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mvn+eclipse构建hadoop项目并运作(超简单hadoop开发入门指南)

热度:79   发布时间:2016-04-22 23:54:41.0
mvn+eclipse构建hadoop项目并运行(超简单hadoop开发入门指南)

本文详述如何在windows开发环境下通过mvn+eclipse构建hadoop项目并运行

必备环境

  • windows7操作系统
  • eclipse-4.4.2
  • mvn-3.0.3及用mvn生成项目架构(参阅http://blog.csdn.net/tang9140/article/details/39157439)
  • hadoop-2.5.2(直接上hadoop官网http://hadoop.apache.org/下载hadoop-2.5.2.tar.gz并解压到某个目录)

windows7下环境配置

1、本地hadoop环境配置
添加环境变量HADOOP_HOME=E:\doc_api\ebook\hadoop-2.5.2
追加环境变量path内容:%HADOOP_HOME%\bin

2、bin下增加hadoop.dll,winutils.exe文件
从https://github.com/srccodes/hadoop-common-2.2.0-bin或从……下载hadoop.dll,winutils.exe,放置到${HADOOP_HOME}\bin目录下

构建hadoop项目

下面以经典的WordCount为例,构建我们第一个hadoop项目。

  • 引包

pom文件中加入依赖包

<dependency>    <groupId>org.apache.hadoop</groupId>    <artifactId>hadoop-mapreduce-client-core</artifactId>    <version>2.5.2</version></dependency><dependency>    <groupId>org.apache.hadoop</groupId>    <artifactId>hadoop-common</artifactId>    <version>2.5.2</version></dependency><dependency>    <groupId>org.apache.hadoop</groupId>    <artifactId>hadoop-hdfs</artifactId>    <version>2.5.2</version></dependency><dependency>    <groupId>org.apache.hadoop</groupId>    <artifactId>hadoop-mapreduce-client-common</artifactId>    <version>2.5.2</version></dependency>
  • 编写WordCount类如下
import java.io.IOException;import java.util.StringTokenizer;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.conf.Configured;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;import org.apache.hadoop.util.Tool;import org.apache.hadoop.util.ToolRunner;/** * @version 1.0 * @author tangqian */public class WordCount extends Configured implements Tool {    public static void main(String[] args) throws Exception {        int result = ToolRunner.run(new Configuration(),new WordCount(), args);        System.exit(result);    }    @Override    public int run(String[] args) throws Exception {        Path inputPath, outputPath;        if(args.length == 2){            inputPath = new Path(args[0]);            outputPath = new Path(args[1]);        }else{            System.out.println("usage <input> <output>");            return 1;        }        Configuration conf = getConf();        Job job = Job.getInstance(conf, "word count");        job.setJarByClass(WordCount.class);        job.setMapperClass(WordCountMapper.class);        job.setReducerClass(WordCountReducer.class);        job.setInputFormatClass(TextInputFormat.class);        job.setOutputFormatClass(TextOutputFormat.class);        job.setOutputKeyClass(Text.class);        job.setOutputValueClass(IntWritable.class);        FileInputFormat.addInputPath(job, inputPath);        FileOutputFormat.setOutputPath(job, outputPath);        return job.waitForCompletion(true) ? 0 : 1;    }    public static class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {        private final static IntWritable one = new IntWritable(1);        private Text word = new Text();        @Override        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {            StringTokenizer itr = new StringTokenizer(value.toString());            while (itr.hasMoreTokens()) {                word.set(itr.nextToken());                context.write(word, one);            }        }    }    public static class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {        private IntWritable result = new IntWritable();        @Override        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {            int sum = 0;            for (IntWritable value : values) {                sum += value.get();            }            result.set(sum);            context.write(key, result);        }    }}

然后在该类上右键Run As->Run Configurations->Arguments标签的Program arguments中指定输入路径和输出路径如下:

file:///e:/word.txt file:///e:/hadoop/result2

点Run即可运行该类,此时可在Console看到输出信息。等完成后,可到e:/hadoop/result2看到结果文件part-r-00000内容如下

is  1test    2this    1two 1

说明:由于是在本地hadoop单机模式下运行,故采用本地文件系统(以file://开头指定输入输出路径)。


hadoop-2.5.2集群安装指南(参阅http://blog.csdn.net/tang9140/article/details/42869531)

如何修改Windows7下的hosts文件?
hosts文件一般在C:\Windows\System32\drivers\etc目录下,在windows7下如果不是管理员身份登录,可能无权限修改,此时可右键hosts文件->属性->安全->编辑,选择当前登录用户,开放修改权限即可,具体操作如下图。
这里写图片描述

这里写图片描述

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