介绍怎样在Intellij Idea中通过创建mavenproject配置MapReduce的编程环境。
一、软件环境
我使用的软件版本号例如以下:
- Intellij Idea 2017.1
- Maven 3.3.9
- Hadoop伪分布式环境( 安装教程可參考)
二、创建mavenproject
打开Idea,file->new->Project,左側面板选择mavenproject。(假设仅仅跑MapReduce创建javaproject就可以，不用勾选Creat from archetype，假设想创建webproject或者使用骨架能够勾选)
设置GroupId和ArtifactId。下一步。
设置project存储路径。下一步。 
Finish之后，空白project的路径例如以下图所看到的。 
完整的project路径例如以下图所看到的：
三、加入maven依赖
在pom.xml加入依赖。对于hadoop 2.7.3版本号的hadoop，须要的jar包有下面几个：
- hadoop-common
- hadoop-hdfs
- hadoop-mapreduce-client-core
- hadoop-mapreduce-client-jobclient
log4j( 打印日志)
pom.xml中的依赖例如以下:
junit junit 4.12 test org.apache.hadoop hadoop-common 2.7.3 org.apache.hadoop hadoop-hdfs 2.7.3 org.apache.hadoop hadoop-mapreduce-client-core 2.7.3 org.apache.hadoop hadoop-mapreduce-client-jobclient 2.7.3 log4j log4j 1.2.17
四、配置log4j
在src/main/resources目录下新增log4j的配置文件log4j.properties。内容例如以下：
log4j.rootLogger = debug,stdout### 输出信息到控制抬 ###log4j.appender.stdout = org.apache.log4j.ConsoleAppenderlog4j.appender.stdout.Target = System.outlog4j.appender.stdout.layout = org.apache.log4j.PatternLayoutlog4j.appender.stdout.layout.ConversionPattern = [%-5p] %d{yyyy-MM-dd HH:mm:ss,SSS} method:%l%n%m%n 五、启动Hadoop
启动Hadoop，执行命令：
cd hadoop-2.7.3/./sbin/start-all.sh
訪问查看hadoop是否正常启动。
六、执行WordCount(从本地读取文件)
在project根目录下新建input目录，input目录下新增dream.txt，随便写入一些单词:
I have a dreama dream
在src/main/java目录下新建包。新增FileUtil.java，创建一个删除output文件的函数，以后就不用手动删除了。内容例如以下:
package com.mrtest.hadoop;import java.io.File;/** * Created by bee on 3/25/17. */public class FileUtil { public static boolean deleteDir(String path) { File dir = new File(path); if (dir.exists()) { for (File f : dir.listFiles()) { if (f.isDirectory()) { deleteDir(f.getName()); } else { f.delete(); } } dir.delete(); return true; } else { System.out.println("文件(夹)不存在!"); return false; } }} 编写WordCount的MapReduce程序WordCount.java，内容例如以下:
package com.mrtest.hadoop;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 java.io.IOException;import java.util.Iterator;import java.util.StringTokenizer;/** * Created by bee on 3/25/17. */public class WordCount { public static class TokenizerMapper extends Mapper { public static final IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(Object key, Text value, Context context) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) { this.word.set(itr.nextToken()); context.write(this.word, one); } } } public static class IntSumReduce extends Reducer { private IntWritable result = new IntWritable(); public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException { int sum = 0; IntWritable val; for (Iterator i = values.iterator(); i.hasNext(); sum += val.get()) { val = (IntWritable) i.next(); } this.result.set(sum); context.write(key, this.result); } } public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException { FileUtil.deleteDir("output"); Configuration conf = new Configuration(); String[] otherArgs = new String[]{ "input/dream.txt","output"}; if (otherArgs.length != 2) { System.err.println("Usage:Merge and duplicate removal "); System.exit(2); } Job job = Job.getInstance(conf, "WordCount"); job.setJarByClass(WordCount.class); job.setMapperClass(WordCount.TokenizerMapper.class); job.setReducerClass(WordCount.IntSumReduce.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); }} 执行完成以后。会在project根目录下添加一个output目录。打开output/part-r-00000，内容例如以下:
I 1a 2dream 2have 1
这里在main函数中新增了一个String类型的数组，假设想用main函数的args数组接受參数。在执行时指定输入和输出路径也是能够的。执行WordCount之前，配置Configuration并指定Program arguments就可以。
七、执行WordCount(从HDFS读取文件)
在HDFS上新建目录:
hadoop fs -mkdir /worddir
假设出现Namenode安全模式导致的不能创建目录提示：
mkdir: Cannot create directory /worddir. Name node is in safe mode.
执行下面命令关闭safe mode:
hadoop dfsadmin -safemode leave
上传本地文件:
hadoop fs -put dream.txt /worddir
改动otherArgs參数，指定输入为文件在HDFS上的路径:
String[] otherArgs = new String[]{ "hdfs://localhost:9000/worddir/dream.txt","output"}; 八、代码下载
代码下载地址: