-- 1 root supergroup 511 2014-08-20 12:29 /user/root/wcinput/nutch-conf.xsl

-rw-r--r-- 1 root supergroup 42610 2014-08-20 12:29 /user/root/wcinput/nutch-default.xml

-rw-r--r-- 1 root supergroup 753 2014-08-20 12:29 /user/root/wcinput/nutch-site.xml

-rw-r--r-- 1 root supergroup 347 2014-08-20 12:29 /user/root/wcinput/parse-plugins.dtd

-rw-r--r-- 1 root supergroup 3016 2014-08-20 12:29 /user/root/wcinput/parse-plugins.xml

-rw-r--r-- 1 root supergroup 857 2014-08-20 12:29 /user/root/wcinput/prefix-urlfilter.txt

-rw-r--r-- 1 root supergroup 2484 2014-08-20 12:29 /user/root/wcinput/regex-normalize.xml

-rw-r--r-- 1 root supergroup 1736 2014-08-20 12:29 /user/root/wcinput/regex-urlfilter.txt

-rw-r--r-- 1 root supergroup 18969 2014-08-20 12:29 /user/root/wcinput/schema-solr4.xml

-rw-r--r-- 1 root supergroup 6020 2014-08-20 12:29 /user/root/wcinput/schema.xml

-rw-r--r-- 1 root supergroup 1766 2014-08-20 12:29 /user/root/wcinput/solrindex-mapping.xml

-rw-r--r-- 1 root supergroup 1044 2014-08-20 12:29 /user/root/wcinput/subcollections.xml

-rw-r--r-- 1 root supergroup 1411 2014-08-20 12:29 /user/root/wcinput/suffix-urlfilter.txt

4、运行程序

[root@jediael project]# hadoop org.jediael.hadoopdemo.wordcount.WordCount wcinput wcoutput3

14/08/20 12:50:25 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.

14/08/20 12:50:26 INFO input.FileInputFormat: Total input paths to process : 26

14/08/20 12:50:26 INFO util.NativeCodeLoader: Loaded the native-hadoop library

14/08/20 12:50:26 WARN snappy.LoadSnappy: Snappy native library not loaded

14/08/20 12:50:26 INFO mapred.JobClient: Running job: job_201408191134_0005

14/08/20 12:50:27 INFO mapred.JobClient: map 0% reduce 0%

14/08/20 12:50:38 INFO mapred.JobClient: map 3% reduce 0%

14/08/20 12:50:39 INFO mapred.JobClient: map 7% reduce 0%

14/08/20 12:50:50 INFO mapred.JobClient: map 15% reduce 0%

14/08/20 12:50:57 INFO mapred.JobClient: map 19% reduce 0%

14/08/20 12:50:58 INFO mapred.JobClient: map 23% reduce 0%

14/08/20 12:51:00 INFO mapred.JobClient: map 23% reduce 5%

14/08/20 12:51:04 INFO mapred.JobClient: map 30% reduce 5%

14/08/20 12:51:06 INFO mapred.JobClient: map 30% reduce 10%

14/08/20 12:51:11 INFO mapred.JobClient: map 38% reduce 10%

14/08/20 12:51:16 INFO mapred.JobClient: map 38% reduce 11%

14/08/20 12:51:18 INFO mapred.JobClient: map 46% reduce 11%

14/08/20 12:51:19 INFO mapred.JobClient: map 46% reduce 12%

14/08/20 12:51:22 INFO mapred.JobClient: map 46% reduce 15%

14/08/20 12:51:25 INFO mapred.JobClient: map 53% reduce 15%

14/08/20 12:51:31 INFO mapred.JobClient: map 53% reduce 17%

14/08/20 12:51:32 INFO mapred.JobClient: map 61% reduce 17%

14/08/20 12:51:39 INFO mapred.JobClient: map 69% reduce 17%

14/08/20 12:51:40 INFO mapred.JobClient: map 69% reduce 20%

14/08/20 12:51:45 INFO mapred.JobClient: map 73% reduce 20%

14/08/20 12:51:46 INFO mapred.JobClient: map 76% reduce 23%

14/08/20 12:51:52 INFO mapred.JobClient: map 80% reduce 23%

14/08/20 12:51:53 INFO mapred.JobClient: map 84% reduce 23%

14/08/20 12:51:55 INFO mapred.JobClient: map 84% reduce 25%

14/08/20 12:51:59 INFO mapred.JobClient: map 88% reduce 25%

14/08/20 12:52:00 INFO mapred.JobClient: map 92% reduce 25%

14/08/20 12:52:02 INFO mapred.JobClient: map 92% reduce 29%

14/08/20 12:52:06 INFO mapred.JobClient: map 96% reduce 29%

14/08/20 12:52:07 INFO mapred.JobClient: map 100% reduce 29%

14/08/20 12:52:11 INFO mapred.JobClient: map 100% reduce 30%

14/08/20 12:52:15 INFO mapred.JobClient: map 100% reduce 100%

14/08/20 12:52:17 INFO mapred.JobClient: Job complete: job_201408191134_0005

14/08/20 12:52:18 INFO mapred.JobClient: Counters: 29

14/08/20 12:52:18 INFO mapred.JobClient: Job Counters

14/08/20 12:52:18 INFO mapred.JobClient: Launched reduce tasks=1

14/08/20 12:52:18 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=192038

14/08/20 12:52:18 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0

14/08/20 12:52:18 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0

14/08/20 12:52:18 INFO mapred.JobClient: Launched map tasks=26

14/08/20 12:52:18 INFO mapred.JobClient: Data-local map tasks=26

14/08/20 12:52:18 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=95814

14/08/20 12:52:18 INFO mapred.JobClient: File Output Format Counters

14/08/20 12:52:18 INFO mapred.JobClient: Bytes Written=123950

14/08/20 12:52:18 INFO mapred.JobClient: FileSystemCounters

14/08/20 12:52:18 INFO mapred.JobClient: FILE_BYTES_READ=352500

14/08/20 12:52:18 INFO mapred.JobClient: HDFS_BYTES_READ=247920

14/08/20 12:52:18 INFO mapred.JobClient: FILE_BYTES_WRITTEN=2177502

14/08/20 12:52:18 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=123950

14/08/20 12:52:18 INFO mapred.JobClient: File Input Format Counters

14/08/20 12:52:18 INFO mapred.JobClient: Bytes Read=244713

14/08/20 12:52:18 INFO mapred.JobClient: Map-Reduce Framework

14/08/20 12:52:18 INFO mapred.JobClient: Map output materialized bytes=352650

14/08/20 12:52:18 INFO mapred.JobClient: Map input records=7403

14/08/20 12:52:18 INFO mapred.JobClient: Reduce shuffle bytes=352650

14/08/20 12:52:18 INFO mapred.JobClient: Spilled Records=45210

14/08/20 12:52:18 INFO mapred.JobClient: Map output bytes=307281

14/08/20 12:52:18 INFO mapred.JobClient: Total committed heap usage (bytes)=3398606848

14/08/20 12:52:18 INFO mapred.JobClient: CPU time spent (ms)=14400

14/08/20 12:52:18 INFO mapred.JobClient: Combine input records=0

14/08/20 12:52:18 INFO mapred.JobClient: SPLIT_RAW_BYTES=3207

14/08/20 12:52:18 INFO mapred.JobClient: Reduce input records=22605

14/08/20 12:52:18 INFO mapred.JobClient: Reduce input groups=6749

14/08/20 12:52:18 INFO mapred.JobClient: Combine output records=0

14/08/20 12:52:18 INFO mapred.JobClient: Physical memory (bytes) snapshot=4799041536

14/08/20 12:52:18 INFO mapred.JobClient: Reduce output records=6749

14/08/20 12:52:18 INFO mapred.JobClient: Virtual memory (bytes) snapshot=19545337856

14/08/20 12:52:18 INFO mapred.JobClient: Map output records=22605

5、查看结果

root@jediael project]# hadoop fs -ls wcoutput3

Found 3 items

-rw-r--r-- 1 root supergroup 0 2014-08-20 12:52 /user/root/wcoutput3/_SUCCESS

drwxr-xr-x - root supergroup 0 2014-08-20 12:50 /user/root/wcoutput3/_logs

-rw-r--r-- 1 root supergroup 123950 2014-08-20 12:52 /user/root/wcoutput3/part-r-00000

[root@jediael project]# hadoop fs -cat wcoutput3/part-r-00000

!!      2

!ci.*.*.us      1

!co.*.*.us      1

!town.*.*.us    1

"AS     22

"Accept"        1

"Accept-Language"       1

"License");     22

"NOW"   1

"WiFi"  1

"Z"     1

"all"   1

"content"       1

"delete 1

"delimiter"     1

三、程序分析

1、WordCountMap类继承了org.apache.hadoop.mapreduce.Mapper，4个泛型类型分别是map函数输入key的类型，输入value的类型，输出key的类型，输出value的类型。

2、WordCountReduce类继承了org.apache.hadoop.mapreduce.Reducer，4个泛型类型含义与map类相同。

3、map的输出类型与reduce的输入类型相同，而一般情况下，map的输出类型与reduce的输出类型相同，因此，reduce的输入类型与输出类型相同。

4、hadoop根据以下代码确定输入内容的格式：

job.setInputFormatClass(TextInputFormat.class);

TextInputFormat是hadoop默认的输入方法，它继承自FileInputFormat。在TextInputFormat中，它将数据集切割成小数据集InputSplit，每一个InputSplit由一个mapper处理。此外，InputFormat还提供了一个RecordReader的实现，将一个InputSplit解析成<key,value>的形式，并提供给map函数：

key：这个数据相对于数据分片中的字节偏移量，数据类型是LongWritable。

value：每行数据的内容，类型是Text。

因此，在本例中，map函数的key/value类型是LongWritable与Text。

5、Hadoop根据以下代码确定输出内容的格式：

job.setOutputFormatClass(TextOutputFormat.class);

TextOutputFormat是hadoop默认的输出格式，它会将每条记录一行的形式存入文本文件，如

the 30

happy 23

……

Hadoop入门经典:WordCount的更多相关文章

Hadoop入门经典:WordCount 分类： A1_HADOOP 2014-08-20 14:43 2514人阅读评论(0) 收藏
以下程序在hadoop1.2.1上测试成功. 本例先将源代码呈现,然后详细说明执行步骤,最后对源代码及执行过程进行分析. 一.源代码 package org.jediael.hadoopdemo.wo ...
Hadoop入门程序WordCount的执行过程
首先编写WordCount.java源文件,分别通过map和reduce方法统计文本中每个单词出现的次数,然后按照字母的顺序排列输出, Map过程首先是多个map并行提取多个句子里面的单词然后分别列出 ...
Hadoop入门实例——WordCount统计单词
首先要说明的是运行Hadoop需要jdk1.6或以上版本,如果你还没有搭建好Hadoop集群,请参考我的另一篇文章: Linux环境搭建Hadoop伪分布模式马上进入正题. 1.启动Hadoop集群 ...
初识Hadoop入门介绍
初识hadoop入门介绍 Hadoop一直是我想学习的技术,正巧最近项目组要做电子商城,我就开始研究Hadoop,虽然最后鉴定Hadoop不适用我们的项目,但是我会继续研究下去,技多不压身. < ...
hadoop 入门实例【转】
原文链接:http://www.cnblogs.com/xia520pi/archive/2012/06/04/2534533.html 1.数据去重 "数据去重"主要是为了掌握 ...
一.hadoop入门须知
目录: 1.hadoop入门须知 2.hadoop环境搭建 3.hadoop mapreduce之WordCount例子 4.idea本地调试hadoop程序 5.hadoop 从mysql中读取数据 ...
Hadoop Mapreduce 案例 wordcount+统计手机流量使用情况
mapreduce设计思想概念:它是一个分布式并行计算的应用框架它提供相应简单的api模型,我们只需按照这些模型规则编写程序,即可实现"分布式并行计算"的功能. 案例一:word ...
大数据初级笔记二：Hadoop入门之Hadoop集群搭建
Hadoop集群搭建把环境全部准备好,包括编程环境. JDK安装版本要求: 强烈建议使用64位的JDK版本,这样的优势在于JVM的能够访问到的最大内存就不受限制,基于后期可能会学习到Spark技术 ...
转 Kafka入门经典教程
Kafka入门经典教程 http://www.aboutyun.com/thread-12882-1-1.html 问题导读 1.Kafka独特设计在什么地方?2.Kafka如何搭建及创建topic. ...

随机推荐

HackerRank and MiniMax
传送门 Sherlock and MiniMax Authored by darkshadows on May 07 2014 Problem Statement Watson gives Sherl ...
从注册流程分析如何安全退出多个Activity 多种方式（附DEMO）
退出Activity注册Android遍历目录(?)[+] 前言知识结构具体方案方案1 方法采用FLAG_ACTIVITY_CLEAR_TOP退出整个程序多activity 方案2 方 ...
IOS基础之 (十五）知识点
一 SEL 1. 方法的存储位置每个类的方法地址列表都存储在类对象中. 每个方法都有一个与之对应的SEL类型的对象. 根据一个SEL对象就可以找到方法的地址,进而调用方法. Person.h #im ...
codeforce 626E(二分）
E. Simple Skewness time limit per test 3 seconds memory limit per test 256 megabytes input standard ...
在Vs2012 中使用SQL Server 2012 Express LocalDB打开Sqlserver2012数据库
http://www.cnblogs.com/huangtailang/p/4221164.html 背景:个人电脑中使用的是VS2012,数据库为2008R2,最近需要打开一个SqlServer20 ...
jquery ajax提交表单数据的两种方式
http://www.kwstu.com/ArticleView/kwstu_201331316441313 貌似AJAX越来越火了,作为一个WEB程序开发者要是不会这个感觉就要落伍,甚至有可能在求职 ...
Spring学习8-Spring事务管理（注解式声明事务管理）
步骤一.在spring配置文件中引入<tx:>命名空间 <beans xmlns="http://www.springframework.org/schema/beans& ...
IDEA 从SVN检出项目相关配置
1.新建好一个工程,然后通过SVN检出项目 2.检出后一般tomcat的环境是配置好的,点击上方Project Structure按钮,弹出窗体,查看Project项,一般没问题,如果要配置就配置Pr ...
Note：JSON
JSON是JavaScript的原生格式,意味着在JavaScript中处理JSON数据不需要特殊的API或工具包,它是完全独立于语言的文本格式,可以把JavaScript对象中的一组对象转化为字符串 ...
B0BO TFS 安装指南（转载）
TFS2008安装过几次,每次都遇到点麻烦,结合网上的一些经验总结一下: Windows SharePoint Services 安装 Windows SharePoint Services你有两个选 ...

Hadoop入门经典:WordCount

Hadoop入门经典:WordCount的更多相关文章

随机推荐

热门专题